presentations of kidney injury

Acute Kidney Injury (AKI) Clinical Presentation

• Author: Biruh T Workeneh, MD, FASN; Chief Editor: Vecihi Batuman, MD, FASN  more...
• Sections Acute Kidney Injury (AKI)
• Practice Essentials
• Pathophysiology
• Epidemiology
• Patient Education
• Physical Examination
• Approach Considerations
• Kidney Function Studies
• CBC, Peripheral Smear, and Serology
• Fractional Excretion of Sodium and Urea
• Bladder Pressure
• Emerging Biomarkers
• Furosemide Stress Testing
• Ultrasonography
• Nuclear Scanning
• Aortorenal Angiography
• Kidney Biopsy
• Vasodilators
• Dietary Modification
• Prevention of Contrast-Induced Nephropathy
• Long-Term Monitoring
• Prevention of Perioperative Nephropathy
• Medication Summary
• Diuretics, Loop
• Inotropic Agents
• Calcium Channel Blockers
• Antidotes, Other
• Questions & Answers
• Media Gallery

A detailed and accurate history is crucial for diagnosing acute kidney injury (AKI) and determining treatment. Distinguishing AKI from chronic kidney disease is important, yet making the distinction can be difficult; chronic kidney disease is itself an important risk factor for AKI. [ 62 ]  A history of chronic symptoms—months of fatigue, weight loss, anorexia, nocturia, sleep disturbance, and pruritus—suggests chronic kidney disease. AKI can cause identical symptoms, but over a shorter course.

It is important to elicit a history of any of the following etiologic factors:

• Volume restriction (eg, low fluid intake, gastroenteritis)
• Nephrotoxic drug ingestion (eg, nonsteroidal anti-inflammatory drugs [NSAIDs], aminoglycosides) [ 62 ] Ref 60
• Exposure to iodinated contrast agents within the past week  [ 62 ]
• Trauma or unaccustomed exertion
• Blood loss or transfusions
• Exposure to toxic substances, such as ethyl alcohol or ethylene glycol
• Exposure to mercury vapors, lead, cadmium, or other heavy metals, which can be encountered in welders and miners

People with the following comorbid conditions are at a higher risk for developing AKI:

• Hypertension
• Chronic heart failure
• Liver disease
• Obesity [ 63 , 64 , 65 , 66 ]
• Multiple myeloma
• Chronic infection
• Myeloproliferative disorder
• Connective tissue disorders
• Autoimmune diseases

Urine output history can be useful. Oliguria generally favors AKI. Abrupt anuria suggests acute urinary obstruction, acute severe glomerulonephritis, or embolic renal artery occlusion. A gradually diminishing urine output may indicate a urethral stricture or bladder outlet obstruction due to prostate enlargement.

Because of a decrease in functioning nephrons, even a trivial nephrotoxic insult may cause AKI to be superimposed on chronic kidney insufficiency.

AKI has a long differential diagnosis. The history can help to classify the pathophysiology of AKI as prerenal, intrinsic, or postrenal failure, and it may suggest some specific etiologies. (See Overview/Etiology .)

Prerenal failure

Patients commonly present with symptoms related to hypovolemia, including thirst, decreased urine output, dizziness, and orthostatic hypotension. Ask about volume loss from vomiting, diarrhea, sweating, polyuria, or hemorrhage. Patients with advanced heart failure leading to depressed renal perfusion may present with orthopnea and paroxysmal nocturnal dyspnea.

Elders with vague mental status change are commonly found to have prerenal or normotensive ischemic AKI. Insensible fluid losses can result in severe hypovolemia in patients with restricted fluid access and should be suspected in elderly patients and in comatose or sedated patients.

Intrinsic kidney failure

Patients can be divided into those with glomerular etiologies and those with tubular etiologies of AKI. Nephritic syndrome of hematuria, edema, and hypertension indicates a glomerular etiology for AKI. Query about prior throat or skin infections. Acute tubular necrosis (ATN) should be suspected in any patient presenting after a period of hypotension secondary to cardiac arrest, hemorrhage, sepsis, drug overdose, or surgery.

A careful search for exposure to nephrotoxins should include a detailed list of all current medications and any recent radiologic examinations (ie, exposure to radiologic contrast agents). Pigment-induced AKI should be suspected in patients with possible rhabdomyolysis (muscular pain, recent coma, seizure, intoxication, excessive exercise, limb ischemia) or hemolysis (recent blood transfusion). Allergic interstitial nephritis should be suspected with fevers, rash, arthralgias, and exposure to certain medications, including NSAIDs and antibiotics.

Postrenal failure

Postrenal failure usually occurs in older men with prostatic obstruction and symptoms of urgency, frequency, and hesitancy. Patients may present with asymptomatic, high-grade urinary obstruction because of the chronicity of their symptoms. A history of prior gynecologic surgery or abdominopelvic malignancy often can be helpful in providing clues to the level of obstruction.

Flank pain and hematuria should raise concern about renal calculi or papillary necrosis as the source of urinary obstruction. Use of acyclovir, methotrexate, triamterene, indinavir, or sulfonamides implies the possibility that crystals of these medications have caused tubular obstruction.

Obtaining a thorough physical examination is extremely important when collecting evidence about the etiology of AKI. Clues may be found in any of the following:

Cardiovascular system

Pulmonary system.

Skin examination may reveal the following:

• Livido reticularis, digital ischemia, butterfly rash, palpable purpura - Systemic vasculitis
• Maculopapular rash - Allergic interstitial nephritis
• Track marks (ie, intravenous drug abuse) - Endocarditis

Petechiae, purpura, ecchymosis, and livedo reticularis provide clues to inflammatory and vascular causes of AK. Infectious diseases, thrombotic thrombocytopenic purpura (TTP), disseminated intravascular coagulation (DIC), and embolic phenomena can produce typical cutaneous changes.

Eyes and ears

Eye examination may reveal the following:

• Keratitis, iritis, uveitis, dry conjunctivae - Autoimmune vasculitis
• Jaundice - Liver diseases
• Band keratopathy (ie, hypercalcemia) - Multiple myeloma
• Signs of diabetes mellitus
• Signs of hypertension
• Atheroemboli - Retinopathy

Evidence of uveitis may indicate interstitial nephritis and necrotizing vasculitis. Ocular palsy may indicate ethylene glycol poisoning or necrotizing vasculitis. Findings suggestive of severe hypertension, atheroembolic disease, and endocarditis may be observed on careful examination of the eyes.

Ear examination may reveal the following:

• Hearing loss - Alport disease, aminoglycoside toxicity, and platinum compound toxicity
• Mucosal or cartilaginous ulcerations - granulomatosis with polyangiitis (Wegener granulomatosis)

The most important part of the physical examination is the assessment of cardiovascular and volume status. The physical examination must include the following:

• Pulse rate and blood pressure measured in the supine and the standing position
• Close inspection of the jugulovenous pulse
• Careful examination of the heart and lungs, skin turgor, and mucous membranes
• Assessment for peripheral edema

Cardiovascular examination may reveal the following:

• Irregular rhythms (ie, atrial fibrillation) - Thromboemboli
• Murmurs - Endocarditis
• Pericardial friction rub - Uremic pericarditis
• Increased jugulovenous distention, rales, S 3 - Heart failure

In hospitalized patients, accurate daily records of fluid intake and urine output, as well as daily measurements of patient weight, are important. Hypovolemia leads to hypotension; however, hypotension may not necessarily indicate hypovolemia.

Severe heart failure may also cause hypotension. Although patients with heart failure may have low blood pressure, volume expansion is present and effective renal perfusion is poor, which can result in AKI.

Severe hypertension with kidney failure suggests one of the following disorders:

• Renovascular disease
• Glomerulonephritis
• Atheroembolic disease
• Subcapsular hematoma

Abdominal examination may reveal the following:

• Pulsatile mass or bruit - Atheroemboli
• Abdominal or costovertebral angle tenderness - Nephrolithiasis, papillary necrosis, renal artery thrombosis, renal vein thrombosis
• Pelvic, rectal masses; prostatic hypertrophy; distended bladder – Urinary obstruction
• Limb ischemia, edema - Rhabdomyolysis

Abdominal examination findings can be useful in helping to detect obstruction at the bladder outlet as the cause of renal failure; such obstruction may be due to cancer or to an enlarged prostate.

The presence of tense ascites can indicate elevated intra-abdominal pressure that can retard renal venous return and result in AKI. The presence of an epigastric bruit suggests renal vascular hypertension, which may predispose to AKI.

Pulmonary examination may reveal the following:

• Rales - Goodpasture syndrome, granulomatosis with polyangiitis (Wegener granulomatosis)
• Hemoptysis - Wegener granulomatosis

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Rim MY, Ro H, Kang WC, Kim AJ, Park H, Chang JH, et al. The effect of renin-angiotensin-aldosterone system blockade on contrast-induced acute kidney injury: a propensity-matched study. Am J Kidney Dis . 2012 Oct. 60 (4):576-82. [QxMD MEDLINE Link] .

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• Pigmented, muddy brown, granular casts are visible in the urine sediment of a patient with acute tubular necrosis (400x magnification).
• Photomicrograph of a kidney biopsy specimen shows renal medulla, which is composed mainly of renal tubules. Features suggesting acute tubular necrosis are the patchy or diffuse denudation of the renal tubular cells with loss of brush border (blue arrows); flattening of the renal tubular cells due to tubular dilation (orange arrows); intratubular cast formation (yellow arrows); and sloughing of cells, which is responsible for the formation of granular casts (red arrow). Finally, intratubular obstruction due to the denuded epithelium and cellular debris is evident (green arrow); note that the denuded tubular epithelial cells clump together because of rearrangement of intercellular adhesion molecules.
• Table 1. RIFLE Classification System for Acute Kidney Injury
• Table 2. Acute Kidney Injury Network Classification/Staging System for AKI 

Contributor Information and Disclosures

Biruh T Workeneh, MD, FASN Professor of Medicine, University of Texas MD Anderson Cancer Center Biruh T Workeneh, MD, FASN is a member of the following medical societies: American Society of Nephrology , National Kidney Foundation Disclosure: Nothing to disclose.

Omar Mamlouk, MBBS Instructor, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center Omar Mamlouk, MBBS is a member of the following medical societies: American Society of Nephrology , American Society of Onconephrology , National Kidney Foundation , Texas Medical Association Disclosure: Nothing to disclose.

Eleanor Lederer, MD, FASN Professor of Medicine, Chief, Nephrology Division, Director, Nephrology Training Program, Director, Metabolic Stone Clinic, Kidney Disease Program, University of Louisville School of Medicine; Consulting Staff, Louisville Veterans Affairs Hospital Eleanor Lederer, MD, FASN is a member of the following medical societies: American Association for the Advancement of Science , American Society for Bone and Mineral Research , American Society of Nephrology , American Society of Transplantation , International Society of Nephrology , Kentucky Medical Association , National Kidney Foundation Disclosure: Serve(d) as a director, officer, partner, employee, advisor, consultant or trustee for: American Society of Nephrology<br/>Received income in an amount equal to or greater than $250 from: Healthcare Quality Strategies, Inc.

Vecihi Batuman, MD, FASN Professor of Medicine, Section of Nephrology-Hypertension, Deming Department of Medicine, Tulane University School of Medicine Vecihi Batuman, MD, FASN is a member of the following medical societies: American College of Physicians , American Society of Hypertension , American Society of Nephrology , Southern Society for Clinical Investigation Disclosure: Nothing to disclose.

Mahendra Agraharkar, MD, MBBS, FACP, FASN Clinical Associate Professor of Medicine, Baylor College of Medicine; President and CEO, Space City Associates of Nephrology Mahendra Agraharkar, MD, MBBS, FACP, FASN is a member of the following medical societies: American College of Physicians , American Society of Nephrology , National Kidney Foundation Disclosure: Nothing to disclose.

Rajiv Gupta, MD Assistant Professor, Department of Medicine, Texas A&M University College of Medicine; Consulting Staff, Veterans Affairs Medical Center Rajiv Gupta, MD is a member of the following medical societies: Alpha Omega Alpha , American College of Cardiology , Society for Cardiovascular Angiography and Interventions Disclosure: Nothing to disclose.

Aruna Agraharkar, MD, FACP Consulting Staff, Department of Gerontology, Space Center Clinic

Aruna Agraharkar, MD, FACP is a member of the following medical societies: American Medical Assocation

Disclosure: Nothing to disclose.

Eleanor Lederer, MD Professor of Medicine, Chief, Nephrology Division, Director, Nephrology Training Program, Director, Metabolic Stone Clinic, Kidney Disease Program, University of Louisville School of Medicine; Consulting Staff, Louisville Veterans Affairs Hospital

Eleanor Lederer, MD is a member of the following medical societies: American Association for the Advancement of Science , American Federation for Medical Research , American Society for Biochemistry and Molecular Biology , American Society for Bone and Mineral Research , American Society of Nephrology , American Society of Transplantation , International Society of Nephrology , Kentucky Medical Association , National Kidney Foundation , and Phi Beta Kappa

Disclosure: Dept of Veterans Affairs Grant/research funds Research

Laura Lyngby Mulloy, DO, FACP Professor of Medicine, Chief, Section of Nephrology, Hypertension, and Transplantation Medicine, Glover/Mealing Eminent Scholar Chair in Immunology, Medical College of Georgia

Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference

Disclosure: Medscape Salary Employment

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Acute kidney injury (aki), table of contents, about acute kidney injury (aki), signs and symptoms, complications, preparing for your appointment.

Acute kidney injury (AKI) is a term used to describe when your kidneys are suddenly not able to filter waste products from the blood. This can happen within a few hours or a few days. For most people, AKI develops within 48 hours, but sometimes it can take as long as 7 days.

This replaces an older term “acute renal failure” (or ARF) which you may still see or hear occasionally.

Check out our online communities to connect, learn more and hear from others going through similar experiences.

The signs and symptoms of AKI can differ depending on many factors like the cause, severity, and your other health conditions. If symptoms do happen, they may include one or more of the following:

• Making less urine (pee) than usual or no urine
• Swelling in legs, ankles, and/or feet
• Fatigue or tiredness
• Shortness of breath (trouble breathing)
• Confusion or mood changes
• High blood pressure
• Decreased appetite (low desire to eat)
• Flank pain (pain on the side of your back - between your ribs and hips)
• Chest pain or pressure
• Seizures or coma (in severe cases)

In some cases, AKI causes no symptoms and is only found through other tests done by your healthcare professional.

AKI can have many different causes. Many people get AKI when a related disease or condition puts extra stress on your kidneys. Another common cause for AKI is when your body is reacting to an urgent or emergent health concern (such as heart surgery or COVID-19 infection). Lastly, AKI can be caused by medications or other substances that you may consume. Examples for each of these scenarios are provided below.

Usually, AKI happens because of a combination of factors. This is especially true for older adults who are at higher risk given their age.

Related disease or condition

• Autoimmune kidney disease, such as glomerulonephritis , lupus , or IgA nephropathy
• Cancer (especially bladder, cervical, ovarian, or prostate cancer)
• Chronic kidney disease
• Diabetes flare-up (also known as diabetes-related ketoacidosis or DKA)
• Heart disease (e.g. heart attack, heart failure, or other condition leading to decreased heart function)
• Kidney infection
• Kidney stones
• Liver disease or cirrhosis
• Multiple myeloma (a specific type of blood cancer)
• Vasculitis (long-term inflammation and scarring in your blood vessels)

Urgent or emergent health concerns

• Acute tubular necrosis (ATN), a situation causing very low blood flow to the kidneys
• Anaphylaxis (severe allergic reaction)
• Blood clot or cholesterol blocking a blood vessel in your kidney(s)
• Hypotension (very low blood pressure) or shock
• Hemorrhage (severe loss of blood)
• Major surgery
• Pregnancy complications
• Severe dehydration (not getting enough water or fluids for your body’s needs)
• Severe diarrhea and/or vomiting
• Severe skin burns

Medications and other substances

Items in this list may not cause AKI by themselves, but when combined with other factors from the other 2 categories above, your risk of AKI goes up significantly.

• Certain antibiotics, especially ones given for severe infections
• Certain blood pressure medicines, like ACE inhibitors/ARBs or diuretics (water pills)
• ibuprofen (Motrin, Advil)
• indomethacin (Indocin)
• naproxen (Aleve, Naprosyn)
• diclofenac tablets or capsules (Cataflam, Zipsor)
• celecoxib (Celebrex)
• meloxicam (Mobic)
• aspirin (only if more than 325 mg per day)
• Iodine-based contrast dye (used for CT scans and other forms of medical imaging)
• Recreational drugs, such as heroin or cocaine
• Some medicines used for cancer or HIV
• Toxic alcohols, such as methanol, ethylene glycol (antifreeze), or isopropyl/isopropanol (rubbing alcohol)

AKI can cause a build-up of waste products in your blood and make it hard to keep the right balance of fluid and minerals in your body. It can also cause permanent damage to your kidneys, leading to chronic kidney disease (CKD) . Without treatment, AKI can also affect other organs such as the brain, heart, and lungs. So, it is important to know what to watch for and how to lower your risk.

If your healthcare professional suspects AKI, they will perform an assessment to identify its potential cause (or causes). This may include performing a physical exam, reviewing your medical conditions and medication use history in the past week (including over-the-counter products and herbal supplements), asking about recent events and experiences (e.g. symptoms, water intake, recreational drug use, relevant travel), and ordering blood and/or urine tests.

Some of the most common tests used to check for AKI, include:

• Serum (blood) creatinine – a blood test used to check how well your kidneys are filtering this waste product from your blood
• Estimated glomerular filtration rate (eGFR) – this is calculated based on your serum (blood) creatinine level, age, and sex to estimate your kidney function
• Blood urea nitrogen (BUN) – similar to creatinine, this test can be used to measure another waste product in your blood to see how well your kidneys are filtering the blood
• Other blood tests , such as sodium, potassium, and bicarbonate (to see if anything is out of balance)
• Urine output – your healthcare professional may track how much urine (pee) you pass each day, especially if you are having AKI in the hospital
• Urine test (urinalysis) – a general urine test may be used to find more clues about the cause of AKI
• Imaging tests , like an ultrasound, may be helpful in some cases
• Kidney biopsy – in some less common situations, your healthcare professional may need to look at a tiny piece of your kidney under a microscope to get a better idea about the cause

Other tests may be ordered based on what your healthcare professional thinks might be causing your AKI.

Treatment for AKI depends on what caused it in the first place. This is why finding the cause is so important. Some most common approaches to treating AKI include:

• Stopping any medicines that may be causing or contributing to your AKI
• Giving you fluids (either by mouth or through your veins)
• Antibiotics (if AKI is caused by a bacterial infection)
• Placing a urine catheter (a thin tube used to drain your bladder, useful if AKI is caused by a blockage)
• In most cases, dialysis treatments are only temporary until the kidneys can recover.

Most people with AKI will need to spend some time in the hospital to be monitored while receiving treatment.

After having AKI, you have a higher risk for other health problems, such as chronic kidney disease (CKD), heart disease, or stroke). You are also at a higher risk of getting AKI again in the future. So, it is important to have regular follow-up visits with your healthcare professional and check your kidney health, starting with two simple tests (ideally within 3 months of finishing treatment for your AKI).

Questions to ask

• What are my biggest risk factors for AKI?
• What can I do to help lower my risk for AKI?
• Are there any medications I should avoid (either now or in the future) due to my kidneys?
• [If having potential symptoms of AKI] Should I go to the emergency room for my symptoms?
• Was the cause of my AKI preventable? If so, what can I do to prevent it from happening again?
• When should I follow up after my AKI treatment is done to check my kidney health?

This content is provided for informational use only and is not intended as medical advice or as a substitute for the medical advice of a healthcare professional.

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The protective mechanism of SIRT3 and potential therapy in acute kidney injury

Affiliations.

• 1 Department of Nephrology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
• 2 Department of Nephrology, 980th Hospital of PLA Joint Logistical Support Force (Bethune International Peace Hospital), Shijiazhuang, 050011, China.
• 3 Department of Postgraduate Student, Xi'an Medical University, Xi'an, 710021, China.
• 4 Department of Geriatric, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
• PMID: 37354530
• DOI: 10.1093/qjmed/hcad152

Acute kidney injury (AKI) is a complex clinical syndrome with a poor short-term prognosis, which increases the risk of the development of chronic kidney diseases and end-stage kidney disease. However, the underlying mechanism of AKI remains to be fully elucidated, and effective prevention and therapeutic strategies are still lacking. Given the enormous energy requirements for filtration and absorption, the kidneys are rich in mitochondria, which are unsurprisingly involved in the onset or progression of AKI. Accumulating evidence has recently documented that Sirtuin 3 (SIRT3), one of the most prominent deacetylases highly expressed in the mitochondria, exerts a protective effect on AKI. SIRT3 protects against AKI by regulating energy metabolism, inhibiting oxidative stress, suppressing inflammation, ameliorating apoptosis, inhibiting early-stage fibrosis and maintaining mitochondrial homeostasis. Besides, a number of SIRT3 activators have exhibited renoprotective properties both in animal models and in vitro experiments, but have not yet been applied to clinical practice, indicating a promising therapeutic approach. In this review, we unravel and summarize the recent advances in SIRT3 research and the potential therapy of SIRT3 activators in AKI.

© The Author(s) 2023. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For permissions, please email: [email protected].

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• Published: 19 June 2024

The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study

• Yipeng Fang   ORCID: orcid.org/0000-0001-6051-5274 1 , 2 , 3 ,
• Yuan Zhang 3 &
• Xin Zhang   ORCID: orcid.org/0000-0001-5113-1420 1 , 2 , 3  

BMC Nephrology volume  25 , Article number:  201 ( 2024 ) Cite this article

304 Accesses

Metrics details

There is no evidence to determine the association between the lactate dehydrogenase to albumin ratio (LAR) and the development of sepsis-associated acute kidney injury (SAKI). We aimed to investigate the predictive impact of LAR for SAKI in patients with sepsis.

A total of 4,087 patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC IV) database were included. Logistic regression analysis was used to identify the association between LAR and the risk of developing SAKI, and the relationship was visualized using restricted cubic spline (RCS). The clinical predictive value of LAR was evaluated by ROC curve analysis. Subgroup analysis was used to search for interactive factors.

The LAR level was markedly increased in the SAKI group ( p  < 0.001). There was a positive linear association between LAR and the risk of developing SAKI (p for nonlinearity = 0.867). Logistic regression analysis showed an independent predictive value of LAR for developing SAKI. The LAR had moderate clinical value, with an AUC of 0.644. Chronic kidney disease (CKD) was identified as an independent interactive factor. The predictive value of LAR for the development of SAKI disappeared in those with a history of CKD but remained in those without CKD.

Conclusions

Elevated LAR 12 h before and after the diagnosis of sepsis is an independent risk factor for the development of SAKI in patients with sepsis. Chronic comorbidities, especially the history of CKD, should be taken into account when using LAR to predict the development of AKI in patients with sepsis.

Peer Review reports

Sepsis, defined by the Sepsis 3.0 definition as organ dysfunction caused by an imbalanced host response to infection, is common in intensive care units (ICUs) [ 1 ]. Acute kidney injury (AKI) is one of the most common complications of sepsis, and its prevalence increases progressively with the aggravation of sepsis [ 2 ]. However, epidemiological studies investigating the prevalence of sepsis-associated AKI (SAKI) are still limited. The incidence of SAKI is approximately 10 million (1.4 per 1000 population) per year [ 3 ]. Due to the low detection rate of SAKI, the actual percentage in real life would be even higher [ 3 ]. The high mortality rate of SAKI is also a major public health concern. Compared to patients with AKI induced by other causes, patients with SAKI had a higher risk of in-hospital mortality and longer hospital stays [ 4 ]. Although SAKI has received much attention and remarkable progress has been made in SAKI treatment, the mortality of SAKI remains unacceptably high [ 5 ]. As early reversal of SAKI is associated with decreased morality [ 6 ], early identification of sepsis patients at high risk of SAKI is crucial.

Lactic dehydrogenase (LDH) is one of the key enzymes involved in glycolysis and is widely distributed in various tissues and organs throughout the human body [ 7 ]. LDH acts as a catalyst for the conversion of pyruvate to lactic acid. Under hypoxic conditions, activation of LDH catalyzes the conversion of pyruvate to lactate during glycolysis [ 8 ]. When cell damage occurs, LDH could be released into the bloodstream from LDH-containing cells, leading to an increase in serum LDH levels. It has been shown to be an independent risk factor for poor outcome in sepsis [ 9 ], acute pancreatitis [ 10 ], acute kidney disease [ 11 ] and tumors [ 12 ]. However, evidence regarding the predictive value of LDH for AKI is still limited. Two studies found that elevated LDH was an independent risk factor for AKI after cardiac surgery [ 13 , 14 ]. According to the study by Amitai I et al., LDH > 380 U/L and albumin < 3.6 gr/dLwere significantly associated with the development of high-dose methotrexate-induced AKI [ 15 ]. However, the predictive role of LDH in the development of SAKI remains unclear.

Serum albumin is a commonly used laboratory parameter for assessing patients’ nutritional status and renal injury, especially in chronic disease [ 16 , 17 ]. Podocyte injury can disrupt the integrity of the glomerular filtration barrier, leading to proteinuria and hypoproteinemia [ 18 ]. Previous evidence suggests that decreased serum albumin is associated with higher mortality in sepsis and AKI cohorts [ 19 , 20 ]. In addition, serum albumin can serve as a predictor of AKI [ 21 ]. Several combined indicators with albumin showed strong predictive and prognostic value for AKI, such as the fibrinogen to albumin ratio [ 22 ], uric acid to albumin ratio [ 23 ] and lactate to albumin ratio [ 24 ].

Overall, serum LDH and albumin have shown potential as biomarkers for the diagnosis and prognosis of AKI. A recent study has reported that the combination of LDH and albumin showed a better prognostic value in patients with AKI than the use of either parameter alone [ 25 ]. However, the predictive value of LDH combined with albumin for SAKI has not been investigated. In the present study, we aimed to investigat the relationship between the lactate dehydrogenase to albumin ratio (LAR) and the development of SAKI, as well as the predictive value of LAR for SAKI.

Methods and materials

Study design.

This is a descriptive, retrospective, single-center study using hospital information from the Medical Information Mart for Intensive Care IV (MIMIC-IV database, Vision 2.1). The MIMIC-IV database contains information on approximately 180,000 patients, including 50,934 with ICU admission records, between 2008 and 2019 at the Beth Israel Deaconess Medical Center in Boston, Massachusetts, USA. It is a public database developed by the MIT Lab for Computational Physiology. Author FYP (certification number 43,025,968) was responsible for the initial data extraction using PgAdmin4 and PostgreSQL (version 9.6) software. Present manuscript was reported in accordance with the STROBE guidelines [ 26 ].

Adult patients with sepsis during their ICU stay were initially screened according to the Sepsis 3.0 criteria. The following patients were excluded from the initial cohort: (1) patients with recurring hospital admissions (only the first ICU admission record was included); (2) patients with the development of AKI before sepsis diagnosis; (3) patients who died within 48 h of ICU admission or had a length of ICU stay less than 48 h; and (4) patients with missing LDH or albumin results 12 h before or after sepsis diagnosis.

The present study included demographic data, comorbidities, vital signs, laboratory parameters, disease severity scores and microbiological culture results. Demographics included age, sex, ethnicity and body weight. Comorbidities included hypertension, coronary heart disease, congestive heart failure, diabetes mellitus, chronic lung disease, liver disease, chronic kidney disease (CKD) and malignant cancer. Vital signs, including heart rate, respiratory rate, mean arterial pressure (MAP), temperature and oxygen saturation (SpO 2 ), were measured at the time of sepsis diagnosis. The initial values of laboratory parameters obtained after sepsis diagnosis were used in the final analysis, including serum white blood cell (WBC) count, hemoglobin, platelets, creatinine (SCr), blood urea nitrogen (BUN), sodium, potassium, chloride and lactate levels. The initial Simplified Acute Physiology Score II (SAPS II) and Glasgow Coma Scale (GCS) at the time of ICU admission were used, while the initial value of the Sequential Organ Failure Assessment (SOFA) score at the time of sepsis diagnosis was used. Since LDH is strongly associated with lactate formation and liver dysfunction, the level of lactic acid and liver injury-related markers at the time of sepsis diagnosis, including bilirubin, alanine transaminase (ALT) and aspartate transaminase (AST), were also included in the final analysis.

Exposure and clinical outcomes

The exposure was the value of LAR (IU/g). Only the results of LDH (IU/L) and albumin (g/L) obtained 12 h before or after the diagnosis of sepsis were retained. If multiple values were available, the mean value was used to calculate the LAR value (IU/g). Patients were divided into four equal subgroups according to their LAR values: Q1, LAR ≤ 6.5 IU/g; Q2, 6.5 IU/g < LAR ≤ 9.3 IU/g; Q3, 9.3 IU/g < LAR ≤ 15.2 IU/g; and Q4, LAR ≥ 15.2 IU/g.

The development of AKI after sepsis was the primary outcome. AKI was diagnosed and stratified only on the basis of the change in plasma creatinine according to the KIDGO guidelines as reported in previous studies [ 27 , 28 ]. SAKI was defined as the presence of AKI within the first 48 h after sepsis diagnosis. The secondary outcomes included RRT after sepsis diagnosis, the use of vasoactive drugs within 48 h of sepsis diagnosis, mortality indicators and LOS indicators.

Data cleaning

Scatter plots were drawn to check for outliers. Outliers were handled as missing values. As the percentage of missing values was less than 10%, median/mean imputation was used for most variables. Missing lactic acid values, constituting 13% of the data, were imputed using a regression method based on the specified regression equation. Indicators with missing data exceeding 15% were omitted from the analysis. Details concerning the missing values are provided in Table S1 .

Statistical analysis

Normally distributed variables were shown as the mean ± standard deviation (SD), and nonnormal variables were shown as the median and interquartile range (IQR). Categorical variables were presented as numbers and percentages. For pairwise comparisons of continuous variables, Student’s t test (for normally distributed values) and the Mann–Whitney U test (for nonnormally distributed values) were performed. For multiple comparisons of continuous variables, one-way ANOVA (for normally distributed values) and the Kruskal‒Wallis H tests (for nonnormally distributed values) were used. For categorical variables, the chi-square test was used. Univariate and multivariate logistic regression models were developed to investigate the predictive value of the LAR value for SAKI development. We evaluated multicollinearity among candidate variables using variance inflation factors (VIF), considering a VIF greater than 10 as indicative of significant collinearity [ 29 ]. To address significant multicollinearity, variables with a VIF exceeding 10 were converted into categorical variables based on their median or mean values. The VIF details for all variables are presented in Table S2 . The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were examined to determine the clinical predictive value of LAR for SAKI development. Restricted cubic spline (RCS) was performed to determine the linear and nonlinear relationship between the LAR value and the risk of developing SAKI. Subgroup analysis was performed to verify the robustness of the initial results and to find potential interactive factors. We performed all statistical analyses using Stata (version 15.1) and R software (version 4.1.3). A two-sided p value < 0.05 was considered statistically significant.

Population and baseline information

In the MIMIC-IV database (Vision 2.1), there were 22,396 adult patients meeting the Sepsis-3.0 criterion during their ICU stay. A total of 4,087 patients were included in our final analysis. The flow chart of population screening is shown in Fig.  1 . The incidence of SAKI was 26.25% (1,073/4,087). As shown in Table  1 , there was no significant difference in age between the SAKI and non-SAKI subgroups ( p  = 0.455). Patients with SAKI were more likely to be men but less likely to be Caucasians. Body weight was higher in the SAKI subgroup. Patients with SAKI had a higher proportion of comorbid coronary heart disease, congestive heart failure, diabetes mellitus, liver disease and CKD but a lower proportion of comorbid hypertension. Patients in the SAKI subgroup had higher values for heart rate, respiratory rate, SOFA score, SAPS II score, WBC and potassium but lower values for MAP, temperature, GCS score, platelets, sodium and chloride. Patients in SAKI subgroup also had higher values for lactic acid, bilirubin, ALT and AST than those in non-SAKI subgroup (all p  < 0.001). They were also more likely to have a positive culture and using vasopressor during their ICU stay. Levels of LDH (348 (235, 618) vs. 265 (199, 392)) and LAR (12.5 (7.7, 22.4) vs. 8.6 (6.2, 13.5)) were higher in the SAKI subgroup, whereas albumin (30.0 (25.0, 34.0) vs. 31.0 (27.0, 36.0)) was decreased in the SAKI subgroup (all p  < 0.05).

Flow chart. Flow chart of patient selection

Linear relationship between log 2 (LAR) value and SAKI development

Figure  2 shows the relationship between the log 2 (LAR) value and SAKI development in patients with sepsis in the ICU using the RCS technique. A positive linear relationship was detected (p for nonlinearity = 0.867), with the reference point log 2 (LAR) = 3.22 (LAR = 9.32). An LAR value higher than 9.32 IU/g was considered a risk factor for the development of SAKI (OR > 1). Therefore, an LAR of 9.32 IU/g was used as the cutoff point to generate the high-LAR and low-LAR subgroups for the subgroup analysis.

Restricted cubic spline. There was a positive linear relationship between log 2 (LAR) and the risk of developing SAKI in patients with sepsis

LAR categories and clinical outcomes

Patients were further divided into four categories according to the IQR of the LAR value (Q1 –Q4 categories). The crude outcomes of those four subgroups are shown in Table  2 . The incidence rate of SAKI increased with increasing LAR, with the incidence rate increasing stepwise from Q1 (15.82%) to Q4 (41.35%, p  < 0.001). In SAKI patients, the incidence rate of stage 2 and 3 SAKI also increased stepwise from Q1 (24.22%) to Q4 (50.12%, p  < 0.001). In the SAKI subgroups, more RRT was performed in the Q4 category (LAR > 15.2 IU/g), but no difference was observed from Q1 to Q4. No significant difference was found in the time interval from sepsis to developing SAKI and from SAKI to using RRT among Q1 –Q4 categories ( p  = 0.854 and 0.242). Increasing trends were also observed for vasopressor use, 28-day mortality, 90-day mortality, hospital mortality, ICU mortality, hospital-LOS and ICU-LOS (all p  < 0.001). Patients in the Q4 category had the highest 28-day mortality rate (33.33%), followed by Q3 (22.24%), Q2 (15.18%) and Q1 (8.64%).

Logistic regression models were performed to further determine the crude and adjusted effects of LAR on the development of SAKI. Table  3 shows that in one original model and three adjusted models, each IU/g increase in LAR was significantly associated with a 1–2% increase in the risk of SAKI development (OR: 1.001–1.002, p  < 0.001). The risk of SAKI increased stepwise from Q2 (OR 1.53, 95% CI 1.22–1.91, p  < 0.001) to Q4 (OR 3.75, 95% CI 3.04–4.63, p  < 0.001) in the unadjusted model, using the Q1 category as a reference. After adjustment for potential confounders, a similar trend was observed, but the Q2 and Q3 categories lost statistical significance in Model 3 ( p  = 0.259 and 0.152). Elevated LAR was also considered an independent risk factor for RRT in patients with SAKI (all OR > 1, p  < 0.001). When LAR was divided into four categories, only extremely high LAR, the Q4 category (LAR > 15.2 IU/g), was identified as an independent risk factor for RRT, taking the Q1 category (LAR ≤ 6.5 IU/g) as a reference. This significant effect was lost after adjusting potential confounders in Model 3 ( p  = 0.065). In addition, elevated LAR was identified as an independent risk factor for 28-day and in-hospital mortality in all models (all OR > 1, p  < 0.01). The risk of mortality tended to increase steadily with increasing LAR level from Q2 (OR 1.42, 95% CI 1.05–1.90, p  = 0.021 for 28-day mortality; OR 0.157, 95% CI 1.05–2.29, p  = 0.017 for in-hospital mortality) to Q4 (OR 3.32, 95% CI 2.49–4.42, p  < 0.001 for 28-day mortality; OR 3.88, 95% CI 2.73–5.52, p  < 0.001 for in-hospital mortality) in model 3, with the Q1 category (LAR ≤ 6.5 IU/g) as a reference.

Clinical predictive values

The clinical value of LAR in predicting SAKI was determined by ROC curve analysis. As shown in Fig.  3 , LAR showed a moderate predictive ability for the development of SAKI (AUC 0.644, 95% CI 0.624–0.664). LAR had a significantly better predictive ability than LDH alone (AUC 0.633, 95% CI 0.614–0.653, p  = 0.012). Albumin alone had the worst predictive ability (AUC 0.561, 95% CI 0.541–0.581).

ROC curve. LAR (blue line) had a better predictive value for SAKI in patients with sepsis than LDH alone (purple line) and serum albumin alone (red line)

Subgroup analysis and post hoc analysis

The relationship between the LAR value and SAKI development was still robust in different statuses (shown in Fig.  4 ). Four interactive factors were found, including sex, CKD, chronic pulmonary disease and diabetes ( p for interaction < 0.05). It should be noted that the LAR value and SAKI showed a negative relationship in patients with a history of CKD, but no statistical significance was reached (OR 0.75, 95% CI 0.53–1.01, p  = 0.064).

Subgroup analysis. The association between LAR and the risk of SAKI development was detected in the crude model ( a ) and adjusted model ( b ). Subgroup analysis indicated that there were significant ‘LAR×sex’, ‘LAR×CKD’, ‘LAR×pulmonary disease’ and ‘LAR×diabetes’ interactions

In the post hoc analysis, the relationship and predictive value between LAR and SAKI development in patients with or without a history of CKD were further determined. Figure  5 a shows that a significant positive linear relationship between the LAR and SAKI development still existed in patients without CKD ( p for nonlinear = 0.057). LAR showed moderate predictive value for SAKI (AUC 0.694), which was better than LDH alone (AUC 0.673) and albumin alone (AUC 0.597) (Fig.  5 b). A similar trend was observed in logistic regression analysis in patients without a history of CKD compared with the overall cohort (Fig.  5 c).

Post hoc analysis. The association between the LAR and the risk of SAKI development was further investigated in the non-CKD ( a - c ) and CKD cohorts ( d - f ) of patients with sepsis. ( d ) Restricted cubic spline showed that the positive linear relationship disappeared in sepsis patients with a history of CKD. ( e ) LAR had poor predictive value for SAKI development in sepsis patients with a history of CKD. ( f ) LAR was not associated with the risk of SAKI development in the adjusted logistic regression model

The above findings did not hold true for sepsis patients with a history of CKD. As shown in Fig.  5 d, there was no significant trend between LAR and the development of SAKI in patients with a history of CKD (95% CI included 1). Although an extremely high LAR was associated with a higher risk of SAKI development, this was only confirmed by the very small sample. A poor clinical predictive value of LAR was detected in the ROC curve (AUC 0.545, Fig.  5 e). In the adjusted logistic regression model, a high LAR showed no association with the development of SAKI and RRT, but the elevated LAR was independent risk factors for 28-day and in-hospital mortality (Fig.  5 f).

Discussions

In the present study, we found a positive linear correlation between LAR and the development of SAKI. Increased LAR was significantly associated with the risk of developing SAKI in patients with sepsis. LAR showed a moderate predictive value for the development of SAKI, which was superior to LDH or albumin alone. The LAR was also of significant value in identifying mortality. To interpret the value of LAR accurately, the history of CKD of the patients should not be ignored. The predictive values of LAR on predicting SAKI development did not exist in sepsis patients with a history of CKD but still existed in those without CKD. To the best of our knowledge, our study is the first to investigate the predictive value of LAR for the development of SAKI.

Serum albumin is a commonly used clinical indicator that reflects the nutritional status of patients and is involved in acute inflammatory responses [ 30 ]. Decreased serum albumin reflects poor nutrition and a potential systemic inflammatory reaction. Serum albumin plays several important roles in the development of AKI. First, albumin has been shown to have potent antioxidative stress and anti-inflammatory properties [ 30 , 31 ]. Physiological level of albumin would help to alleviate renal tissue injury by downregulating oxidative stress and inhibiting proinflammatory reactions [ 32 ]. Second, as an important component of plasma colloid osmotic pressure, maintaining serum albumin in the physiological range would contribute to the regulation of fluid balance, intravascular volume and tissue perfusion [ 33 ], which may halt the process of AKI and loss of renal function. The product of albumin binding to platelet-activating factor and nitrogen oxide, named S-nitroso-albumin, helps maintain renal perfusion by dilating the local vascular network of the kidney [ 34 ]. Third, albumin may inhibit tissue damage by regulating several classical signaling pathways, like PI3K/AKT, NF-κB, MAPK and GSK-3β [ 35 , 36 , 37 , 38 ]. In renal proximal tubular cells (PTECs), activation of the PI3K/AKT pathway affects the level of albumin uptake by regulating PTEC protein reabsorption [ 35 ]. In the T2DM mouse model, recombinant albumin can effectively relieve endoplasmic reticulum stress and apoptosis by regulating the activation of the PI3K-AKT signaling pathway and alleviate T2DM by promoting glucose homeostasis and protecting islet β cells [ 36 ]. Pea albumin can inhibit DSS-induced colitis via inhibition of inflammation, regulation of NF-κB signaling and modulation of gut microbiota [ 37 ]. In addition, albumin inhibited serum starvation-induced mitochondrial damage, autophagy and apoptosis by regulating p38 MAPK and Akt/GSK-3β signaling [ 38 ]. Although there is no direct evidence to verify the potential signaling pathways involved in the effect of albumin on the development of AKI, the above classical signaling pathways have been widely demonstrated to be involved in the occurrence and development of AKI. In particular, albumin overload also leads to tissue injury [ 39 ]. Fourth, a normal serum albumin level is associated with a good physiological status of the body, reflecting the ability of humans to resist disease. Decreased serum albumin has been identified to be associated with several kinds of disease [ 39 ].

Many composite indicators using serum albumin are widely used in patients with sepsis and show higher predictive power than using parameters alone. The lactate-to-albumin ratio has a moderate predictive value for mortality in patients with sepsis or septic shock (AUC 0.74), with pooled sensitivity, specificity, and diagnostic odds ratios of 0.71, 0.68 and 5.23, respectively [ 40 ]. The blood urea nitrogen to albumin ratio (BAR) was found to be an independent risk factor for mortality in patients with sepsis (AUR 0.661) [ 41 ]. The red blood cell distribution width-to-albumin ratio (RAR) was reported as an independent risk indicator for 90-day mortality in elderly patients with AKI (AUC 0.656) [ 42 ]. Elevated RAR was independently associated with an increased risk of SAKI (RR 1.09) [ 43 ]. Combination with serum albumin is a commonly used method to improve the clinical value of indicators.

LDH is widely distributed enzyme across various cells and tissues. Elevated LDH levels indicate damage to the cell membrane and cell death, making it a common marker for predicting acute heart and liver injury in clinical settings [ 44 , 45 ]. LDH is one of the key enzymes in glycolysis and is involved in lactate production. However, the diagnostic and prognostic value of LDH in patients with sepsis and SAKI has received much less attention. Its potential value as a predictive biomarker for nonsepsis-induced AKI has been demonstrated previously [ 13 , 14 , 15 ]. Elevated LDH was associated with multiple factors in the setting of AKI, as follows. First, as an important factor in the development of AKI, the activation of hypoxia-inducible factor (HIF) induced by hypoxia upregulates the transcription of LDH to promote glycolysis [ 46 ]. Second, LDH has been shown to be widely distributed in various tissues, including the kidney [ 13 ]. Renal tissue damage caused by inflammation, oxidative stress and ischemic/hypoxic events during AKI may lead to the release of intracellular LDH into the serum [ 47 ]. The above pathophysiological mechanisms are also relevant to the development of sepsis. In our present study, we found that patients with SAKI had higher LDH levels than those without SAKI. LDH alone was only moderately predictive of SAKI. As LDH is widely distributed and commonly elevated in many diseases, especially in acute myocardial injury, the value of using LDH alone to predict SAKI may be limited. Undeniably, the predictive value of LDH alone in AKI has been widely demonstrated in several AKI cohorts [ 13 , 14 , 15 ].

Recent studies have investigated the clinical value of LDH in combination with albumin. Lee BK et al. reported that an increased LAR was independently positively associated with hospital mortality in patients with lower respiratory tract infection, with good prognostic value (AUC = 0.808) [ 48 ]. In a nasopharyngeal carcinoma cohort, an LAR greater than 4.04 was associated with a 1.71-fold increased risk of death compared to those with a lower LAR [ 49 ]. Two recent studies have investigated the potential association between LAR and mortality in patients with sepsis. Deng YH et al. demonstrated a positive nonlinear relationship between LAR and mortality in critically ill patients with sepsis [ 25 ]. A similar trend of LAR on mortality was demonstrated in the AKI subgroup in patients with sepsis [ 50 ]. To date, the predictive value of LAR for SAKI remains unclear. Our results suggested a clear positive linear correlation between LAR and the risk of developing SAKI. LAR had a higher clinical prognostic value for SAKI than LDH alone and albumin alone in both crude and adjusted models.

To mitigate the effects of heart and liver tissue injuries on the predictive accuracy of LAR, we controlled for several variables including coronary heart disease, heart failure, liver disease, as well as levels of lactate, transaminase, and bilirubin in our multi-factor logistic regression analysis. Despite controlling for these potential confounders, LAR’s predictive significance for the development of SAKI remained substantial. However, caution is still warranted as our subgroup analysis revealed that an elevated LAR does not independently predict SAKI in patients suffering from liver disease or heart failure. This might be attributed to LDH being a non-specific indicator of tissue and cellular damage. Consequently, the diagnostic utility of LAR for SAKI could be compromised by increased LDH levels originating from cardiac and liver injuries. This highlights the necessity of considering the impact of these conditions when utilizing LAR as a predictor for SAKI.

Interestingly, a significant LAR-CKD interaction effect was observed. The prognostic value of LDH on SAKI was still robust in the non-CKD subgroup but disappeared in the CKD subgroup. We speculated that the possible mechanism might be due to the following aspects. Above all, chronic kidney injury may cause slow but constant damage to the cell and reduce the physiological reserve of LDH in the cell. We found that patients with CKD had lower levels of LDH (273 (208,410) vs. 284 (205,447), p  = 0.064) and LAR (8.8 (6.5, 14.1) vs. 9.5 (6.5, 15.5), p  = 0.024) than those without a history of CKD in the present cohort. In addition, proteinuria caused by podocyte injury significantly influences serum albumin levels and may also decrease the predictive value of LAR. More evidence is needed to support our speculation. Our findings also serve as a reminder that CKD history should not be ignored when using LAR to predict the development of AKI.

Our study possesses multiple strengths. Primarily, it utilizes data from a high-quality intensive care database with a substantial sample size, enhancing the accuracy and reliability of our findings. Additionally, the use of publicly accessible data mining codes from the MIMIC IV database ( https://github.com/MIT-LCP/mimic-code ) supports the precision and reproducibility of our results [ 51 ]. Our research rigorously evaluates the predictive capability of the leukocyte-to-albumin ratio (LAR) for acute kidney injury (AKI) in patients with sepsis. We carefully excluded patients who developed AKI prior to the diagnosis of sepsis to reduce potential confounding effects on the serum levels of LDH and albumin. We also considered several confounders, including acute cardiac injury, acute liver dysfunction, and chronic kidney disease (CKD). Notably, our post-hoc analysis revealed the influence of CKD on the clinical utility of LAR in forecasting sepsis-associated AKI (SAKI), which is critical for the effective application of LAR as a prognostic marker.

Admittedly, despite above benefits, some limitations do exist in present study, and the results should be interpreted with caution. First, this was a retrospective study using data from a single center, which may be subject to inherent bias. Second, selection bias seems inevitable because only patients with laboratory results of LDH and albumin were included in the final analysis. We think that patients with LDH and albumin results may be a different population from those without. Third, as dynamic change indicators, their values at a single point in time may not accurately reflect the true situation of patients. Trajectory analysis to identify the different trajectory groups of LAR would be an optional method to solve this problem. Fourth, information on the mechanism and pathogenesis, especially of LDH, is still limited. Firstly, the diagnostic criteria for sepsis and SAKI used in our study do not fully align with those commonly applied in clinical settings, which might limit the practical applicability of our results in a clinical context. Therefore, more well-designed clinical studies, trajectory analysis and basic research are necessary in the future.

There is a positive linear correlation between the LAR and the risk of developing SAKI in sepsis patients without a history of CKD. Increased LAR was an independent risk factor and had moderate predictive value for SAKI development in the non-CKD sepsis cohort.

Data availability

ALL data were obtained from the public database MIMIC IV (version 2.1, https://doi.org/10.13026/rrgf-xw32 ). Structured data for final analysis in the present study are uploaded in supplemental files. More details can be obtained from the corresponding author upon reasonable request.

Abbreviations

Area under the curve

Blood urea nitrogen to albumin ratio

Blood urea nitrogen

Chronic kidney disease

Intensive care units

Glasgow Coma Scale

Interquartile range

Lactate dehydrogenase to albumin ratio

Lactic dehydrogenase

Mean arterial pressure

The Medical Information Mart for Intensive Care IV

Red blood cell distribution width-to-albumin ratio

Restricted cubic spline

Receiver operating characteristic

Sepsis-induced acute kidney injury

Simplified Acute Physiology Score II

Serum creatinine

Standard deviation

Sequential Organ Failure Assessment

Oxygen saturation

Serum white blood cell

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Acknowledgements

We thank all participants for their support and cooperation.

This work was supported by the National Nature Science Foundation of China, Grant/Award Number: 31371509; the 2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant, Grant/Award Number: 2020LKSFG20B; the 2021 Science and Technology Special Fund of Guangdong Province, Grant/Award Number: 210713156872672; and the 2022 Characteristics and Innovation Grant for College of Guangdong Province, Grant/Award Number: 2022KTSCX040.

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Yipeng Fang: Writing – original draft, Conceptualization, Data curation, Formal Analysis, Methodology, Project administration, Software, Validation, Visualization. Xin Zhang: Writing – review & editing, Conceptualization, Funding acquisition, Project administration, Supervision. All of the authors gave final approval of the version to be published and agreed to be accountable for all aspects of the work.

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Fang, Y., Zhang, Y. & Zhang, X. The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study. BMC Nephrol 25 , 201 (2024). https://doi.org/10.1186/s12882-024-03636-5

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Dehydration during hot weather can lead to acute kidney injury

by Liz Bonis & Megan Burgasser, WKRC

CINCINNATI (WKRC) - Amid summer heat, health providers have issued a warning about staying hydrated. Dehydration is bringing people with kidney problems into the doctor’s office.

It’s not the usual hot weather complication people hear about, but it’s a dangerous one.

Dr. Scott Woods said he’s seen acute kidney injury, likely from dehydration. Here’s what that means:

“We had several people who ran into trouble with their fluid balance. Some of which had to be hospitalized, many of which had to go to the emergency room,” said Dr. Woods, program director of Bethesda Family Medicine.

It’s a reminder to everyone that if people wait until they are thirsty to hydrate – they’ve likely waited too long.

Here are some of the early warning signs that people could be putting their kidneys at risk:

“Lightheaded, sweating very hard when you are trying to cool off, possibly even passing out,” Dr. Woods said. “One caveat is even though your kidney labs go back to normal when your fluids have been replenished, that acute kidney injury actually permanently changes the functioning of the kidney. It decreases kidney function, so multiple events like this actually causes quite a bit of kidney destruction.”

For those taking certain diabetes or high blood pressure medications – they can also raise the risk of dehydration and sun sensitivity or sunburn, which could add to kidney complications.

“Some of these would be antibiotics as a big one, and this is true. There are some antibiotics that can make sunburn worse, so it’s really important that it’s completed, or even a few days after it’s completed, so it doesn't cause as severe sunburn,” said Dr. Andrew Straw, associate professor of pharmacy practice at Cedarville University.

Another note: Dehydration can also raise the risk in some people of other serious health concerns, including urinary tract infections and kidney stones, particularly for those who’ve had them before. Early warning signs include changes in urine output or color and unusual pain. People who notice those symptoms should call a doctor.

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Fixed-Ratio Insulin Combinations May Reduce Nausea, Other Side Effects

Kerry Dooley Young

June 23, 2024

ORLANDO, Fla. — Using fixed-ratio insulin combinations (FRC) can reduce side effects such as nausea in treating diabetes, an advantage that should persuade clinicians to consider these drugs more often, according to a presentation at the American Diabetes Association (ADA) 84th Scientific Sessions.

"People treating diabetes tend to kind of grimace at fixed ratio combinations," Liana K. Billings, MD, MMSc, of NorthShore University Health System, Skokie, Illinois, during the presentation. "They tend to shy away. They want to be tinkering and micromanaging, up and down, here and there. And maybe it's improving outcomes, but maybe it's not." 

The ADA session on "off-target" effects of diabetes medications featured Billings' arguments, based on previously published data, about the potential advantages for patients from fixed-ratio insulin combinations such as insulin degludec / liraglutide (IDegLira). In her presentation, Billings emphasized both reduced side effects and increased convenience for patients with FRC. 

A 2016 paper in the journal Diabetes Care reported there were lower rates of nausea (9.6%) and vomiting (3.2%) events for patients on iGlarLixi, a fixed-ratio combination of insulin glargine (iGlar) and lixisenatide than for lixisenatide alone (24% and 6.4%, respectively) in a study.

Physicians need to keep in mind how patients react to nausea and vomiting, as these can lead people to abandon therapies. It's essential to build trust with patients in new therapies, especially in the first 12 weeks of use, she said.

"If you give them a therapy and they feel really sick on it, they may not continue it," she said. 

Other research indicates FRCs lower hypoglycemia risk compared to basal bolus or basal insulin alone, while also minimizing other side effects such as weight gain, Billings said. In addition, the FRCs are more convenient for patients and their clinicians, with a potential to get the same kind of A1c control with 365 injections a year as opposed to about 1460, she said.

"You can kill two birds with one stone, or whatever idiom you want to use, with fixed-ratio combinations," Billings said. "They're simple. They relieve treatment burden by reducing fingersticks and injections. They allow for safe patient managed titration. They reduce burden on diabetes clinicians."

"I challenge you to change your paradigm and don't shy away from fixed-ratio combinations," she concluded. "Use it as a key piece in your toolbox in treating type 2 diabetes ."

In her presentation, Billings also emphasized that the FRC approach may be a cost-effective option. According to Billings, for every $1 spent on insulin degludec/liraglutide (IDegLira) to achieve an A1c target of less than 7.5% without hypoglycemia or weight gain, it costs:

• $2.43 for IGlar up-titration
• $6.33 for basal bolus therapy

Examining SGLT2 Inhibitors Side Effects

At the session, Ronald M. Goldenberg, MD, of Toronto-based LMC Diabetes and Endocrinology addressed concerns about sodium-glucose cotransporter-2 (SGLT2) inhibitors, including ones raised in recent years in safety warnings issued by the US Food and Drug Administration (FDA).

In general, the benefits of SGLT2 inhibition, when indicated, outweigh the low risk of off-target adverse effects, he said. And risk mitigation strategies can help in managing these effects. Accepted as rare potential side effects are diabetic ketoacidosis and lower limb amputation. 

Among his key conclusions were:

Acute kidney injury.  In 2016, the FDA strengthened its warning s about the risk for acute kidney injury for canagliflozin (Invokana, Invokamet) and dapagliflozin (Farxiga, Xigduo XR). 

But the view on this risk appears to be changing, with some research suggesting this class of drugs may actually offer protection against acute kidney injury, Goldenberg said. He added that there ongoing studies looking at prescribing an SGLT2 inhibitor vs a placebo in cardiac surgery patients, a high-risk group for acute kidney injury 

"It’s extremely nasty, and if you look at pictures of this, you will have nightmares for weeks to come," he said.

The FDA found 12 cases from 2013 to 2018, seven in men and five in women. A theoretical connection between SGLT2 inhibitors could be as a follow-on effect of genital and urinary tract infections, leading to a cascade of events including endothelial damage and microthrombosis and then gangrene, Goldenberg said.

Goldenberg said he did a meta-analysis of 15 published large outcome trials of SGLT2 inhibitors, finding a total of 17 events, seven from SGLT2 arms and 10 in placebo. This analysis was inconclusive due to the limited number of events, he said. In looking at reviews of case reports, Goldenberg concluded that "diabetes is a risk factor for Fournier's [gangrene] but causality to SGLT2 inhibitors has not been proven."

GLP-1s and Surgery

At the end of the session, panelists fielded a question about a 2023 recommendation from the American Society of Anesthesiologists (ASA). That group last year suggested withholding GLP-1 receptor agonists for patients ahead of elective procedures, given the concerns about potential for delayed gastric emptying and an associated high risk for regurgitation and aspiration of gastric contents.

The ADA panelists were united in disagreeing with a blanket recommendation about pausing these drugs ahead of anesthesia . Tina Vilsbøll, MD, of the Steno Diabetes Center in Copenhagen, Denmark, said she wouldn’t initiate a GLP-1 right before a procedure but also would not have strong concerns for a patient well established on one of these drugs.

"I'm not too worried about it actually," she said.

John Buse, MD, PhD, the panel moderator and a professor at the University of North Carolina School of Medicine, Chapel Hill, said there's been "a lot of chaos and mayhem" resulting from this ASA recommendation. Buse said some clinicians have done preoperative ultrasound and examined the stomach contents or asked patients to refrain from eating.

Goldenberg said there's a need for a risk-stratification protocol to identify people more likely to have complications under anesthesia. Such screening might look for people who have symptoms of gastroparesis or who have been on a GLP-1 for a relatively short time and thus may be more likely to have an issue with gastric emptying.

But it would be "blatantly wrong" to employ a "blanket recommendation to stop GLP-1s in asymptomatic people who have been on them for ages," he said.

Billings reported honoraria or having served as a principal investigator for Bayer, Dexcom, Eli Lilly, Endogenex, Iventiva, Medtronic, Novo Nordisk, Pfizer, Sanofi, and Xeris. 

Buse has reported relationships in connection with other ADA presentations as follows: Novo Nordisk. Consultant: Corcept Therapeutics, Alkahest, Anji Pharmaceuticals, Aqua Medical, Altimmune Inc., AstraZeneca, Boehringer Ingelheim, CeQur, Eli Lilly, Embecta, GentiBio, Glyscend Inc., Mellitus Health, Metsera, Pendulum Therapeutics, Praetego LLC, Stability Health, Terns Pharmaceuticals, Insulet Corporation, Vertex Pharmaceuticals, vTv Therapeutics. Research Support: Corcept Therapeutics, Dexcom, Inc., Insulet. Other Relationship: Medtronic. Stock/Shareholder: Glyscend Inc., Mellitus Health, Pendulum Therapeutics, Praetego LLC, Stability Health. 

Goldenberg reported having received honoraria or research support from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, HLS, Janssen, Novo Nordisk, Sanofi. 

Vilsbøll has reported having the following relationships: Consultant: AstraZeneca. Advisory Panel: Boehringer Ingelheim. Speaker's Bureau: Mundipharma, Bayer Inc., Gilead Sciences, Inc. Advisory Panel: Novo Nordisk, Lilly Diabetes, Sanofi, Sun Pharmaceutical Industries Ltd. Research Support: Lilly Diabetes. 

Kerry Dooley Young is a freelance journalist based in Washington, DC. 

Send comments and news tips to [email protected] .

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The graphs exclude the fourth quarter of 2022 (October, November, and December) to address data missingness and censoring. MA indicates Medicare Advantage. The blue dashed line in all panels represents the launch of the ETC.

Each coefficient presented represents a comparison of home dialysis use in the End-Stage Renal Disease Treatment Choices (ETC) model in ETC regions relative to another cohort of interest. Age 65 years and older is compared to age younger than 65 years; female sex is compared to male sex; Black race and Hispanic ethnicity are compared to White race; any dual, partial dual, and full dual enrollment are compared to nondual enrollment; and the top poverty quartile is compared to all other quartiles.

eFigure 1. Visual Representation of the Timeline for CMS’ ETC Model (2019 – 2027)

eFigure 2. Sample Cohort Construction

eTable 1. Outcome measure technical definitions

eTable 2. Covariate measure technical definitions

eTable 3. Individual-Level Distribution of Characteristics Across ETC and Non-ETC Assigned Regions, Active-Model Time Period (2021-2022)

eTable 4. Individual-Level Distribution of Characteristics Across ETC and Non-ETC Assigned Regions, Pre-ETC Model Time Period (2017 - 2020)

eFigure 3. Event Study Plots

eTable 5. Triple Difference-in-Difference Results for Home Dialysis Utilization (%) Among Kidney Failure Patients, Stratified by Social Determinants of Health Factors (2017-2022)

eFigure 4. Unadjusted Home Dialysis Trends by Quarter, Stratified Analyses

eTable 6. Individual-Level Distribution of Characteristics Across ETC and Non-ETC Assigned Regions, Distributed by Staying in Traditional Medicare vs Switching to Medicare Advantage in Jan. 2021 (2020)

eTable 7. Pre-Period (2020) Person-Month Level Difference in Outcomes Between those who Stayed in Traditional Medicare vs those who Switched to Medicare Advantage in Jan. 2021, (2020)

eTable 8. Post-Period (2021) Person-Month Level Difference in Outcomes Between those who Stayed in Traditional Medicare vs those who Switched to Medicare Advantage in Jan. 2021, (2021)

eTable 9. Individual-Level Distribution of Characteristics Across ETC and Non-ETC Assigned Regions, Among Incident Kidney Failure Patients (2017-2022)

eTable 10. Difference-in-Difference Results Among Incident Kidney Failure Patients, Months 1-3 Post Treatment Incidence (2017-2022)

eTable 11. Difference-in-Difference Results Among Kidney Failure Patients, Sensitivity Analysis Using July 2019 Model Announcement Date (2017-2022)

eTable 12. Difference-in-Difference Results Among Kidney Failure Patients, Sensitivity Analysis Using September 2020 HRR Randomization Announcement Date (2017-2022)

eTable 13. Difference-in-Difference Results Among Kidney Failure Patients using HRR fixed effects (2017-2022)

eReferences

Data Sharing Statement

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Koukounas KG , Kim D , Patzer RE, et al. Pay-for-Performance Incentives for Home Dialysis Use and Kidney Transplant. JAMA Health Forum. 2024;5(6.9):e242055. doi:10.1001/jamahealthforum.2024.2055

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Pay-for-Performance Incentives for Home Dialysis Use and Kidney Transplant

• 1 Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
• 2 Providence VA Medical Center, Providence, Rhode Island
• 3 Regenstrief Institute, Indianapolis, Indiana
• 4 Division of Transplant Surgery, Department of Surgery, Indiana University School of Medicine, Indianapolis
• 5 Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta, Georgia
• 6 Kidney Research Institute, Division of Nephrology, Department of Medicine, University of Washington School of Medicine, Seattle
• 7 Warren Alpert Medical School of Brown University, Providence, Rhode Island
• 8 Division of Kidney Disease and Hypertension, Rhode Island Hospital, Providence
• 9 Partnered Evidence-Based Policy Resource Center, VA Boston Healthcare System, Boston, Massachusetts
• 10 Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island

Question   How was the Centers for Medicare & Medicaid Services’ End-Stage Renal Disease Treatment Choices (ETC) model associated with use of home dialysis and kidney transplant in the first 2 years of implementation?

Findings   In this cross-sectional study of 724 406 traditional Medicare beneficiaries with kidney failure, there were no statistically significant differences in the use of home dialysis or kidney transplant between those treated in regions randomly assigned to the ETC model and those treated in control regions.

Meaning   In its first 2 years of implementation, the ETC payment model has shown little impact in further promoting the uptake of home dialysis and kidney transplant among patients with kidney failure.

Importance   The Centers for Medicare & Medicaid Services’ mandatory End-Stage Renal Disease Treatment Choices (ETC) model, launched on January 1, 2021, randomly assigned approximately 30% of US dialysis facilities and managing clinicians to financial incentives to increase the use of home dialysis and kidney transplant.

Objective   To assess the ETC’s association with use of home dialysis and kidney transplant during the model’s first 2 years and examine changes in these outcomes by race, ethnicity, and socioeconomic status.

Design, Setting, and Participants   This retrospective cross-sectional study used claims and enrollment data for traditional Medicare beneficiaries with kidney failure from 2017 to 2022 linked to same-period transplant data from the United Network for Organ Sharing. The study data span 4 years (2017-2020) before the implementation of the ETC model on January 1, 2021, and 2 years (2021-2022) following the model’s implementation.

Exposure   Receiving dialysis treatment in a region randomly assigned to the ETC model.

Main Outcomes and Measures   Primary outcomes were use of home dialysis and kidney transplant. A difference-in-differences (DiD) approach was used to estimate changes in outcomes among patients treated in regions randomly selected for ETC participation compared with concurrent changes among patients treated in control regions.

Results   The study population included 724 406 persons with kidney failure (mean [IQR] age, 62.2 [53-72] years; 42.5% female). The proportion of patients receiving home dialysis increased from 12.1% to 14.3% in ETC regions and from 12.9% to 15.1% in control regions, yielding an adjusted DiD estimate of −0.2 percentage points (pp; 95% CI, −0.7 to 0.3 pp). Similar analysis for transplant yielded an adjusted DiD estimate of 0.02 pp (95% CI, −0.01 to 0.04 pp). When further stratified by sociodemographic measures, including age, sex, race and ethnicity, dual Medicare and Medicaid enrollment, and poverty quartile, there was not a statistically significant difference in home dialysis use across joint strata of characteristics and ETC participation.

Conclusions and Relevance   In this cross-sectional study, the first 2 years of the ETC model were not associated with increased use of home dialysis or kidney transplant, nor changes in racial, ethnic, and socioeconomic disparities in these outcomes.

Kidney failure (also known as end-stage kidney disease) is a lethal condition in which dialysis treatment or kidney transplant is required to sustain life. In 2021, more than 800 000 individuals in the US lived with kidney failure. 1 Most patients are treated with in-center hemodialysis, a time-intensive modality requiring thrice-weekly, in-person treatments at dialysis centers followed by prolonged postdialysis symptoms. 2 Research has suggested that some patients and clinicians prefer dialyzing at home, 3 - 5 which allows for greater flexibility and independence, shorter recovery times, and some improved mortality outcomes. 6 , 7 As of 2021, about 14.1% of prevalent patients received home dialysis, 1 with higher use among White patients compared to Black or Hispanic patients, even though as many as 85% of patients are thought to be medically eligible for this service. 8 , 9 Furthermore, the national prevalence of kidney transplant among patients undergoing dialysis was 4.0 per 100 person-years in 2021, below that of other high-income countries. 1

In 2021, the Centers for Medicare & Medicaid Services (CMS) launched the End-Stage Renal Disease Treatment Choices (ETC) model, which sought to increase the use of home dialysis, kidney transplant, and transplant wait-listing among traditional Medicare beneficiaries. 4 The model randomly selected 30% of the nation’s hospital referral regions (HRRs) for mandatory participation, such that all dialysis facilities and managing clinicians in selected HRRs are evaluated on model performance measures. Participants received payment incentives and penalties on the basis of their attributed patients’ use of home dialysis and kidney transplant or wait-listing. 10 The model will run from 2021 though 2027, during which time outcomes in all participating facilities will be measured against their own historic performance and the performance of nonparticipating peers. Achievement and improvement relative to these benchmarks are scored and translated into payment adjustments, ranging from −5% to 4% in the first 2 years of the model. 10

Evaluations of the model’s first year have reported mixed findings. One study found a small increase in initiation of home dialysis among incident patients in ETC relative to control regions. 11 Another study, examining incident Medicare beneficiaries 66 years and older, found no meaningful difference in home dialysis use stemming from the ETC model. 12 Our previous research evaluating ETC’s impact on participating safety-net facilities (those serving a high proportion of patients with social risk factors) found that the model disproportionately penalized high-risk facilities. 13 Published evaluations to date have focused on first-year model outcomes, have been limited to the incident patient population, and did not separately examine effects for racial and ethnic minoritized populations or those with low income.

In this cross-sectional study, we evaluate the association of the ETC model with the use of home dialysis and kidney transplant during the model’s first 2 years. Given extensive evidence of racial and socioeconomic disparities in access to home dialysis and transplant, 3 , 8 , 14 we additionally examined changes in these outcomes for Black, Hispanic, and Medicare and Medicaid dual eligible beneficiaries.

This study analyzed claims and enrollment data for traditional Medicare beneficiaries from 2017 to 2022, linked to same-period transplant data from the United Network for Organ Sharing. The United Network for Organ Sharing serves as the nation’s transplant system, collecting and reporting data on every organ transplant conducted in the US. 15 The study data span 4 years (2017-2020) before the implementation of the ETC model on January 1, 2021, and 2 years (2021-2022) following the model’s implementation. Additional detail on study methods can be found in the eMethods in Supplement 1 .

The ETC model was proposed in July 2019 and finalized in September 2020 with the randomized selection of participating HRRs, stratified by census region. 16 Despite randomization, there were preintervention imbalances in facility and patient characteristics, as well as use of home dialysis between ETC and non-ETC regions. 17 To account for this, we used a difference-in-differences (DiD) approach to estimate changes in outcomes among patients treated in regions randomly selected for ETC participation, compared with concurrent changes among patients treated in control regions. The model was implemented on January 1, 2021, and is set to run through 2027 (eFigure 1 in Supplement 1 ), during which time CMS will monitor yearly performance for participating facilities and make corresponding payment adjustments to all reimbursements under Medicare’s End-Stage Renal Disease Prospective Payment System. In the first 2 years, these adjustments ranged from bonuses of 4% to penalties of −5%, with this range widening as the model progresses. 10 The institutional review board at Brown University approved the study.

The sample was constructed at the patient-month level, consisting of all qualifying months associated with individuals who met ETC model inclusion criteria, in an approach that mirrors how CMS conducts model measurement and attribution. We began by identifying the set of traditional Medicare beneficiaries with an end-stage kidney disease enrollment designation and aggregated their associated data at the month level for all months with 1 or more claims demonstrating the receipt of maintenance dialysis during the study period. 18 , 19 Consistent with ETC model criteria, we excluded any person-months where beneficiaries did not have both Parts A and B coverage, were enrolled in Medicare Advantage (MA), lived outside of the US, were younger than 18 years, received dialysis care in hospice or nursing home settings, or had acute kidney injury, Alzheimer disease, or dementia (eFigure 2 in Supplement 1 ). 10 , 16 Exclusions were done at the person-month level, such that individuals meeting the criteria previously listed may not have been fully excluded from the sample if for some months they were not subject to an exclusion criteria (eg, they began dialysis with no Alzheimer disease or dementia diagnosis but later received one). We used the HRR of the patient’s dialysis center to track ETC participation status, using CMS’s published list of 95 randomly selected HRRs to define the study’s treatment group, with all others as the control group. 20 For patients who saw multiple dialysis centers in a single month, we prioritized the HRR of their most-used dialysis center in that month, excluding 8221 person-months (757 individuals) for whom an associated HRR could not be found. Transition from ETC-participating (ETC) to non–ETC-participating (control) regions was not common in the study sample, as fewer than 5% of all study participants experienced any transition over the 5-year study period. The final study sample included 724 406 unique patients.

Study measures compared outcomes in ETC regions to those in control regions across the prepolicy (2017-2020) and postpolicy (2021-2022) periods. Primary outcomes of interest were home dialysis and kidney transplant, reflecting those studied by CMS in the ETC model. While CMS measures kidney transplant and transplant wait-listing as part of its ETC model evaluation, data limitations prevented us from incorporating transplant wait-listing in this study. Secondary outcomes included measures that could plausibly be affected by the ETC model, including 3-month mortality, hospital admissions, and disenrollment to MA (eTable 1 in Supplement 1 ). Three-month mortality was calculated excluding the last 3 months of 2022 to account for 2023 data censoring. The concurrent launch of the 21st Century Cures Act on January 1, 2021, which expanded MA enrollment to persons with kidney failure and resulted in a large exit of these patients to MA, prompted interest in the evaluation of any differential disenrollment to MA across ETC and non-ETC regions. 21 All outcome measures are calculated at the month level, such that they reflect the unique number of monthly occurrences divided by the total person-months for the study group, except 3-month mortality, which is calculated using the 3-month period from the month of observation.

We conducted a DiD analysis comparing changes in monthly outcome measures between ETC and control regions (first difference) across prepolicy and postpolicy periods (second difference) to account for baseline differences across ETC and control regions. 17 We adjusted the analysis for monthly age, sex, race and ethnicity (derived from the Centers for Medicare & Medicaid Services’ member enrollment file), dual Medicare and Medicaid enrollment (hereafter, dual status), reason for Medicare entitlement, zip code–level poverty and college completion (obtained from the American Community Survey), 22 and monthly county-level COVID-19 mortality rates (obtained from The New York Times ) 23 (eTable 2 in Supplement 1 ). We additionally included month and census-region fixed effects to reflect the cyclical timing of dialysis treatment and the level at which model randomization was stratified. Standard errors were clustered at the level of treatment randomization (HRR) (eAppendix in Supplement 1 ).

To assess disparities in outcomes across measures of social risk, triple-difference analyses for home dialysis use were conducted across demographic and socioeconomic strata. These stratifications included age (<65 years vs ≥65 years), sex, race and ethnicity (Hispanic, non-Hispanic Black, and non-Hispanic White), dual status (nondual, any dual, partial dual, and full dual), and poverty quartile. The same covariates and fixed effects from the main DiD analysis were included, exempting those that overlapped with the strata of interest (eAppendix in Supplement 1 ).

Additional sensitivity analyses included (1) assessments of the preimplementation parallel trends between ETC and control regions 24 ; (2) a change in the end point of the prepolicy period to reflect model announcement (July 2019) or (3) model finalization through HRR randomization (September 2020); (4) sample restriction to incident patients undergoing dialysis, studying outcomes for the 3-month period following dialysis initiation; (5) evaluation of 1-year, pre-ETC and post-ETC use trends among patients who were not included in the ETC model due to transition to MA on January 1, 2021; and (6) the use of HRR fixed effects in place of census-region fixed effects. All analyses were conducted in Stata, version 17 (StataCorp), with a 2-sided P  < .05 considered statistically significant.

The study population included 724 406 persons with kidney failure (mean [IQR] age, 62.2 [53-72] years; 42.5% female), reflecting 18 118 190 person-months from January 1, 2017, to December 31, 2022. Across the full study period, ETC regions, compared with control regions, had a higher proportion of non-Hispanic Black patients (35.4% vs 30.5%) and a lower proportion of non-Hispanic White patients (48.7% vs 50.4%) and Hispanic patients (5.9% vs 8.6%); the ETC sample overrepresented the Southern (47.8% vs 43.8%) and Northern (17.2% vs 14.7%) US Census Bureau regions compared to the Midwest (17.8% vs 20.8%) and West (17.2% vs 20.6%). Finally, ETC regions vs control regions had slightly fewer dual beneficiaries (41.5% vs 42.8%), primarily driven by fewer full dual beneficiaries (32.7% vs 35.1%). Other covariates demonstrated relative balance across cohorts ( Table 1 ). These trends remained constant across both postpolicy (eTable 3 in Supplement 1 ) and prepolicy (eTable 4 in Supplement 1 ) time periods.

Unadjusted trends over time demonstrated that control regions had consistently higher baseline use of home dialysis than ETC regions—on average 12.9% compared to 12.1% in the prepolicy period ( Figure 1 ). The test of parallel preimplementation outcome trends in eFigure 3 in Supplement 1 did not suggest a statistically significant change in this gap over time between ETC and control regions.

There were no statistically significant associations between implementation of the ETC model and changes in any of the primary and secondary outcomes ( Table 2 ). Between the prepolicy and postpolicy periods, home dialysis use increased by 2.2 percentage points (pp), from 12.1% to 14.3%, in ETC regions and 2.2 pp, from 12.9% to 15.1%, in control regions, resulting in an adjusted DiD estimate of −0.2 pp (95% CI, −0.7 to 0.3 pp). For kidney transplant, there was an increase of 0.03 pp in ETC regions (0.29% to 0.32%) and 0.01 pp in control regions (0.29% to 0.30%), resulting in an adjusted DiD estimate of 0.02 pp (95% CI, −0.01 to 0.04 pp). Unadjusted trends over time for primary and secondary outcomes can be seen in Figure 1 .

Figure 2 demonstrates the results of triple-difference analyses on home dialysis use across different stratifications of social risk. No statistically significant associations with the ETC model were observed for any of the subgroups. Expanded results are summarized in eTable 5 in Supplement 1 . Unadjusted home dialysis trends over time for stratified populations can be seen in eFigure 4 in Supplement 1 .

When comparing patients with kidney failure who transitioned to MA on January 1, 2021, to those who remained in traditional Medicare, prepolicy differences were observed in both patient characteristics (eTable 6 in Supplement 1 ) as well as use of home dialysis, kidney transplant, and hospital admission (eTable 7 in Supplement 1 ). Differences in patient characteristics mirrored those shown in prior work, with higher proportions of patients who were non-Hispanic Black, were from the South, had a disability, and had dual eligibility or lower income transitioning to MA. 21 In both ETC- and non-ETC–participating regions, home dialysis use in 2020 was 2.7 pp to 3.1 pp higher among patients who stayed in traditional Medicare compared to those who disenrolled to MA. Furthermore, in the year following MA transition, lower rates of mortality and kidney transplant were observed among those disenrolled to MA compared to those who remained in traditional Medicare (eTable 8 in Supplement 1 ).

When the population was limited to incident patients in the 3-month period following dialysis initiation, a small but statistically significant effect in favor of the ETC policy change was observed in the unadjusted home dialysis DiD among this cohort (1.1 pp; 95% CI, 0.02-2.2 pp), as well as in adjusted mortality (−0.3 pp; 95% CI, −0.6 to −0.03 pp) and hospital admissions (−7.0 pp; 95% CI, −13.0 to −0.9 pp). A description of the incident patient cohort can be found in eTable 9 in Supplement 1 , and full DiD results are summarized in eTable 10 in Supplement 1 . The main study results are robust to an adjusted prepolicy end date of either model announcement in July 2019 (eTable 11 in Supplement 1 ) or HRR randomization in September 2020 (eTable 12 in Supplement 1 ), as well as to adjustment of fixed effects from Census region to HRR (eTable 13 in Supplement 1 ).

In the first 2 years of CMS’s ETC model, we observed no statistically significant differences in the use of home dialysis or kidney transplant among model participants compared to nonparticipants. Despite temporal increases in home dialysis and kidney transplant use nationally, the ETC model was not associated with differentially increased use of these services among patients treated by model participants relative to those treated by dialysis facilities in control regions. Secondary outcomes, including 3-month mortality, hospital admissions, and disenrollment to MA, similarly showed no statistically significant differences between patients treated in ETC vs control regions. Finally, when further stratified by sociodemographic measures including age, sex, race and ethnicity, dual status, and poverty quartile, home dialysis use did not meaningfully differ across joint strata of characteristics and ETC participation.

The concurrent launch of the 21st Century Cures Act on January 1, 2021, meant that a substantial portion of patients with kidney failure left traditional Medicare for MA at the exact time that the ETC model launched, making them ineligible for model participation. 21 Lower prepolicy use of home dialysis and kidney transplant among the population that transitioned to MA suggests that some of the observed increases in these outcomes among traditional Medicare beneficiaries may be an artifact of individuals with lower service use disproportionately switching to MA after January 1, 2021.

This research expands on prior ETC evaluations in important ways. First, it includes both the first and second years of the model implementation and demonstrates that additional time and model experience has not improved outcomes relative to control regions. Second, it evaluates results across the entire traditional Medicare kidney failure population (incident and prevalent patients) using claims data, which allow us to track documented dialysis modality over time. Prior research has found modest effects of the ETC model in the first year when limited to incident patients but only when using data from CMS’s Medical Evidence Report (form 2728). 11 This form reflects data collected at dialysis initiations and is not updated as treatment continues. Thus, the present research adds to the literature by studying the real-time modality patients receive over the model period. Finally, we evaluated differential policy impact by race and ethnicity and socioeconomic status.

The ETC model’s limited influence on home dialysis and kidney transplant use in the first 2 years may be attributed to several factors. First, home dialysis use in the US has been steadily increasing since 2009, likely triggered by that year’s expansion of the Prospective Payment System. 1 , 25 As such, there is an existing financial incentive to increase home dialysis use that extends to all national dialysis facilities. Second, the use of home dialysis requires stable housing, as well as the ability to learn and self-administer complex medical regimens, family and caregiver support, and the financial resources for potential home modifications and higher utility bills. 26 , 27 The application of pay-for-performance incentives to dialysis facilities does not address these patient-level barriers. Third, the process of kidney transplant is lengthy, complex, and requires several steps from referral to evaluation, wait-listing, and ultimately transplant. As such, it may take several years to observe any impact from the ETC model on access to transplant. Fourth, the consolidation of the dialysis treatment market means that 2 large parent companies operate approximately 70% of the facilities present in both ETC and control regions. Therefore, the payment penalties in one set of facilities may be offset by revenue or bonuses from other facilities owned by the same company. Additionally, it is possible that care-management practices may be standardized across all facilities operated by a large dialysis organization, which may reduce the possibility that these organizations introduced interventions in only their ETC-exposed facilities. These factors may potentially blunt the effect of financial incentives.

The ETC model is currently set to run through 2027, during which time the payment bonuses and penalties will ultimately escalate to 8% and −10%, respectively. 10 The disproportionate penalization of facilities serving patients with high social risk 13 and the lack of consistent evidence that the ETC model is improving outcomes raise concerns about the continued implementation of the model as is through its scheduled end date. CMS could consider providing additional resources to facilities, particularly those that treat patients with higher social risk, to help overcome structural barriers that prevent uptake of home dialysis or kidney transplant. 27 - 29 Research should continue to monitor the ETC’s impact on patients and safety-net dialysis facilities to ensure that escalating penalizes do not contribute to widening disparities.

This study has several limitations. First, we cannot observe the potential ETC model spillovers to those not enrolled in traditional Medicare. Second, we are unable to track transplant wait-listing in the data and thus have not studied the ETC model’s effect on this precursor to kidney transplant receipt. Third, the study was limited to the first 2 years of the ETC model.

In this cross-sectional study of 724 406 traditional Medicare beneficiaries with kidney failure, we observed no statistically significant changes in the use of home dialysis or kidney transplant in the first 2 years of CMS’s ETC model. These findings, coupled with prior research that demonstrates the disproportionate penalization of safety-net dialysis facilities, supports careful consideration of the model’s future implementation and efficacy within this at-risk population.

Accepted for Publication: May 15, 2024.

Published: June 30, 2024. doi:10.1001/jamahealthforum.2024.2055

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Koukounas KG et al. JAMA Health Forum .

Corresponding Author: Amal N. Trivedi, MD, MPH, Department of Health Service, Policy and Practice, Brown University School of Public Health, 121 S Main St, 7th Floor, Providence, RI 02907 ( [email protected] ).

Author Contributions: Ms Koukounas had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Patzer, Wilk, Drewry, Thorsness, Trivedi.

Acquisition, analysis, or interpretation of data: Koukounas, Kim, Wilk, Lee, Drewry, Mehrotra, Rivera-Hernandez, Meyers, Shah, Schmid, Trivedi.

Drafting of the manuscript: Koukounas, Lee, Schmid, Trivedi.

Critical review of the manuscript for important intellectual content: Kim, Patzer, Wilk, Drewry, Mehrotra, Rivera-Hernandez, Meyers, Shah, Thorsness, Trivedi.

Statistical analysis: Koukounas, Kim, Wilk, Lee, Schmid.

Obtained funding: Patzer.

Administrative, technical, or material support: Meyers, Trivedi.

Supervision: Patzer.

Conflict of Interest Disclosures: Ms Koukounas reported consulting fees from Group 17a outside the submitted work. Dr Rivera-Hernandez reported grants from the National Institute on Minority Health and Health Disparities (R01MD016961), the National Institute on Aging (K01AG057822, RF1AG078262), and Brown University (OVPR Research Seed Award) outside the submitted work. Dr Shah reported personal fees from Otsuka and Calliditas outside the submitted work. Dr Trivedi reported grants from the US Department of Veterans Affairs and the US Department of Defense outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by grant R01MD017080 from the National Institute of Minority Health and Health Disparities, grant R01HS28285 from the Agency for Healthcare Research and Quality, and grants R01DK113298 and K01DK128384 from the National Institute of Diabetes and Digestive and Kidney Disease.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the US Department of Veterans Affairs or the US government.

Meeting Presentation: This study was presented at the AcademyHealth 2024 Annual Research Meeting; June 30, 2024; Baltimore, Maryland.

Data Sharing Statement: See Supplement 2 .

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Language: English | French

Acute kidney injury and liver disease in an American bulldog with suspected leptospirosis

A 6-year-old spayed female American bulldog was brought to a veterinary clinic with a 3-day history of vomiting, lethargy, anorexia, icterus, hemorrhagic diarrhea, and oliguria. The dog’s clinical signs, complete blood (cell) count, serum biochemistry, urinalysis, and diagnostic imaging were indicative of acute kidney injury and acute hepatopathy consistent with leptospirosis. Treatment for leptospirosis was initiated but, due to the dog’s lack of response and progression of clinical signs, euthanasia was ultimately elected after 3 d of hospitalization. The dog tested negative for Leptospira spp. on ELISA; urine, blood, and tissue PCRs; and immunohistochemistry. This case demonstrates that confirmation of leptospirosis can be challenging, even in an animal with the expected clinical presentation. Therefore, limitations of the diagnostic tests available, as well as the possibility of other, less likely differential diagnoses such as toxicosis, must be considered.

Résumé

Lésion rénale aiguë et maladie hépatique chez un bouledogue américain avec leptospirose suspectée. Une femelle bouledogue américain stérilisée âgée de 6 ans a été présenté à une clinique vétérinaire avec une histoire d’une durée de 3 jours de vomissement, léthargie, anorexie, ictère, diarrhée hémorragique et oligurie. Les signes cliniques de la chienne, un comptage cellulaire sanguin complet, une biochimie sérique, une analyse d’urine et de l’imagerie diagnostique étaient indicateur de lésion rénale aiguë et d’hépatopathie aiguë compatibles avec la leptospirose. Un traitement pour la leptospirose a été instauré mais, étant donné l’absence de réponse de l’animal et la progression des signes cliniques, l’euthanasie a finalement été décidée après 3 jours d’hospitalisation. L’animal s’est avéré négatif par ELISA pour Leptospira spp.; l’urine, le sang et les tissus étaient également négatifs par PCR; et par immunohistochime. Ce cas illustre le fait que la confirmation de la leptospirose peut représenter un défi, même chez un animal avec la présentation clinique attendue. Ainsi, les limites des tests diagnostiques disponibles, de même que la possibilité d’autres diagnostics différentiels moins probables, tel qu’une toxicose, doivent être considérés.

(Traduit par D r Serge Messier)

Case description

In August 2023, a 6-year-old spayed female American bulldog was brought to a veterinary clinic in southern Ontario with a 3-day history of vomiting, lethargy, anorexia, hemorrhagic diarrhea, and oliguria. The animal was up to date on vaccinations for rabies, canine distemper virus, canine adenovirus Type 2, canine parvovirus, and canine parainfluenza virus, with no history of Leptospira vaccination. The dog had a history of conjunctivitis, otitis externa, and perivulvar dermatitis, all of which were successfully treated. There had been no health concerns in the past year. The dog had no known travel history outside Ontario.

On physical examination, the dog was quiet, alert, and responsive, with a capillary refill time < 2 s, heart rate of 90 beats per min, respiratory rate of 28 breaths per min, and rectal temperature of 37.7°C. The dog was 5% dehydrated, appeared to experience pain on abdominal palpation, and was severely icteric ( Figure 1 ).

Severe, diffuse icterus of the dog’s skin, with petechiae and ecchymoses in the caudal abdominal region and hind limbs.

Several diagnostic tests were ordered following physical examination. A complete blood (cell) count (CBC) revealed a mild leukocytosis with mild neutrophilia [12.77 × 10 9 /L; reference interval (RI): 2.95 to 11.64 × 10 9 /L] and mild monocytosis (1.38 × 10 9 /L; RI: 0.16 to 1.12 × 10 9 /L), consistent with a stress response. Serum biochemistry revealed azotemia (urea: > 46.4 mmol/L, RI: 2.5 to 9.5 mmol/L; creatinine: 1269 μmol/L, RI: 44 to 159 μmol/L), hyperphosphatemia (> 5.20 mmol/L; RI: 0.81 to 2.20 mmol/L), hyponatremia (135 mmol/L; RI: 144 to 160 mmol/L), hypochloremia (95 mmol/L; RI: 109 to 122 mmol/L), hyperglobulinemia (51 g/L; RI: 25 to 45 g/L), elevated alanine aminotransferase (ALT: 341 U/L; RI: 10 to 125 U/L), elevated alkaline phosphatase (ALP: 1072 U/L; RI: 23 to 212 U/L), elevated gamma-glutyl transferase (GGT: 12 U/L; RI: 0 to 11 U/L), hyperbilirubinemia (> 477 μmol/L; RI: 0 to 15 μmol/L), and elevated amylase (1573 U/L; RI: 500 to 1500 U/L). Results of a SNAP (IDEXX) canine pancreatic lipase test were abnormal. Urinalysis of a cystocentesis sample revealed a urine specific gravity of 1.018, proteinuria (500 mg/dL; RI: < 50 mg/dL), pyuria (8/HPF; RI: 0 to 3/HPF), glucosuria (50 mg/dL), elevated urobilinogen (8 mg/dL; RI: 0.2 to 1.0 mg/dL), bilirubinuria (6 mg/dL), hematuria (> 50/HPF), elevated nonsquamous epithelial cell count (3 to 5/HPF), and suspected presence of bacterial cocci and rods. Abdominal radiographs revealed mild bilateral renal enlargement and abdominal ultrasound revealed enlargement of all abdominal lymph nodes. The diagnostic test results were suspicious for acute kidney injury and acute hepatopathy. The top differential diagnosis was leptospirosis. Other initial differential diagnoses included pyelonephritis, cholangiohepatitis, neoplasia, sepsis, and toxicosis. The dog’s prognosis was guarded to grave.

The dog was hospitalized on the day of presentation and treatment was initiated with ampicillin (Sterile Ampicillin Sodium Injection 250 mg; Teva Canada, Scarborough, Ontario), 22 mg/kg, IV, q6 to 8h, due to suspected leptospirosis. Gastroprotectants, including famotidine (Famotidine Omega 20 mg/2 mL; Omega Laboratories, Montréal, Quebec), 1 mg/kg, SC, q12h and sucralfate (Sulcrate 1 g/5 mL; Aptalis Pharma Canada, Markham, Ontario), 38.5 mg/kg, PO, q12h, were given due to the dog’s vomiting and in case of uremic gastritis. Additional medications given included S-adenosylmethionine (Denosyl 425 mg tablets; Nutramax Laboratories, Lancaster, South Carolina, USA), 16 mg/kg, PO, q24h, for liver protection; maropitant (Cerenia 10 mg/mL; Zoetis Canada, Kirkland, Quebec), 1 mg/kg, IV, q24h, as an anti-emetic; as well as methadone (Comfortan 10 mg/mL; Dechra Veterinary Products, Pointe-Claire, Quebec), 0.2 mg/kg, IV, q6h and gabapentin (Apo-Gabapentin 300 mg capsules; Apotex, Toronto, Ontario), 11.5 mg/kg, PO, q12h, for analgesia. Intravenous crystalloid fluids (Plasma-Lyte A 1000 mL; Baxter Corporation, Mississauga, Ontario) were given, starting at 1.5× maintenance rate and adjusted as needed. The dog was transferred to an emergency clinic overnight and returned the next morning. A SNAP Leptospira test (WITNESS Lepto; Zoetis Canada) was done that night and the result was interpreted as faintly positive.

Hematology and serum chemistries were rechecked the day after initial presentation. Most values were consistent with those on the previous day, with the major exceptions of a mild, non-regenerative normocytic hyperchromic anemia (red blood cells: 4.34 × 10 12 /L, RI: 5.65 to 8.87 × 10 12 /L; hematocrit: 0.273, RI: 0.373 to 0.617; hemoglobin: 109 g/L, RI: 131 to 205 g/L; MCHC: 399 g/L, RI: 320 to 379 g/L; reticulocytes: 6.5 K/μL, RI: 10 to 110 K/μL) and mild thrombocytopenia (116 × 10 9 /L; RI: 148 to 484 × 10 9 /L). A coagulation profile was performed and revealed a prolonged partial thromboplastin time (PTT: 18.5 s; RI: 10.6 to 16.8 s). A fecal parasitology antigen profile was negative for Giardia , flea tapeworm, hookworm, whipworm, and roundworm. Urine and blood PCR tests were negative for Leptospira spp. and serum ELISA was negative for Leptospira spp. antibodies. Despite these results, leptospirosis was still the top differential diagnosis based on clinical presentation, clinical pathology results, and urine abnormalities.

There was no improvement by the second day of hospitalization. Because of concern for a possible non- Leptospira infection, enrofloxacin (Baytril 2.27%; Elanco Canada, Mississauga, Ontario), 10 mg/kg, IV, q24h, was added to the dog’s treatment plan. In addition, metronidazole (Metronidazole 5 mg/mL; Baxter), 10 mg/kg, IV, q12h, was given because of vomiting and diarrhea. By the second night of hospitalization, the animal’s oliguria had progressed to anuria. Consequently, a bolus of furosemide (Furosemide Injection USP 20 mg/2 mL; Teligent Canada, Mississauga, Ontario), 2 mg/kg, IV, was given, followed by an additional dose the next day, with the goal of increasing urine output.

A CBC on the third day of hospitalization revealed progression to a moderate neutrophilia (23.44 × 10 9 /L), resolution of the anemia, and an improved platelet count (204 × 10 9 /L). An additional abdominal ultrasound revealed thickening of the gastric wall, thought to be uremic gastritis secondary to kidney and liver disease, as well as the previously noted renomegaly and abdominal lymphadenopathy. On physical examination, petechiae and ecchymoses were identified in the axillary region, caudal abdominal region, and hind limbs ( Figure 1 ). These, in combination with the dog’s low platelet count and prolonged PTT, were suggestive of disseminated intravascular coagulation. By this point, the dog was showing clinical signs of tachypnea and dyspnea.

Due to the progression of clinical signs over several days and the dog’s grave prognosis, the client elected for euthanasia on the third day of hospitalization. On postmortem examination, severe, diffuse icterus of the skin, mucous membranes, and most abdominal organs was noted, as well as mild bilateral renal enlargement (~10 cm × 6 cm × 5 cm) with mild loss of corticomedullary definition, and mild, diffuse thickening of the gastric wall (~0.75 cm).

Tissue samples were sent to the University of Guelph Animal Health Laboratory (Guelph, Ontario). The major histologic findings were subacute renal tubular degeneration ( Figure 2 ) and hepatocellular necrosis ( Figure 3 ), consistent with leptospirosis. Additional lesions included edema and vascular congestion in the submucosa of the stomach, suggestive of uremic gastritis, as well as pulmonary alveolar hemorrhage and collapse with large numbers of circulating neutrophils in the alveolar septa, which could also support a diagnosis of leptospirosis.

Microscopic image showing severe, acute, renal tubular degeneration/necrosis, characterized by cortical tubule cell hypertrophy with vacuolated cytoplasm (black arrow) and nuclear pyknosis (blue arrow). Hematoxylin and eosin, 20× magnification.

Microscopic image showing severe, acute, hepatocellular necrosis with abundant mitotic figures (blue circles), as well as bile plugs within canaliculi (green circle), indicating cholestasis. Hematoxylin and eosin, 40× magnification.

Additional postmortem diagnostic tests included immunohistochemistry and Leptospira spp. PCR on kidney and liver samples. The results were negative for both tests.

Leptospirosis is a difficult disease to diagnose based on clinical signs alone due to its variety of presentations and lack of pathognomonic signs. Clinical signs may include lethargy, inappetence, vomiting, diarrhea, oliguria, polyuria, polydipsia, icterus, fever, and hypothermia ( 1 ). Dogs with leptospiral pulmonary hemorrhagic syndrome may also show signs of acute respiratory distress, such as dyspnea and tachypnea ( 2 ). Complete blood (cell) count results associated with leptospirosis may include thrombocytopenia, anemia, and leukocytosis with neutrophilia. Serum biochemistry findings indicative of acute kidney injury and acute hepatopathy, such as azotemia, hyperbilirubinemia, elevated ALT, elevated AST, elevated ALP, hyponatremia, and hyperphosphatemia, can all support the diagnosis of leptospirosis ( 1 ). Due to the rapid progression of clinical signs and potentially fatal outcome, the recommendation is to treat all dogs with clinical signs and to interpret diagnostic test abnormalities suggestive of acute kidney injury and hepatic disease as if they identify the dog has leptospirosis, until proven otherwise ( 2 ). Additional diagnostic findings associated with leptospirosis may include hematuria and glucosuria on urinalysis; and splenomegaly, hepatomegaly, and renomegaly on abdominal radiographic and ultrasound imaging ( 1 ).

In the case described here, all initial diagnostic test results were supportive of leptospirosis, with no other obvious major differential diagnoses, leading to immediate treatment with antimicrobials. For dogs with signs of acute leptospirosis, including gastrointestinal signs, the recommendation is to begin treatment with a beta lactam antibiotic, such as ampicillin 20 mg/kg, IV, q6h. When the gastrointestinal signs resolve, the antibiotic can be changed to doxycycline ( 2 ). In this case, the dog’s gastrointestinal signs did not resolve; therefore, the dog was maintained on ampicillin for the duration of hospitalization. Concurrent fluoroquinolone use is typically not advised due to the risk of contributing to resistance in other bacteria ( 2 ). However, for this dog, enrofloxacin treatment was started in case there was another underlying bacterial infection such as pyelonephritis or cholangiohepatitis. The diagnosis of leptospirosis was not confirmed in this case and no measurable improvement was seen in response to ampicillin alone.

There are several possible confirmatory tests for leptospirosis, each with its own benefits and limitations. In this case, the antemortem tests conducted were Leptospira spp. antibody ELISA and Leptospira spp. urine and blood PCRs. Although the negative results for all these tests did not support the suspected diagnosis, leptospirosis could not be definitively ruled out. False negative results for Leptospira spp. antibody ELISAs are more likely to occur in the early stages of disease because antibody development typically requires 5 to 7 d ( 3 ). This is why no additional serologic testing, such as a microscopic agglutination test (MAT), was undertaken in this case. However, a MAT may have been beneficial in this case, as MAT is considered the current diagnostic test of choice for dogs with suspected leptospirosis ( 2 ). The “gold standard” for leptospirosis diagnosis is paired MATs, with the first MAT done on initial presentation and the second done 7 to 14 d later, with seroconversion defined as a 4-fold or greater change in titer ( 2 , 3 ). An additional benefit to MATs is the ability to differentiate Leptospira serogroups, though this may be limited due to cross-reactivity ( 2 ). False positives may occur if dogs have been vaccinated for Leptospira spp. In this case, the dog had never received a Leptospira vaccination, so this would not have been a concern if an MAT had been attempted ( 4 ).

Blood and urine PCR tests are of diagnostic value to identify animals with active Leptospira infections, though false negatives can occur with low numbers of bacteria, the presence of PCR inhibitors, and in animals that have begun antimicrobial treatment before sample collection ( 2 ). To maximize the chances of successfully diagnosing leptospirosis with PCR, blood and urine samples should be collected and stored before commencing antimicrobial treatment ( 2 ). In this case, both blood and urine PCRs were used. When financial limitations are present, blood PCR testing is recommended over urine initially, because Leptospira spp. levels are higher in blood than in urine for the first 10 d of disease ( 2 ). In addition, urinary shedding of Leptospira spp. is intermittent, which can also cause false negative results for urine PCR tests ( 2 ). Some healthy dogs can have Leptospira spp. in their urine, so a positive urine PCR should be interpreted in conjunction with compatible clinical signs. Liver and kidney samples were evaluated by PCR in this case and, though the negative results suggested that the dog was not infected with Leptospira spp., postmortem PCRs have limitations similar to those for antemortem PCRs ( 2 ). Because the dog in this case had received several days of antimicrobial therapy before the postmortem PCRs were conducted, a false negative result was more likely than if the samples had been taken before treatment.

Immunohistochemistry for Leptospira spp. is also prone to false negative results in dogs, with 1 study finding 40% of acute leptospirosis cases tested negative on immunohistochemistry ( 5 ). False negative immunohistochemistry results may be associated with low numbers of bacteria in the kidneys and liver, especially in acute infections ( 5 ).

With several negative results for Leptospira spp. using multiple diagnostic tests, it must be considered that, despite the clinical signs and results from serum biochemistry, CBC, urinalysis, diagnostic imaging, and histopathology all being supportive of leptospirosis, there may have been another disease affecting the dog in this case. The histopathologic results were not supportive of pyelonephritis or cholangiohepatitis and did not demonstrate evidence of neoplasia, leaving toxicosis as the top non-leptospirosis differential diagnosis. If not for financial limitations, the next step would have been to perform a general toxin screen using fresh kidney and liver samples. Although there are a limited number of toxins that could cause this presentation, one possibility is cyanobacteria (blue-green algae) intoxication. Cyanobacteria, found in water sources such as lakes and ponds, contain hepatotoxins that can cause clinical signs such as vomiting, lethargy, icterus, and anuria, as well as elevated liver and kidney values on serum biochemistry and hepatocellular and renal tubular necrosis on histopathology ( 6 ). However, some findings in this case, such as thrombocytopenia, neutrophilia, and respiratory distress, were consistent with leptospirosis but not cyanobacteria intoxication ( 6 ) In addition, this dog had no known history of interacting with any bodies of water where cyanobacteria intoxication may have occurred.

Although leptospirosis presentation may vary among dogs, veterinarians around the world must be able to recognize the signs of acute renal and hepatic disease associated with Leptospira spp. infection. Due to the limitations of each type of diagnostic test, a combination of blood/urine PCR and serologic testing, preferably paired MATs, should be used to reduce the risk of inaccurate results. Even with multiple diagnostic tests, leptospirosis may never be confirmed, as seen in the case presented here. It is important to consider other diseases, such as toxicosis, in these cases. However, leptospirosis should remain the top differential diagnosis until it can be definitively ruled out, as prompt, appropriate treatment will provide the dog with the greatest chance of survival.

Acknowledgments

The author thanks the team at Cheltenham Veterinary Centre for their teaching and support during the externship program. The author also thanks Dr. Amanda Mansz for contributing valuable knowledge and sharing the dog’s histopathology images. Last, thank you to Dr. Allison Collier for providing guidance and insight for this case report. CVJ

Use of this article is limited to a single copy for personal study. Anyone interested in obtaining reprints should contact the CVMA office ( gro.vmca-amvc@yargk ) for additional copies or permission to use this material elsewhere.

• DOI: 10.1016/j.hrtlng.2024.06.008
• Corpus ID: 270670451

Perioperative fluid balance and early acute kidney injury after lung transplantation.

• Yan Shen , Daishan Jiang , +7 authors Min Li
• Published in Heart & lung : the journal of… 21 June 2024
• Heart & lung : the journal of critical care

46 References

Influence of fluid therapy on kidney function in the early postoperative period after lung transplantation., incidence and perioperative risk factors of acute kidney injury among lung transplant recipients., acute kidney injury after lung transplantation: perioperative risk factors and outcome., acute kidney injury following adult lung transplantation, incidence of early acute kidney injury in lung transplant patients: a single-center experience., acute kidney injury after lung transplantation: a narrative review, acute kidney injury influences mortality in lung transplantation, risk factors and mortality of acute kidney injury within 1 month after lung transplantation, association between transient acute kidney injury and morbidity and mortality after lung transplantation: a retrospective cohort study., postoperative acute kidney injury in lung transplant recipients., related papers.

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Acute Kidney injury

Apr 05, 2019

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Prepared by: Dr. Abdulbari A. Mahdi FIBMS ( Ped . Nephrology). Acute Kidney injury. Acute Kidney Injury. Abrupt increase in the blood concentration of creatinine and nitrogenous waste products and by the inability to regulate fluid and electrolyte homeostasis appropriately.

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Prepared by: Dr. Abdulbari A. Mahdi FIBMS (Ped. Nephrology) Acute Kidney injury

Acute Kidney Injury Abrupt increase in the blood concentration of creatinine and nitrogenous waste products and by the inability to regulate fluid and electrolyte homeostasis appropriately

A Common, Serious Problem Present in 5% of all hospitalized patients, & up to 30% of ICU patients Incidence is increasing at an alarming rate Mortality rate >50% in dialyzed ICU patients 25% of ICU dialysis survivors progress to ESKD within 3 years

Terminology • More than 30 different definitions • Variety of quoted incidence rates, risk factors, and morbidity and mortality rates • Change in nomenclature of this condition to acute kidney injury (AKI), acknowledging that acute renal dysfunction occurs due to injurious endogenous or exogenous disease processes • Recently, a group of pediatric and adult nephrologists and intensivists founded the Acute Dialysis Quality Initiative and proposed a consensus definition called the RIFLE classification

In 2004, a consensus definition for AKI was proposed by the Acute Dialysis Quality Initiative: the RIFLE criteria - R = risk for renal dysfunction - I = injury to the kidney - F = failure of kidney function - L = loss of kidney function - E = end-stage renal disease

When the achieved designation results from urine output criteria a subscript “o” is added e.g. RIFLE-Fo • A subscript “c” is used to denote the presence of preexisting chronic kidney disease

Pediatric RIFLE criteria • The adult-derived RIFLE definition was modified, and then applied and validated in pediatric patients and renamed as the pediatric RIFLE (pRIFLE) criteria. • pRIFLE stratifies AKI from mild (RIFLE R, risk) to severe (RIFLE F, failure) based on changes in the SCR or estimated creatinine clearance (eCCl) • Estimated creatinine clearance (ml/min/1.73 m2) is calculated using the Schwartz formula: eCCl = k × height / SCR

pRIFLE R – eCCl decrease by 25% • OR urine output is < 0.5 ml/kg/hr for 8 hr

pRIFLE I – eCCl decrease by 50% OR urine output < 0.5 ml/kg/hr for 16 hr

pRIFLE F – eCCL decrease by 75% or eCCl < 35 ml/min/1.73 m2 OR urine output < 0.3 ml/kg/hr for 24 hr or anuric for 12 hr

pRIFLE L – persistent failure > 4 weeks

pRIFLE E – persistent failure > 3 months (ESRD)

Pediatric RIFLE criteria definition and classifications of AKI

Aetiologic Classification • Pre-renal • Renal (intrinsic) • Postrenal (obstructive)

Prerenal failure Decreased true intravascular volume • Dehydration • GIT losses • Salt-wasting renal or adrenal diseases. • Central or nephrogenic diabetes inipidus • Third space losses: sepsis trauma nephrotic syndrome Decreased effective intravascular volume • congestive heart failure • Pericarditis • cardiac tamponade • hepatorenal syndrome

Prerenal Azotemia Pathophysiology Pathophysiology Renal Autoregulation Renal Autoregulation myogenic reflex myogenic reflex glomerulotubular feedback glomerulotubular feedback angiotensin II angiotensin II Sodium and water reabsorption Sodium and water reabsorption aldosterone aldosterone vasopressin vasopressin

Mechanisms of Intrarenal Autoregulation Afferent Maintenance of RBF Arteriolar Resistance Reduced Myogenic Reflex Maintenance Renal and Tubuloglomerular Feedback of Perfusion GFR Pressure Angiotensin II Efferent Maintenance of Arteriolar GHP Resistance

Mechanisms of Sodium and Water Conservation in Prerenal Azotemia Decreased Renal Perfusion Renin Vasopressin Angiotensin II Aldosterone Renal Tubular Na Renal Tubular H2O Reabsorption Reabsorption Urine Volume Concentrated Urine Urine Sodium

Intrinsic ARF Intrinsic ARF may be due to the following broad Intrinsic ARF may be due to the following broad categories: categories: ischemic ischemic acute tubular necrosis nephrotoxic nephrotoxic - glomerular changes vascular / glomerular vascular / glomerular - minimal tubular involvement other other

Acute Tubular Necrosis Hypoxic / ischemic ATN • Prolonged prerenal injury OR severe hypoxic insults • Urinalysis → Casts + Epithelial cells Casts ± low grade proteinuria • Urinary indices: inability to conserve Na+ and water • Serum creatinine ↑↑ 0.5 – 2 mg/dl/day • U/S : Normal sized-kidneys with loss of C.M. differentiation • Prognosis ?? → CKD • Recovery + diuretic phase → attention to fluid and electrolyte balance

Acute Tubular Necrosis Nephrotoxic AKI • Antibiotics • Acyclovir, Cidofovir, Indinavir, Foscarnet, Pentamidine, Aminoglycosides and amphotericine B • Organic solvents • Ethylene glycol, Toluene • Poisons • Paraquat, Snake bites • Chemotherapeutic agents • Cisplatin, Ifosphamide • Anti-inflammatory and immunosuppressive agents • NSAIDs, Cyclosporin, Tacrolimus, IVIG, Radiocontrast agents

Acute Interstitial Nephritis • Reaction to drug OR idiopathic • Presentation: • Fever, Arthralgia, Rash, Uveitis, Eosinophilia,Pyuria • Pathogenesis: Hypersensitivity reaction with the development of antitubular basement membrane antibodies • U/S: large echogenic kidneys • Biopsy: Interstitial infiltrates with many eosinophils • Specific therapy → withdrawal of the drug and corticosteroid

Etiology of AIN

Hemolytic Uremic Syndrome • One of the most common causes of community-acquired AKI in young children • Triad of microangiopathic hemolytic anemia, thrombocytopenia, and renal insufficiency • HUS has clinical features in common with thrombotic thrombocytopenic purpura (TTP) which is also characterized by these features but can include central nervous system (CNS) involvement and fever and can have a more gradual onset • A low platelet count can usually, but not always, be detected early in the illness, but it can then become normal or even high. If a platelet count obtained within 7 days after onset of the acute gastrointestinal illness is not <150,000/mm3, other diagnoses should be considered

Terminology and Classification

Microangiophathic hemolytic anemia with fragmented erythrocytes (schistocytes)

Postrenal AKI • Obstructive cause • - Solitary kidney • - Ureters bilaterally • - Urethra • Congenital OR Acquired • Rx: promptly relieve the obstruction

Clinical Approach to AKI: Pre-, Intra-, and Post-Renal History Volume status Ultrasound Urinalysis US shows Hydronephrosis Urinalysis Normal Urinalysis Abnormal Post-Renal Pre-renal Tubulointerstial Disorders Glomerular and Vascular Disorders

Nephrologists Clinical Approach to AKI History Volume Status Ultrasound Urinalysis Normal Urinalysis Hydronephrosis Pre-Renal Post-Renal Vascular Disorders Abnormal urinalysis Low ECF Volume GI losses Hemorrhage Diuretics Osmotic diuresis Altered renal blood flow or hemodynamics Sepsis Heart failure Cirrhosis/Hepatorenal syndrome Hypercalcemia Medications NSAIDs/Cox-2 inhibitors ACE inhibitors Angiotensin II receptor blockers Vascular disease Prostate disease BPH Cancer Pelvic malignancy Stones Stricture Retroperitoneal fibrosis Arterial Renal artery stenosis Renal artery thromboembolism Fibromuscular dysplasia Takayasu arteritis Medium vessel Polyarteritis nodosa Kawasaki disease Small vessel Glomerulonephritis Thrombotic microangiopathies Cholesterol emboli Renal vein Renal vein thrombosis Abdominal compartment syndrome Renal parenchymal disorders Glomerular Disorders Tubulointerstitial Disorders Tubular obstruction Crystals Calcium oxalate (Ethylene glycol, orlistat) Indinivir Acyclovir Methotrexate Tumor lysis syndrome Myeloma cast nephropathy Acute tubular necrosis Ischemic Nephrotoxic Contrast-induced Rhabdomyolysis Acute interstitial nephritis Medication-induced Autoimmune Sjogren syndrome Sarcoidosis Infection-related

Treatment of AKI Aims of treatment: Maintenance of Fluid and Electrolyte Homeostasis Preventing Life-threatening Complications Avoiding Further Kidney Injury Providing Apprpriate Nutrition RRT in most severe forms of AKI

The treatment of AKI divided into: • nondialytic therapy (supportive therapy and medical management) • dialytic therapy . • The nondialytic therapy: • to date the only effective nondialytic treatment of AKI entails: • 1. Restoration of adequate renal blood flow • 2. Avoidance of nephrotoxic medications or those that interfere with renal compensatory mechanisms • 3. Assurance that renal perfusion has been maximized before exposure to nephrotoxic agents.

1- Vasoactive agents: a- dopamine : • . the use of “renal dose” dopamine(0.5-5 μg / kg / min) to improve renal perfusion after an ischemic insult has become very common in ICU(in the absence of hypertension). • . dopamine increases renal blood flow by promoting vasodilatation and may improve urine output by promoting natriuresis. b- ANP: an atrial natriuretic peptide, it increases the GFR by dilating afferent arterioles while constricting efferent arterioles and so improve GFR , urinary out put .

2- Diuretics therapy : • Stimulating urine output eases management of AKI, but the conversion of oliguric to nonoliguric AKI has not been shown to alter the course of the disorder. • Diuretics therapy have no value in patient with established anuria. • These agents act by altering tubular function but it should be recognized that the increase in urine flow does not represent an improvement in renal function nor does it affect the natural history of the disease that precipitated the AKI.

1. Mannitol(0.5-1 g/kg delivered over 30 minutes) may increase intratubular urine flow to limit tubular obstruction and may limit cell damage by preventing swelling or by acting as a scavenger of free radicals or reactive oxygen molecules. • S.E. of mannitol a. Lack of response to therapy can precipitate congestive heart failure, particularly if the child’s intravascular volume is expanded before mannitol b. Lack of excretion may result in hyperosmolarity. 2. Furosemide (Lasix) (1-5 mg / kg / dose) • . increases urine flow rate to decrease intratubular obstruction • . inhibits Na-K ATP ase, which limits oxygen consumption in already damaged tubules with a low oxygen supply . • S.E. of Furosemide is ototoxicity. Continuous in fusions may be more effective and may be associated with less toxicity than bolus administration.

3- Fluid Balance: • Depending on the cause of AKI and the presence or absence of associated symptoms such as vomiting or diarrhea, children with AKI may present with hypovolemia, euvolemia, or fluid over loadandpulmonary edema. • Patients with salt-wasting renal disease, diarrhea or vomiting may present with fluid deficits that need correction to a euvolemic state, whereas patients with oliguria or anuria more commonly present with hypervolemia and need fluid restriction and/or acute fluid removal to achieve a euvolemic state. • In some oliguric patients it may be imposible to distinguish whether oliguria is due to hypoperfusion (hypovolemia) or impending ATN . so evaluation of the urine may prove helpful in this regard

. in patient with hypovolemia • 1- urine is concentrated (urine osmolality >500mOsm / kg) because increase reabsorption of water • 2- urinary Na conc. < 20 m Eq / L because Na reabsorption increase • 3- Fractional excretion of sodium (F.E.Na) is usually <1% • 4- increase serum BUN to creatinine ratio due to increase tubular reabsorption of urea. • 5- Increase urine to plasma creatinine ratio because the creatinine is not reabsorbed.

by contrast in patient with ATN 1- Dilute urine is (osmolality<350mOsm / kg) 2- urine Na conc.>40 mEq / L 3- FE Na > 1% 4- Urine creatinine to plasma creatinine ratio dose not increase above 20:1 ratio. 5- The serum BUN to creatinine ratio does not increase

Assessment of the patient for fluid balance • . Weight, BP, heart rate, skin turgor and capillary refill are each used to assess the intravascular volume. • 1- in children who are intravascularlyvolume depleted, 10-20 ml / kg of normal saline can be infused to reestablish intravascular volume (dehydrated pt. generally void with in 2 hours) . • If U.O.P. does not increase and azotemia does not improve after fluid resuscitation, then catheterization of the bladeler and central venous pressure monitoring may be necessary to further guide fluid therapy. This achieved through the use of central venous catheter that positioned in the central venous area of the right heart is satisfactory guide to the speed of fluid administration; the CVP normally between 2 and 12 cm H2O. If clinical and laboratory evaluations show that the patient is adequately hydrated, then aggressive diuretic therapy may be considered.

2- for fluid overload, fluid restriction and/or fluid removal with dialysis or hemofiltration may be instituted if the child does not respond to diuretic therapy. • . when intravascular volume normalized, euvolemia can be maintained by providing the child with fluid to replace normal water losses from the skin, respiratory tract, and GIT (insensible losses, 400 ml / m2 / 24hr. + UOP) • . excess losses need to be accounted for as well and replaced with the appropriate fluid. • In general, glucose containing solutions (10-30%)with out electrolytes are used as maintance fluids . the composition of the fluid may be modified in accordance with the state of electrolyte balance. • . daily weight measurements, BP, accurate fluid input & output records, physical examination and nutritional needs of the child guide ongoing fluid therapy.

4-Electrolyte and Acid-Base Balance: • 1. Na+ Balance • . mild hyponatremia is very common in AKI due to hyponatremic dehydration but fluid overload with dillutionalhyponatremic is much more common. • . if the serum Na level is >120 m Eq / L , fluid restriction or removal by dialytic therapy corrects the serum Na. • . However, if the serum Na level is <120 m Eq / L , the child is at higher risk for seizures due to hyponatremia and correction to a Na level of approximately 125m Eq / L with hypertonic saline should be considered. • The amount of Na required can be calculated by the following formula:(125-PNa ) (wt. in kg) (0.6) = mEq Na • The required amount is usually infused over several hours to ovoid rapid correction of serum Na level . • Rapid correction of the serum Na conc. In adults with chronic hyponatermia has been associated with Neurologic injury, particularly central pontinemyelinolysisalthongh the incidence of such injury in children is unknoun .

2. K+ balance: • Common and potentially life threatening. • . kidney tightly regulates K+ balance and excretes approximately 90% of dietary K+ intake. • a. decrease filtration b. impaired tubular secretion. c. altered distribution of K+ by acidosis, which shifts potassium from the intracellular to the extracellular compartment d. release of intracellular K+ due to the associated catabolic state. • True hyperkalemia results in disturbances of cardiac rhythm by its depolarizing effect on the cardiac conduction pathways . • ECG: → Tall, peaked T waves are the first manifestation of cardiotoxicity, and prolongation of the PR interval, flattening of P waves & widening of QRS complexes are later abnormalities. Severe hyperkalemia leads to ventricular tachycardia and fibrillation. • . symptoms of hyperkalemia include malaise, nausea & progressive muscle weakness. • . Treatment of hyperkalemia is indicated if cardiac conduction abnormalities are noted or if the K+ levels are higher than 6 to 7 mEq/L.

Table : Treatment of Hyperkalemia

3. acidosis: • . as long as the Child’s CNS is intact, respiratory compensation provides partial correction of the acidosis. But if the child is obtunded, respiratory compensation may be compromised, which results in severe acidosis. • . severe acidosis (arterial pH <7.15, serum Hco3 <8 mEq / L “m.mol. / kg”) may increase myocardial irritability and requires treatment to raise the PH to 7.20 which approximates a serum Hco3 level to 12 mEq / L. • . severe acidosis can be treated with intravenous or oral NaHCO3, oral sodium citrate solutions, and/or dialysis . • . it is important to consider the serum total and ionized Ca level • . because of the risks involved in the rapid infusion of alkali, the acidosis should be corrected only partially by the IV route according to the correction formula : • mEqNaHCO3required =0.3×wt(kg)×(12-serum HCO3{mEq/L}) • . the remainder of the correction should be accomplished only after normalization of the serum Ca and phosphorus level may be made by oral administration of NaHCO3tablets or Na citrate solution.

4. Ca + phosphate Balance: • Hyperphosphatemia treated with dietary phosphorus restriction and with oral CaCo3 or other Ca compounds • Dialysis therapy also effectively removes phosphorus, but it cross the dialysis membranes less readily than uncharged molecules such urea or K+ • . The causes of hypocalcemia in AKI is multifactorial • a. hyperphosphatemia . • b. inadequate GI Ca absorption due to in adequate 1,25-dihydroxy vitamin D production by the kidney . • c. Skeletal resistance to the action of PTH • . If hypocalcemia is severe and/or if HCo3 therapy is necessary for hyperkalemia , treatment with 10% calcium gluconate (100mg/kg up to aminimum of 1g , or 1ml/kg up to a maximum of 10 ml) should be given over 30-60 minutes with continuous ECG monitoring . • . hypocalcemia may also be treated by oral administration of CaCo3 or other Ca salts.

5- Medications: • . when medications are prescribed in AKI, the mechanism of drug elimination and the metabolic pathway of the drug must be considered and adjustments made for renal impairment . • . many drug adjustment tables are based on the level of Renal function (GFR>50ml/min/1.73m2 ,GFR of 20-50ml/min/1.73m2 , or GFR<20ml/min/1.73m2) and it is important to estimate the Child’s level of RF appropriately and to consider the rate of increase in the serum creatinine level rather than the absolute creatinine level . • . To prevent further insults to the kidney it is best to avoid nephrotoxic drugs in ARF , if potentially nephrotoxic drugs are needed it is appropriate to use them while monitoring drug levels and potential adverse effects.

6- Hypertension: • . HT in AKI is commonly related to volume overload and/or to alterations in vascular tone. • . if HT is releated to volume overload → diuretic therapy if no response then dialysis or hemofiltration. • . antihypertensive drugs may also indicated depending on the degree of BP elevation & the cause of HT • . The choice of antihypertension therapy depends on • a. degree of BP elevation. • b. presence of CNS symptoms of HT • c. presence of associated conditions • d. the cause of AKI • . For the child who has sever HT and/or is encephalopathic IV therapy with Na nitroprusside (beginning dose 0.5-1μg/kg/min) is indicated with monitoring of the serum levels of thiocyanate, a metabolic product of nitroprusside that is excreted by the kidney . • Alternative therapies include IV labetalol (0.5-3.0 mg/kg/h) also diazoxide (1-5mg/kg/dose), enalaprilat (0.005-0.01mg/kg/day) and nicardipine (1-3μg/kg/min) . • . for less sever HT IV hydralazine or sublingual nifedipine can be used , sever hypotension and tissue ischemia after sublingual administration of Nifedipine, which has been observed in adult pts, is uncommon in pediatric patients . • . once the BP is controlled treatment with oral long-acting agents can be initiated.

7- Nutritional support • . AKI is associated with marked catabolism & malnutrition leading to delayed recovery from AKI • . if GIT is intact and functional, enteral feedings with formula (similac PM 60/40 for Newborns & infants) should be instituted . • . Dilute formula should be given initially and then feedings can be increase and concentrated to achieve optimal calories intake. • . in older children a diet of high-biologic-value protein, low-phosphorus& low-potassium foods can be used. • . infants should receive maintenance calories (120 Kcal/kg/day) and older children appropriate maintenance calories or higher if needed due to the catabolic state and malnutrition. • . if enteral feeding are not possible, then hyperalimentation, usually through a central line, with high concentration of dextrose (25%), lipids (10-20%), and protein (1-2g/kg/day) should be instituted . • . if the child is oliguric or anuric and sufficient caloric intake cannot be achieved while appropriate fluid balance is maintained, dialysis should be initiated earlier than in the usual case.

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Acute Kidney Injury Adding Insult to Injury Thursday 11 th June 2009 RSM London Dr Kevin Harris Clinical Vice President. Acute Kidney Injury.

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Acute Kidney Injury. Chapter 47. Acute Kidney Injury Etiology and Pathophysiology. Prerenal Causes are factors external to the kidneys that reduce renal blood flow Severe dehydration, heart failure, ↓ CO Decreases glomerular filtration rate Causes oliguria

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