Definition Of Acute Kidney Injury Research Articles

Reflections on the KDIGO Definition of Acute Kidney Injury and Its Integration in the Concept of Acute Diseases and Disorders and Chronic Kidney Diseases

Acute kidney injury (AKI) describes a heterogeneous group of conditions, without specification of their etiology and diagnosed only by indirect markers of glomerular filtration rate (GFR), such as serum creatinine and urine output. Bedside estimation of GFR and detection of structural alterations with novel biomarkers, and stress tests have more recently been developed. These novel findings should probably be included in future AKI definitions. Chronic kidney disease (CKD) is defined by abnormalities in kidney function and structure that persist over >3 months and is classified according to cause, GFR, and albuminuria. Acute kidney disease (AKD) is the term representing patients with abnormalities of function and structure with a duration of ≤3 months that fall outside the definitions of AKI or CKD. Since AKI is by definition also AKD, 2 types of AKD have been proposed, one with and one without AKI. AKD without AKI is common, often undetected, occurs frequently in the outpatient population and shows increased risk of CKD, ESKD and mortality. Alternatively, AKD has also been defined as the period of incomplete recovery following an AKI episode, the latter limited for the duration of 7 days. This contribution discusses the pros and cons of the existence of these 2 definitions of AKD.

POS-880 ACUTE KIDNEY INJURY IN PATIENTS WITH COVID-19 USING AN EXTENDED KDIGO DEFINITION: RESULTS FROM THE ISARIC PROSPECTIVE, MULTINATIONAL, MULTICENTRE, OBSERVATIONAL STUDY

Acute kidney injury (AKI) has been identified as one of most common and significant problems in hospitalised patients with COVID-19 leading to increased morbidity and mortality. Little is yet known about the incidence and impact of AKI occurring in the community or early in the hospital admission in this population. An extended KDIGO (eKDIGO) definition of AKI that incorporates a decrease in the serum creatinine (sCr) has been used in previous studies to improve detection of these cases, particularly in low-income country settings.

Short- and long-term outcomes of intensive care patients with acute kidney disease.

SummaryBackgroundAcute kidney disease (AKD) is a proposed definition for acute kidney injury (AKI) lasting 7 days or longer. Little has been reported regarding characteristics of patients with AKD and their short- and long-term outcomes. We describe the epidemiology and risk factors for AKD and outcomes following AKD.MethodsThis retrospective observational cohort study identified patients aged 16 or older admitted to the Glasgow Royal Infirmary and Queen Elizabeth University Hospital intensive care units (ICUs) in Scotland between 1st July 2015 and 30th June 2018. Baseline serum creatinine and subsequent values were used to identify patients with de-novo kidney injury (DNKI). Patients with recovery prior to day 7 were classified as AKI; recovery at day 7 or beyond was classified as AKD. Outcomes were in-hospital and long-term mortality, and proportion of major adverse kidney events (MAKEs). Multivariable logistic regression was used to identify risk factors for AKD. A Cox proportional hazards model was used to identify factors associated with long-term outcomes.FindingsOf the 5,334 patients admitted to ICU who were assessed for DNKI, 1,620 (30·4%) suffered DNKI and of these, 403 (24·9%) met AKD criteria; 984 (60·7%) were male and the median age was 60·0 (IQR=48·0–72·0). Male sex, sepsis and lower baseline estimated glomerular filtration rate (eGFR) were associated with development of AKD. In-ICU (16·1%vs6·2%) and in-hospital (26·1%vs11·6%) mortality rates were significantly higher in AKD patients than AKI patients. Long-term survival was not different for AKD patients (HR=1·16; p-value=0·261) but AKD was associated with subsequent MAKEs (OR=1·25).InterpretationOne in four ICU patients with DNKI met AKD criteria. These patients had an increased risk of short-term mortality and long-term MAKEs. Whilst the trend for long-term survival was lower, this was not significantly different from shorter-term AKI patients. Patients with AKD during their ICU stay should be identified to initiate interventions to reduce risk of future MAKEs.FundingNo funding was associated with this study.

Incidence, risk and risk factors for acute kidney injury associated with the use of intravenous indomethacin in neonatal patent ductus arteriosus: A 16-year retrospective cohort study.

Background:Intravenous indomethacin has been used in infants for many years as the pharmacological closure of ductus arteriosus, but the incidence, risk, and risk factors of acute kidney injury (AKI) among infants treated with indomethacin, were still scarce.Objectives:To determine the incidence, risk, and risk factors of AKI among infants treated with indomethacin (exposed group) for patent ductus arteriosus (PDA) closure compared with the matched non-exposed infants.Methods:A matched retrospective cohort study of infants admitted to the neonatal intensive care unit of Songklanagarind Hospital from January 2003 to December 2018 was performed. All data were collected from computerized medical records. A non-exposed infant was matched (1:1) by gestational age and birth weight to each exposed infant. AKI, the outcome of interest, was diagnosed according to neonatal AKI definitions. The incidence (95% CI) of AKI was estimated for each group. Conditional logistic regression was used to estimate the odds ratio (OR) of developing AKI among those who received indomethacin compared with those who did not, adjusted for potential confounders (concomitantly used nephrotoxic potential medications including aminoglycosides, amphotericin B, vancomycin, furosemide, systemic corticosteroids, and systemic vasopressors and inotropes). Kaplan-Meier estimate was performed to examine probability of recovery from AKI after AKI events.Results:The matching resulted in 193 pairs of exposed and non-exposed infants. The incidences [95% CI] of AKI in the exposed and the non-exposed group, were 33.7% [27.0%:40.4%] and 15.5% [10.4%:20.7%], respectively. Indomethacin statistically increased the risk for developing AKI, crude OR 2.94[95%CI 1.77:4.90], McNemar’s chi square p<0.001, and adjusted OR 2.73 [95%CI 1.55:4.80], p=0.001. The risk of AKI associated with potentially nephrotoxic medications were inconclusive. Time to recovery from AKI was relatively rapid, median recovery time was 3 days in both groups and all infants who developed AKI recovered within 6 days.Conclusions:The incidence of AKI among infants treated with indomethacin for PDA closure were doubled that in the indomethacin-nonexposed infants. Indomethacin significantly increased the risk of AKI, while the risk associated with other concomitant nephrotoxic medications were inconclusive. Transient nephrotoxicity associated with indomethacin should be balanced with the risk associated with delayed PDA closure. All infants receiving indomethacin should be routinely monitored for serum creatinine and/or urine output, throughout the treatment and one to two weeks after treatment cessation. Alternatives with better renal safety profiles should be considered in the population with higher risk of AKI.

Biomarkers of acute kidney injury after pediatric cardiac surgery: a meta-analysis of diagnostic test accuracy.

A variety of biomarkers have been proposed as predictors of cardiac surgery-associated AKI in children, of which uNGAL was the most prominent with excellent diagnostic qualities. However, more consolidatory evidence will be required before these novel biomarkers may eventually help realize precision medicine in AKI management. • Acute kidney injury (AKI) occurs in about 30-60% of children undergoing cardiac surgery and is associated with increased in-hospital mortality and adverse short-term outcomes.However, in current clinical practice, AKI definitions and detection often rely on changes in serum creatinine and urine output, which are late and insensitive markers of kidney injury. • Although various novel biomarkers have been studied for the diagnosis of AKI in children after cardiac surgery, it remains unclear how these compare to one another in terms of diagnostic accuracy. • Pooled analyses suggest that for the diagnosis of AKI in children who underwent cardiac surgery, NGAL is the most accurate among the most frequently studied biomarkers. • A number of other promising biomarkers have been reported, although they will require further research into their diagnostic accuracy and clinical applicability.

Prevalence and mortality of transient acute kidney injury within 48h, as new subtype, following coronary angiography: a cohort study.

The association of transient acute kidney injury (AKI) with mortality was controversial. Our study aims to investigate the prevalence and impact of transient AKI on mortality in patients following coronary angiography (CAG). Our study retrospectively enrolled 3970 patients with pre-operative serum creatinine (Scr) and twice measurements within 48h after procedure. Transient AKI defined as the diagnosis of AKI (Scr > 0.3mg/dL or > 50% from the baseline level) on day 1 when Scr failed to meet the criteria for AKI on the day 2. Maintained AKI was defined as AKI not meeting the definition for transient AKI. The primary outcome was 1-year all-cause mortality. Multivariable logistic regression was used to assess the association between transient AKI and 1-year mortality. Among 3,970 participants, 861 (21.7%) occurred AKI, of whom 128 (14.9%) was transient AKI and 733 (85.1%) was maintained AKI. 312 (7.9%) patients died within 1-year after admission. After multivariable analysis, transient AKI was not associated with higher 1-year mortality [adjusted odds ratio (aOR), 1.37; CI 0.68-2.51] compared without AKI. Among AKI patients, transient AKI was associated with a 52% lower 1-year mortality compared with maintained AKI. Additionally, maintained AKI was significantly associated with higher 1-year mortality (aOR, 2.67; CI 2.05-3.47). Our data suggested that transient AKI within 48h was a common subtype of AKI following CAG, without increasing mortality. More attention needs to be paid to the patients suffering from maintained AKI following CAG.

A Comparison of AKIN, KDIGO, and RIFLE Definitions to Diagnose Acute Kidney Injury and Predict the Outcomes after Cardiac Surgery in a South Asian Cohort

Background: Acute kidney injury (AKI) after cardiac surgery is associated with an increased mortality and morbidity. Different definitions for AKI have been used such as Acute Kidney Injury Network (AKIN), Kidney Disease: Improving Global Outcomes (KDIGO), or risk, injury, failure, loss, end-stage kidney disease (RIFLE). Each of these definitions has their own benefits and limitations for predicting the degree of AKI and adverse outcomes following cardiac surgery. This study was aimed to compare the three AKI definitions to diagnose AKI and their predictive ability for mortality and morbidity after isolated coronary artery bypass surgery (CABG) in a South Asian cohort. Material and Methods: A single-center retrospective review was conducted on 1,508 patients having undergone isolated CABG surgery from January 2015 to January 2019. AKI was assessed on three definitions, and comparative receiver operating characteristics curves were built against the outcomes to assess discriminative power of each. Results: Mean age of participants was 59.43 (±1.12) years, predominantly males (82.6%). Patients with AKI were elder, more likely to be diabetic and hypertensive. AKI by any definition occurred in 58.7% (885/1,508) patients. Frequency of AKI was 508 (33.7%), 517 (34.4%), and 871 (57.8%) on AKIN, KDIGO, and RIFLE criteria, respectively. The proportion of patients with RIFLE-risk 619 (41%) was greater compared with AKIN stage 1 (342 [22.7%]) and KDIGO stage 1 (330 [21.9%]), while for stages 2 and 3 the proportions were comparable across the three systems. Area under the curve (AUC) for 30-day mortality for AKIN was (0.786, [95% CI: 0.764–0.806]), KDIGO: (0.796, [95% CI: 0.775–0.816]) and for RIFLE (0.844, [95% CI: 0.825–0.862]). AUC for overall morbidity was in undesirable ranges (i.e., >0.5–≤0.7) for all three definitions. Conclusion: In a South Asian cohort, performance of AKIN and KDIGO criteria was comparable to diagnose AKI, while RIFLE definition, though overestimated the incidence of AKI particularly stage 1, and had an excellent discriminatory power to predict mortality compared to other two definitions.

Effect of a Perioperative Hypotension-Avoidance Strategy Versus a Hypertension-Avoidance Strategy on the Risk of Acute Kidney Injury: A Clinical Research Protocol for a Substudy of the POISE-3 Randomized Clinical Trial.

Background:Most patients who take antihypertensive medications continue taking them on the morning of surgery and during the perioperative period. However, growing evidence suggests this practice may contribute to perioperative hypotension and a higher risk of complications. This protocol describes an acute kidney injury substudy of the Perioperative Ischemic Evaluation-3 (POISE-3) trial, which is testing the effect of a perioperative hypotension-avoidance strategy versus a hypertension-avoidance strategy in patients undergoing noncardiac surgery.Objective:To conduct a substudy of POISE-3 to determine whether a perioperative hypotension-avoidance strategy reduces the risk of acute kidney injury compared with a hypertension-avoidance strategy.Design:Randomized clinical trial with 1:1 randomization to the intervention (a perioperative hypotension-avoidance strategy) or control (a hypertension-avoidance strategy).Intervention:If the presurgery systolic blood pressure (SBP) is <130 mmHg, all antihypertensive medications are withheld on the morning of surgery. If the SBP is ≥130 mmHg, some medications (but not angiotensin receptor blockers [ACEIs], angiotensin receptor blockers [ARBs], or renin inhibitors) may be continued in a stepwise manner. During surgery, the patients’ mean arterial pressure (MAP) is maintained at ≥80 mmHg. During the first 48 hours after surgery, some antihypertensive medications (but not ACEIs, ARBs, or renin inhibitors) may be restarted in a stepwise manner if the SBP is ≥130 mmHg.Control:Patients receive their usual antihypertensive medications before and after surgery. The patients’ MAP is maintained at ≥60 mmHg from anesthetic induction until the end of surgery.Setting:Recruitment from 108 centers in 22 countries from 2018 to 2021.Patients:Patients (~6800) aged ≥45 years having noncardiac surgery who have or are at risk of atherosclerotic disease and who routinely take antihypertensive medications.Measurements:The primary outcome of the substudy is postoperative acute kidney injury, defined as an increase in serum creatinine concentration of either ≥26.5 μmol/L (≥0.3 mg/dL) within 48 hours of randomization or ≥50% within 7 days of randomization.Methods:The primary analysis (intention-to-treat) will examine the relative risk and 95% confidence interval of acute kidney injury in the intervention versus control group. We will repeat the primary analysis using alternative definitions of acute kidney injury and examine effect modification by preexisting chronic kidney disease, defined as a prerandomization estimated glomerular filtration rate <60 mL/min/1.73 m2.Results:Substudy results will be analyzed in 2022.Limitations:It is not possible to mask patients or providers to the intervention; however, objective measures will be used to assess acute kidney injury.Conclusions:This substudy will provide generalizable estimates of the effect of a perioperative hypotension-avoidance strategy on the risk of acute kidney injury.

Comparison Of Two Definitions (P-Rifle And Kdigo) For Prevalence Of Acute Kidney Injury And In Hospital Mortality In A Paediatric Intensive Care Unit Of Pakistan.

To compare the Paediatric RIFLE (p-RIFLE) and Kidney Disease Improving Global Outcomes (KDIGO) definitions of acute kidney injury (AKI) for frequency of (AKI) and in-hospital mortality in critically ill children. Retrospective review of medical records of all patients (aged 1 month - 16 years) admitted in Paediatric Intensive Care Unit from January 2015-December 2016, with length of stay >48 hours, was done. Patients with chronic kidney disease were excluded. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the p-RIFLE and KDIGO criteria to predict the AKI related mortality. Logistic regression analysis was done to determine the association of different variables with mortality in AKI patient based on p-RIFLE, KDIGO. A p-value of <0.05 was considered significant. Out of total 823 patients admitted during the study period, 562 patients were included in the study. Median age was 2 years (Interquartile range 8 years). Acute kidney injury frequency according to p-RIFLE and KDIGO were 391 (70%), and 372 (66%) respectively. Overall, 106/823 (12.8%) children died during study period, 78 (19.9%) in AKI by p-RIFLE and 76 (20.4%) in AKI by KDIGO died. The area-under- curve for in-hospital mortality for p-RIFLE and KDIGO criteria were 0.525 (p=0.427), and 0.534 (p=0.276), respectively. P-RIFLE is more sensitive compared to KDIGO in diagnosing AKI in critically ill children; identifying a greater number of moderate staged AKI cases. Greater AKI severity is associated with higher mortality in critically ill children.

Machine learning approach to predict acute kidney injury after liver surgery.

BACKGROUNDAcute kidney injury (AKI) after surgery appears to increase the risk of death in patients with liver cancer. In recent years, machine learning algorithms have been shown to offer higher discriminative efficiency than classical statistical analysis.AIMTo develop prediction models for AKI after liver cancer resection using machine learning techniques.METHODSWe screened a total of 2450 patients who had undergone primary hepatocellular carcinoma resection at Changzheng Hospital, Shanghai City, China, from January 1, 2015 to August 31, 2020. The AKI definition used was consistent with the Kidney Disease: Improving Global Outcomes. We included in our analysis preoperative data such as demographic characteristics, laboratory findings, comorbidities, and medication, as well as perioperative data such as duration of surgery. Computerized algorithms used for model development included logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGboost), and decision tree (DT). Feature importance was also ranked according to its contribution to model development.RESULTSAKI events occurred in 296 patients (12.1%) within 7 d after surgery. Among the original models based on machine learning techniques, the RF algorithm had optimal discrimination with an area under the curve value of 0.92, compared to 0.87 for XGBoost, 0.90 for DT, 0.90 for SVM, and 0.85 for LR. The RF algorithm also had the highest concordance-index (0.86) and the lowest Brier score (0.076). The variable that contributed the most in the RF algorithm was age, followed by cholesterol, and surgery time.CONCLUSIONMachine learning algorithms are highly effective in discriminating patients at high risk of developing AKI. The successful application of machine learning models may help guide clinical decisions and help improve the long-term prognosis of patients.

Insuffisance rénale aiguë en soins intensifs-réanimation et ses conséquences : mise au point

Acute kidney injury is a common complication in intensive care unit. Its incidence is variable according to the studies. It is considered to occur in more than 50 % of patients. Acute kidney injury is responsible for an increase in morbidity (length of hospitalization, renal replacement therapy) but also for excess mortality. The commonly accepted definition of acute kidney injury comes from the collaborative workgroup named Kidney Disease: Improving Global Outcomes (KDIGO). It made it possible to standardize practices and raise awareness among practitioners about monitoring plasma creatinine and also diuresis. Acute kidney injury in intensive care unit is a systemic disease including circulatory, endothelial, epithelial and cellular function involvement and an acute kidney injury is not accompanied by ad integrum repair. After prolonged injury, inadequate repair begins with a fibrotic process. Several mechanisms are involved (cell cycle arrest, epithelial-mesenchymal transition, mitochondrial dysfunction) and result in improper repair. A continuum exists between acute kidney disease and chronic kidney disease, characterized by different renal recovery phenotypes. Thus, preventive measures to prevent the occurrence of kidney damage play a major role in management. The nephrologist must be involved at every stage, from the prevention of the first acute kidney injury (upon arrival in intensive care unit) to long-term follow-up and the care of a chronic kidney disease.

Does Artificial Intelligence Make Clinical Decision Better? A Review of Artificial Intelligence and Machine Learning in Acute Kidney Injury Prediction.

Acute kidney injury (AKI) is a common complication of hospitalization that greatly and negatively affects the short-term and long-term outcomes of patients. Current guidelines use serum creatinine level and urine output rate for defining AKI and as the staging criteria of AKI. However, because they are not sensitive or specific markers of AKI, clinicians find it difficult to predict the occurrence of AKI and prescribe timely treatment. Advances in computing technology have led to the recent use of machine learning and artificial intelligence in AKI prediction, recent research reported that by using electronic health records (EHR) the AKI prediction via machine-learning models can reach AUROC over 0.80, in some studies even reach 0.93. Our review begins with the background and history of the definition of AKI, and the evolution of AKI risk factors and prediction models is also appraised. Then, we summarize the current evidence regarding the application of e-alert systems and machine-learning models in AKI prediction.

Acute kidney injury definition following PCI and cardiovascular outcomes

Abstract Background Acute kidney injury (AKI) is a complication of percutaneous coronary intervention (PCI), known to increase rates of adverse medical events. We aimed to identify the optimal definition of AKI in predicting of adverse cardiovascular outcomes and mortality post PCI. Methods From a large registry of patients undergoing PCI between 2006–2018 (n=25,690) at two hospitals, consecutive patients were assessed for the presence of AKI according to four different definitions: a relative elevation of ≥25% or ≥50%; or an absolute elevation of ≥0.3 mg/dL or ≥0.5 mg/dL in serum creatinine at 48 hours post PCI. We assessed the calculated rates of AKI according to the different definitions. The discriminant capacity for 30-day and 1-year mortality and MACE (MACE: all-cause death, myocardial infarction, target-vessel revascularization and coronary artery bypass graft surgery) of each definition was calculated using ROC curves and AUCs. Results Data of 15,153 patients was available for final analysis. Rates of AKI were 12.1%, 3.2%, 8.1% and 3.9% according to the four definitions, respectively. The discriminant capacity of adverse outcomes was highest among those defined as AKI according to the third definition - an absolute elevation of ≥0.3 mg/dL in serum creatinine with an AUC of 0.82 (95% CI 0.80–0.84) for 30-day mortality (P value = 0.036) and an AUC of 0.78 (CI 0.76–0.79) for 30 days MACE. Conclusions An absolute elevation of ≥0.3 mg/dL in serum creatinine 48 hours post PCI predicts overall mortality and MACE most accurately. Funding Acknowledgement Type of funding sources: None.

Kinetic changes in serum procalcitonin predict persistent acute kidney injury in critical patients.

Persistent acute kidney injury (AKI) has been shown to be closely associated with poor prognosis in critical patients. Recent studies have shown that procalcitonin (PCT) is valuable for the early prediction of AKI in critically patients. Our aim was to determine whether PCT and its kinetic changes could predict the occurrence of persistent AKI in critical patients. This is a prospective observational study. The definition of AKI was based on the Kidney Disease: Improving Global Outcomes criteria. Persistent AKI was defined as renal function that does not return to baseline serum creatinine levels within 48 h. Blood samples were obtained at the onset of AKI and two subsequent days of hospital stay. 24-h PCT change (ΔPCT-24 h) was defined as 24 h PCT minus baseline PCT (day 0). A total of 91 critical patients with AKI were included in this study. The persistent AKI group had a stepwise increase in PCT concentration. ΔPCT-24 h was higher in the persistent AKI group (p < .01). Logistic regression analysis showed that ΔPCT-24 h (p=.04) was independent predictors of persistent AKI. The receiver operating characteristic curves showed that area under the curve of ΔPCT-24 h was 0.84 (p < .01), and the cut-off value for PCT to predict persistent AKI was 0.56 ng/ml. Our study showed that the observation of kinetic changes in PCT is more significant for the early prediction of persistent AKI than the index of PCT at a single time point. ΔPCT-24 h is a good predictor of persistent AKI in critical patients.

Association Between Urine Output and Mortality in Critically Ill Patients: A Machine Learning Approach.

Current definitions of acute kidney injury use a urine output threshold of less than 0.5 mL/kg/hr, which have not been validated in the modern era. We aimed to determine the prognostic importance of urine output within the first 24 hours of admission to the ICU and to evaluate for variance between different admission diagnoses. Retrospective cohort study. One-hundred eighty-three ICUs throughout Australia and New Zealand from 2006 to 2016. Patients greater than or equal to 16 years old who were admitted with curative intent who did not regularly receive dialysis. ICU readmissions during the same hospital admission and patients transferred from an external ICU were excluded. One hundred and sixty-one thousand nine hundred forty patients were included with a mean urine output of 1.05 mL/kg/hr and an overall in-hospital mortality of 7.8%. A urine output less than 0.47 mL/kg/hr was associated with increased unadjusted in-hospital mortality, which varied with admission diagnosis. A machine learning model (extreme gradient boosting) was trained to predict in-hospital mortality and examine interactions between urine output and survival. Low urine output was most strongly associated with mortality in postoperative cardiovascular patients, nonoperative gastrointestinal admissions, nonoperative renal/genitourinary admissions, and patients with sepsis. Consistent with current definitions of acute kidney injury, a urine output threshold of less than 0.5 mL/kg/hr is modestly predictive of mortality in patients admitted to the ICU. The relative importance of urine output for predicting survival varies with admission diagnosis.

Mortality and predictors of acute kidney injury in adults: a hospital-based prospective observational study

Acute kidney injury (AKI) is a major global public health problem. It is expensive to manage and associated with a high rate of prolonged hospitalization and in-hospital mortality. Little is known about the burden of acute kidney injury in moderate to low-income countries. We aim to assess predictors of in-hospital mortality among AKI patients admitted to the medical ward. We prospectively identified patients meeting kidney disease improving global outcomes (KIDGO) AKI definitions from April to August 2019. Patients with underlying CKD and patients hospitalized for less than 48 h were excluded. The Cox regression model was fitted to identify predictors of mortality and statistical significance was considered at the p-value of less than 0.05. A total of 203 patients were enrolled over 5 months. Out of this, 121(59.6%) were males, 58(28.6%) were aged greater than 60 years, and 141(69.5%) had community-acquired acute kidney injury. The most common causes of AKI were Hypovolemia 99(48.77%), Glomerulonephritis 51(25.11%), and sepsis 32(15.79%). The overall in-hospital mortality rate was 12.8%. Stage 3 AKI (AHR = 9.61, 95% CI 1.17–28.52, p = 0.035), duration of AKI (AHR = 7.04, 95% CI 1.37–36.08, p = 0.019), length of hospital stay (AHR = 0.19, 95% CI 0.05–0.73, p = 0.012), and hyperkalemia (AHR = 3.61, 95% CI 1.12–11.71, p = 0.032) were significantly associated with in-hospital mortality. There is a high rate of acute kidney injury-related in-hospital mortality in adult patients admitted to the medical ward. The severity of AKI, hyperkalemia duration of AKI, and a short length of hospital stay were predictors of 30-days in-hospital mortality. Most of the causes of AKI are preventable and patients may benefit from early identification and treatment of these reversible causes.

The Definition of “Acute Kidney Injury” Following Percutaneous Coronary Intervention and Cardiovascular Outcomes

Acute kidney injury (AKI) is a complication of percutaneous coronary intervention (PCI), known to increase rates of adverse medical events. We aimed to identify the optimal definition of AKI in predicting adverse cardiovascular outcomes and mortality post PCI. From a large registry of patients undergoing PCI between 2006-2018 (n = 25,690) at our medical center, consecutive patients were assessed for the presence of AKI according to four different definitions: a relative elevation of ≥25% or ≥50%; or an absolute elevation of ≥0.3 mg/dL or ≥0.5 mg/dL in serum creatinine at 48 hours post PCI. We assessed the calculated rates of AKI according to the different definitions. The discriminant capacity for 30-day and 1-year mortality and MACE (MACE: all-cause death, myocardial infarction, target-vessel revascularization and coronary artery bypass graft surgery) of each definition was calculated using ROC curves and AUCs. Data of 15,153 patients was available for the final analysis. Rates of AKI were 12.1%, 3.2%, 8.1% and 3.9% according to the four definitions, respectively. The discriminant capacity of adverse outcomes was highest among those defined as AKI according to the third definition - an absolute elevation of ≥0.3 mg/dL in serum creatinine with an AUC of 0.82 (95% CI 0.80-0.84) for 30-day mortality (P value = 0.036) and an AUC of 0.78 (CI 0.76-0.79) for 30-day MACE. In conclusion, an absolute elevation of ≥ 0.3 mg/dL in serum creatinine 48 hours post PCI predicts overall mortality and MACE most accurately.

Developing an AKI Consensus Definition for Database Research: Findings From a Scoping Review and Expert Opinion Using a Delphi Process

The KDIGO (Kidney Disease: Improving Global Outcomes) definition of acute kidney injury (AKI) is frequently used in studies to examine the epidemiology of AKI. This definition is variably interpreted and applied to routinely collected health care data. The aim of this study was to examine this variation and to achieve consensus in how AKI should be defined for research using routinely collected health care data. Scoping review via searching Medline and EMBASE for studies using health care data to examine AKI by using the KDIGO creatinine-based definition. An international panel of experts formed to participate in a modified Delphi process to attempt to generate consensus about how AKI should be defined when using routinely collected laboratory data. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) extension for scoping reviews was followed. For the Delphi process, 2 rounds of questions were distributed via internet-based questionnaires to all participants with a prespecified cutoff of 75% agreement used to define consensus. The scoping review found 174 studies that met the inclusion criteria. The KDIGO definition was inconsistently applied, and the methods for application were poorly described. We found 58 (33%) of papers did not provide a definition of how the baseline creatinine value was determined, and only 34 (20%) defined recovery of kidney function. Of 55 invitees to the Delphi process, 35 respondents participated in round 1, and 25 participated in round 2. Some consensus was achieved in areas related to how to define the baseline creatinine value, which patients should be excluded from analysis of routinely collected laboratory data, and how persistent chronic kidney disease or nonrecovery of AKI should be defined. The Delphi panel members predominantly came from the United Kingdom, the United States, and Canada, and there were low response rates for some questions in round1. The current methods for defining AKI using routinely collected data are inconsistent and poorly described in the available literature. Experts could not achieve consensus for many aspects of defining AKI and describing its sequelae. The KDIGO guidelines should be extended to include a standardized definition for how AKI should be defined when using routinely collected data.

Acute kidney injury and hepatorenal syndrome in cirrhosis.

Acute kidney injury (AKI) in cirrhosis, including hepatorenal syndrome (HRS), is a common and serious complication in cirrhotic patients, leading to significant morbidity and mortality. AKI is separated into two categories, non-HRS AKI and HRS-AKI. The most recent definition and diagnostic criteria of AKI in cirrhosis and HRS have helped diagnose and prognosticate the disease. The pathophysiology behind non-HRS-AKI and HRS is more complicated than once theorized and involves more processes than just splanchnic vasodilation. The common biomarkers clinicians use to assess kidney injury have significant limitations in cirrhosis patients; novel biomarkers being studied have shown promise but require further studies in clinical settings and animal models. The overall management of non-HRS AKI and HRS-AKI requires a systematic approach. Although pharmacological treatments have shown mortality benefit, the ideal HRS treatment option is liver transplantation with or without simultaneous kidney transplantation. Further research is required to optimize pharmacologic and nonpharmacologic approaches to treatment. This article reviews the current guidelines and recommendations of AKI in cirrhosis.

Advances in management of hepatorenal syndrome.

Hepatorenal syndrome (HRS) is encountered frequently in patients with end-stage liver disease and remains an important cause of morbidity and mortality in this patient population. This review will focus and provide updates on pathophysiology, assessment of kidney function, new definitions, and treatment and prevention of HRS. Pathophysiology of HRS has been elucidated more recently and in addition to hemodynamic changes, the role of systemic inflammatory response contributes significantly to this process. Assessment of kidney function in patients with liver cirrhosis remains challenging. Novel glomerular filtration rate equations have been developed in patients with liver disease to better estimate kidney function and changes made in the definition of acute kidney injury (AKI), which are more aligned with KDIGO criteria for AKI. Vasoconstrictors, especially terlipressin, along with albumin remain the mainstay of pharmacological treatment of HRS-AKI. Biomarkers have been useful in differentiating ATN from HRS at an early stage. HRS remains a significant cause of morbidity and mortality for patients with end-stage liver disease. Newer understanding of mechanisms in development and pathophysiology of HRS have helped with elucidation of the disease process.