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

Association between hyperglycemia at ICU admission and postoperative acute kidney injury in patients undergoing cardiac surgery: Analysis of the MIMIC-IV database

Background

This study aimed to explore the correlation between hyperglycemia at intensive care unit (ICU) admission and the incidence of acute kidney injury (AKI) in patients after cardiac surgery.

Methods

We conducted a retrospective cohort study, in which clinical data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Adults (≥18 years) in the database who were admitted to the cardiovascular intensive care unit after cardiac surgery were enrolled. The primary outcome was the incidence of AKI within 7 days following ICU admission. Secondary outcomes included ICU mortality, hospital mortality, ICU length of stay, and the 28-day and 90-day mortality. Multivariable Cox regression analysis was used to assess the association between ICU-admission hyperglycemia and AKI incidence within 7 days of ICU admission. Different adjustment strategies were used to adjust for potential confounders. Patients were divided into three groups according to their highest blood glucose levels recorded within 24 h of ICU admission: no hyperglycemia (<140 mg/dL), mild hyperglycemia (140-200 mg/dL), and severe hyperglycemia (≥200 mg/dL).

Results

Of the 6905 included patients, 2201 (31.9%) were female, and the median (IQR) age was 68.2 (60.1-75.9) years. In all, 1836 (26.6%) patients had severe hyperglycemia. The incidence of AKI within 7 days of ICU admission, ICU mortality, and hospital mortality was significantly higher in patients with severe admission hyperglycemia than those with mild hyperglycemia or no hyperglycemia (80.3% vs. 73.6% and 61.2%, respectively; 2.8% vs. 0.9% and 1.9%, respectively; and 3.4% vs. 1.2% and 2.5%, respectively; all P <0.001). Severe hyperglycemia was a risk factor for 7-day AKI (Model 1: hazard ratio [HR]=1.4809, 95% confidence interval [CI]: 1.3126 to 1.6707; Model 2: HR=1.1639, 95% CI: 1.0176 to 1.3313; Model 3: HR=1.2014, 95% CI: 1.0490 to 1.3760; all P <0.050). Patients with normal glucose levels (glucose levels <140 mg/dL) had a higher 28-day mortality rate than those with severe hyperglycemia (glucose levels ≥200 mg/dL) (4.0% vs. 3.8%, P <0.001).

Conclusions

In post-cardiac surgery patients, severe hyperglycemia within 24 h of ICU admission increases the risk of 7-day AKI, ICU mortality, and hospital mortality. Clinicians should be extra cautious regarding AKI among patients with hyperglycemia at ICU admission after cardiac surgery.

Preoperative risk prediction models for acute kidney injury after noncardiac surgery: an independent external validation cohort study

BACKGROUND

Numerous models have been developed to predict acute kidney injury (AKI) after noncardiac surgery, yet there is a lack of independent validation and comparison among them.

METHODS

We conducted a systematic literature search to review published risk prediction models for AKI after noncardiac surgery. An independent external validation was performed using a retrospective surgical cohort at a large Chinese hospital from January 2019 to October 2022. The cohort included patients undergoing a wide range of noncardiac surgeries with perioperative creatinine measurements. Postoperative AKI was defined according to the Kidney Disease Improving Global Outcomes creatinine criteria. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUROC), calibration (calibration plot), and clinical utility (net benefit), before and after model recalibration through intercept and slope updates. A sensitivity analysis was conducted by including patients without postoperative creatinine measurements in the validation cohort and categorising them as non-AKI cases.

RESULTS

Nine prediction models were evaluated, each with varying clinical and methodological characteristics, including the types of surgical cohorts used for model development, AKI definitions, and predictors. In the validation cohort involving 13,186 patients, 650 (4.9%) developed AKI. Three models demonstrated fair discrimination (AUROC between 0.71 and 0.75); other models had poor or failed discrimination. All models exhibited some miscalibration; five of the nine models were well-calibrated after intercept and slope updates. Decision curve analysis indicated that the three models with fair discrimination consistently provided a positive net benefit after recalibration. The results were confirmed in the sensitivity analysis.

CONCLUSIONS

We identified three models with fair discrimination and potential clinical utility after recalibration for assessing the risk of acute kidney injury after noncardiac surgery.

Consistency of alerts generated by, and implementation of, the NHS England acute kidney injury detection algorithm in English laboratories

BACKGROUND

National Health Services (NHS) England mandates that an acute kidney injury (AKI) detection algorithm be embedded in laboratories. We evaluated the implementation of the algorithm and the consistency of alerts submitted to the United Kingdom Renal Registry (UKRR).

METHODS

Code was developed to simulate the syntax of the AKI detection algorithm, executed on data from local laboratories submitted to the UKRR, including alerts and serum creatinine (SCr) results spanning 15 months before and after the alert submission. Acute kidney injury alerts were categorized into stages 0/1/2/3. Inter-rater agreement (Gwet's AC1) was used to compare local and centrally derived alerts at individual laboratory and commercial laboratory information management system (LIMS) levels, penalizing extreme disagreements.

RESULTS

The analysis included 9,096,667 SCr results from 29 labs (475,634 patients; median age 72 years, 47% female) between algorithm activation and data extraction (September 30, 2020). Laboratories and the central simulation generated 1,579,633 and 1,646,850 non-zero AKI alerts, respectively. Agreement was high within known laboratory information management system providers (0.97-0.98) but varied across individual laboratories (overall range 0.17-0.98, 0.17-0.23 in three). Agreement tended to be lower (Gwet's AC1 0.88) with the highest baseline SCr quartile (median 164 μmol/L).

CONCLUSIONS

Overall, alerts submitted to the UKRR are a valid source of AKI surveillance but there are concerns about inconsistent laboratory practices, incomplete adoption of the NHSE algorithm code, alert suppression, and variable interpretation of guidelines. Future efforts should audit and support laboratories with low agreement rates, and explore reasons for lower agreement in individuals with pre-existing CKD.

Recognition patterns of acute kidney injury in hospitalized patients

Background

Acute kidney injury (AKI) during hospitalization is associated with increased complications and mortality. Despite efforts to standardize AKI management, its recognition in clinical practice is limited.

Methods

To assess and characterize different patterns of AKI diagnosis, we collected clinical data, serum creatinine (sCr) levels, comorbidities and outcomes from adult patients using the Hospital Discharge Form (HDF). AKI diagnosis was based on administrative data and according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria by evaluating sCr variations during hospitalization. Additionally, patients were categorized based on the timing of AKI onset.

Results

Among 56 820 patients, 42 900 (75.5%) had no AKI, 1893 (3.3%) had AKI diagnosed by sCr changes and coded in the HDF (full-AKI), 2529 (4.4%) had AKI reported on the HDF but not meeting sCr-based criteria (HDF-AKI) and 9498 (16.7%) had undetected AKI diagnosed by sCr changes but not coded in the HDF (KDIGO-AKI). Overall, AKI incidence was 24.5%, with a 68% undetection rate. Patients with KDIGO-AKI were younger and had a higher proportion of females, lower comorbidity burden, milder AKI stages, more frequent admissions to surgical wards and lower mortality compared with full-AKI patients. All AKI groups had worse outcomes than those without AKI, and AKI, even if undetected, was independently associated with mortality risk. Patients with AKI at admission had different profiles and better outcomes than those developing AKI later.

Conclusions

AKI recognition in hospitalized patients is highly heterogeneous, with a significant prevalence of undetection. This variability may be affected by patients' characteristics, AKI-related factors, diagnostic approaches and in-hospital patient management. AKI remains a major risk factor, emphasizing the importance of ensuring proper diagnosis for all patients.

Role of a Pharmacist in Postdischarge Care for Patients With Kidney Disease: A Scoping Review

OBJECTIVE

The objective was to explore and describe the role of pharmacists in providing postdischarge care to patients with kidney disease.

DATA SOURCES

PubMed, Embase (Elsevier), CINAHL (Ebscohost), Web of Science Core Collection, and Scopus were searched on January 30, 2023. Publication date limits were not included. Search terms were identified based on 3 concepts: kidney disease, pharmacy services, and patient discharge. Experimental, quasi-experimental, observational, and qualitative studies, or study protocols, describing the pharmacist's role in providing postdischarge care for patients with kidney disease, excluding kidney transplant recipients, were eligible.

STUDY SELECTION AND DATA EXTRACTION

Six unique interventions were described in 10 studies meeting inclusion criteria.

DATA SYNTHESIS

Four interventions targeted patients with acute kidney injury (AKI) during hospitalization and 2 evaluated patients with pre-existing chronic kidney disease. Pharmacists were a multidisciplinary care team (MDCT) member in 5 interventions and were the sole provider in 1. Roles commonly identified include medication review, medication reconciliation, medication action plan formation, kidney function assessment, drug dose adjustments, and disease education. Some studies showed improvements in diagnostic coding, laboratory monitoring, medication therapy problem (MTP) resolution, and patient education; prevention of hospital readmission was inconsistent. Limitations include lack of standardized reporting of kidney disease, transitions of care processes, and differences in outcomes evaluated.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

This review identifies potential roles of a pharmacist as part of a postdischarge MDCT for patients with varying degrees of kidney disease.

CONCLUSIONS

The pharmacist's role in providing postdischarge care to patients with kidney disease is inconsistent. Multidisciplinary care teams including a pharmacist provided consistent identification and resolution of MTPs, improved patient education, and increased self-awareness of diagnosis.

Epidemiology of acute kidney injury in children: a report from the 26th Acute Disease Quality Initiative (ADQI) consensus conference

The nephrology and critical care communities have seen an increase in studies exploring acute kidney injury (AKI) epidemiology in children. As a result, we now know that AKI is highly prevalent in critically ill neonates, children, and young adults. Furthermore, children who develop AKI experience greater morbidity and higher mortality. Yet knowledge gaps still exist that suggest a more comprehensive understanding of AKI will form the foundation for future efforts designed to improve outcomes. In particular, the areas of community acquired AKI, AKI in non-critically ill children, and cohorts from low-middle income countries have not been well studied. Longer-term functional outcomes and patient-centric metrics including social determinants of health, quality of life, and healthcare utilization should be the foci of the next phase of scholarship. Current definitions identify AKI-based upon evidence of dysfunction which serves as a proxy for injury; biomarkers capable of identifying injury as it occurs are likely to more accurately define populations with AKI. Despite the strength of the association, the causal and mechanistic relationships between AKI and poorer outcomes remain inadequately examined. A more robust understanding of the relationship represents a potential to identify therapeutic targets. Once established, a more comprehensive understanding of AKI epidemiology in children will allow investigation of preventive, therapeutic, and quality improvement interventions more effectively.

Recovery of kidney function after acute kidney disease-a multi-cohort analysis

BACKGROUND

There are no consensus definitions for evaluating kidney function recovery after acute kidney injury (AKI) and acute kidney disease (AKD), nor is it clear how recovery varies across populations and clinical subsets. We present a federated analysis of four population-based cohorts from Canada, Denmark and Scotland, 2011-18.

METHODS

We identified incident AKD defined by serum creatinine changes within 48 h, 7 days and 90 days based on KDIGO AKI and AKD criteria. Separately, we applied changes up to 365 days to address widely used e-alert implementations that extend beyond the KDIGO AKI and AKD timeframes. Kidney recovery was based on resolution of AKD and a subsequent creatinine measurement below 1.2× baseline. We evaluated transitions between non-recovery, recovery and death up to 1 year; within age, sex and comorbidity subgroups; between subset AKD definitions; and across cohorts.

RESULTS

There were 464 868 incident cases, median age 67-75 years. At 1 year, results were consistent across cohorts, with pooled mortalities for creatinine changes within 48 h, 7 days, 90 days and 365 days (and 95% confidence interval) of 40% (34%-45%), 40% (34%-46%), 37% (31%-42%) and 22% (16%-29%) respectively, and non-recovery of kidney function of 19% (15%-23%), 30% (24%-35%), 25% (21%-29%) and 37% (30%-43%), respectively. Recovery by 14 and 90 days was frequently not sustained at 1 year. Older males and those with heart failure or cancer were more likely to die than to experience sustained non-recovery, whereas the converse was true for younger females and those with diabetes.

CONCLUSION

Consistently across multiple cohorts, based on 1-year mortality and non-recovery, KDIGO AKD (up to 90 days) is at least prognostically similar to KDIGO AKI (7 days), and covers more people. Outcomes associated with AKD vary by age, sex and comorbidities such that older males are more likely to die, and younger females are less likely to recover.

Association of early postoperative serum magnesium with acute kidney injury after cardiac surgery

INTRODUCTION

Dysmagnesemia has been demonstrated to be involved in the pathophysiology of kidney diseases and is common in cardiac surgical patients. It remains unknown whether changes of serum magnesium after cardiac surgery affect AKI. We aimed to investigate the association of early postoperative magnesium with cardiac surgery-associated AKI in adults.

METHODS

We conducted a multicenter retrospective cohort study involving patients who underwent cardiac surgery in the eICU Collaborative Research Database between 2014 and 2015. AKI within 7 days after surgery was defined using both serum creatinine and urine output criteria of Kidney Disease Improving Global Outcomes definition. Postoperative AKI was analyzed using multivariable logistic regression with early postoperative serum magnesium measured within the first 24 h after surgery as a continuous variable and categorically by quartiles.

RESULTS

Postoperative AKI was identified in 3498 of 6124 (57.1%) patients receiving cardiac surgery. The median (25th-75th percentiles) early postoperative serum magnesium level of the study population was 2.3 (2.0-2.7) mg/dL. Higher serum magnesium level was associated with a higher risk of developing postoperative AKI (adjusted odds ratio (OR), 1.46 per 1 mg/dL increase; 95% confidence interval (CI), 1.31-1.62; p<.001). The multivariable-adjusted ORs (95% CIs) of postoperative AKI across increasing quartiles of serum magnesium were 1.00 (referent), 1.11 (0.95-1.29), 1.30 (1.12-1.52), and 1.72 (1.47-2.02) (p for trend <.001).

CONCLUSIONS

These data demonstrate a significantly higher incidence of AKI in patients with higher early postoperative serum magnesium who underwent cardiac surgery.

Defining measures of kidney function in observational studies using routine health care data: methodological and reporting considerations

The availability of electronic health records and access to a large number of routine measurements of serum creatinine and urinary albumin enhance the possibilities for epidemiologic research in kidney disease. However, the frequency of health care use and laboratory testing is determined by health status and indication, imposing certain challenges when identifying patients with kidney injury or disease, when using markers of kidney function as covariates, or when evaluating kidney outcomes. Depending on the specific research question, this may influence the interpretation, generalizability, and/or validity of study results. This review illustrates the heterogeneity of working definitions of kidney disease in the scientific literature and discusses advantages and limitations of the most commonly used approaches using 3 examples. We summarize ways to identify and overcome possible biases and conclude by proposing a framework for reporting definitions of exposures and outcomes in studies of kidney disease using routinely collected health care data.

Early Postoperative Acetaminophen Administration and Severe Acute Kidney Injury After Cardiac Surgery

RATIONALE & OBJECTIVE

Oxidative stress may contribute to the development of acute kidney injury (AKI) after cardiac surgery. Acetaminophen can be considered an antioxidant because it inhibits hemoprotein-catalyzed lipid peroxidation. We hypothesized that perioperative acetaminophen administration is associated with reduced AKI after cardiac surgery.

STUDY DESIGN

Retrospective observational cohort study.

SETTING & PARTICIPANTS

Patients aged≥18 years who had cardiac surgery were identified from 2 publicly available clinical registries: the Medical Information Mart for Intensive Care III (MIMIC-III) and the eICU Collaborative Research Database (eICU).

EXPOSURE

Administration of acetaminophen in the first 48 hours after surgery.

OUTCOME

Severe AKI in the first 7 days after surgery, defined as stage 2 or stage 3 AKI according to KDIGO criteria.

ANALYTICAL APPROACH

Multivariable cause-specific hazards regression analysis.

RESULTS

We identified 5,791 patients from the MIMIC-III and 3,840 patients from the eICU registries. The overall incidence of severe AKI was 58% (3,390 patients) in the MIMIC-III cohort and 37% (1,431 patients) in the eICU cohort. Acetaminophen was administered in the early postoperative period to 4,185 patients (72%) and 2,737 patients (71%) in these 2 cohorts, respectively. In multivariable regression models, early postoperative use of acetaminophen was associated with a lower risk of severe AKI in both the MIMIC-III (adjusted hazard ratio [AHR], 0.86 [95% CI, 0.79-0.94]) and eICU (AHR, 0.84 [95% CI, 0.72-0.97]) cohorts. The benefit was consistent across sensitivity and subgroup analyses.

LIMITATIONS

No data on acetaminophen dose.

CONCLUSIONS

Early postoperative acetaminophen administration was independently associated with a lower risk of severe AKI in adults recovering from cardiac surgery. Prospective trials are warranted to assess the extent to which the observed association is causal and estimate the extent to which acetaminophen administration might prevent or reduce the severity of AKI.

Fluids, vasopressors, and acute kidney injury after major abdominal surgery between 2015 and 2019: a multicentre retrospective analysis

BACKGROUND

Practice patterns related to intraoperative fluid administration and vasopressor use have potentially evolved over recent years. However, the extent of such changes and their association with perioperative outcomes, such as the development of acute kidney injury (AKI), have not been studied.

METHODS

We performed a retrospective analysis of major abdominal surgeries in adults across 26 US hospitals between 2015 and 2019. The primary outcome was AKI as defined by the Kidney Disease Improving Global Outcomes definition (KDIGO) using only serum creatinine criteria. Univariable linear predictive additive models were used to describe the dose-dependent risk of AKI given fluid administration or vasopressor use.

RESULTS

Over the study period, we observed a decrease in the volume of crystalloid administered, a decrease in the proportion of patients receiving more than 10 ml kg^-1 h^-1 of crystalloid, an increase in the amount of norepinephrine equivalents administered, and a decreased duration of hypotension. The incidence of AKI increased between 2016 and 2019. An increase of crystalloid administration from 1 to 10 ml kg^-1 h^-1 was associated with a 58% decreased risk of AKI.

CONCLUSIONS

Despite decreased duration of hypotension during the study period, decreased fluid administration and increased vasopressor use were associated with increased incidence of AKI. Crystalloid administration below 10 ml kg^-1 h^-1 was associated with an increased risk of AKI. Although no causality can be concluded, these data suggest that prevention and treatment of hypotension during abdominal surgery with liberal use of vasopressors at the expense of fluid administration is associated with an increased risk of postoperative AKI.

COVID-19 and kidney disease: insights from epidemiology to inform clinical practice

Over the course of the COVID-19 pandemic, numerous studies have aimed to address the challenges faced by patients with kidney disease and their caregivers. These studies addressed areas of concern such as the high infection and mortality risk of patients on in-centre haemodialysis and transplant recipients. However, the ability to draw meaningful conclusions from these studies has in some instances been challenging, owing to barriers in aspects of usual care, data limitations and problematic methodological practices. In many settings, access to SARS-CoV-2 testing differed substantially between patient groups, whereas the incidence of SARS-CoV-2 infection varied over time and place because of differences in viral prevalence, targeted public health policies and vaccination rates. The absence of baseline kidney function data posed problems in the classification of chronic kidney disease and acute kidney injury in some studies, potentially compromising the generalizability of findings. Study findings also require attentive appraisal in terms of the effects of confounding, collider bias and chance. As this pandemic continues and in the future, the implementation of sustainable and integrated research infrastructure is needed in settings across the world to minimize infection transmission and both prevent and plan for the short-term and long-term complications of infectious diseases. Registries can support the real-world evaluation of vaccines and therapies in patients with advanced kidney disease while enabling monitoring of rare complications.

Patient outcomes following AKI and AKD: a population-based cohort study

BACKGROUND

Acute kidney injury (AKI) is common and associated with adverse outcomes as well as important healthcare costs. However, evidence examining the epidemiology of acute kidney disease (AKD)-recently defined as AKI persisting between 7 and 90 days-remains limited. The aims of this study were to establish the rates of early AKI recovery, progression to AKD and non-recovery; examine risk factors associated with non-recovery and investigate the association between recovery timing and adverse outcomes, in a population-based cohort.

METHODS

All adult residents of Tayside & Fife, Scotland, UK, with at least one episode of community or hospital-managed AKI using KDIGO creatinine-based definition during the period 1 January 2010 to 31 December 2018 were identified. Logistic regression was used to examine factors associated with non-recovery, and Cox modelling was used to establish associations between AKI recovery timing and risks of mortality and development of de novo CKD.

RESULTS

Over 9 years, 56,906 patients with at least one AKI episode were identified with 18,773 (33%) of these progressing to AKD. Of those progressing to AKD, 5059 (27%) had still not recovered at day 90 post AKI diagnosis. Risk factors for AKD included: increasing AKI severity, pre-existing cancer or chronic heart failure and recent use of loop diuretics. Compared with early AKI recovery, progression to AKD was associated with increased hazard of 1-year mortality and de novo CKD (HR = 1.20, 95% CI 1.13 to 1.26 and HR = 2.21, 95% CI 1.91 to 2.57 respectively).

CONCLUSIONS

These findings highlight the importance of early AKI recognition and management to avoid progression to AKD and long-term adverse outcomes.

Prediction and Clinically Important Factors of Acute Kidney Injury Non-recovery

OBJECTIVE

This study aimed to identify phenotypic clinical features associated with acute kidney injury (AKI) to predict non-recovery from AKI at hospital discharge using electronic health record data.

METHODS

Data for hospitalized patients in the AKI Recovery Evaluation Study were derived from a large healthcare delivery system in Taiwan between January 2011 and December 2017. Living patients with AKI non-recovery were used to derive and validate multiple predictive models. In total, 64 candidates variables, such as demographic characteristics, comorbidities, healthcare services utilization, laboratory values, and nephrotoxic medication use, were measured within 1 year before the index admission and during hospitalization for AKI.

RESULTS

Among the top 20 important features in the predictive model, 8 features had a positive effect on AKI non-recovery prediction: AKI during hospitalization, serum creatinine (SCr) level at admission, receipt of dialysis during hospitalization, baseline comorbidity of cancer, AKI at admission, baseline lymphocyte count, baseline potassium, and low-density lipoprotein cholesterol levels. The predicted AKI non-recovery risk model using the eXtreme Gradient Boosting (XGBoost) algorithm achieved an area under the receiver operating characteristic (AUROC) curve statistic of 0.807, discrimination with a sensitivity of 0.724, and a specificity of 0.738 in the temporal validation cohort.

CONCLUSION

The machine learning model approach can accurately predict AKI non-recovery using routinely collected health data in clinical practice. These results suggest that multifactorial risk factors are involved in AKI non-recovery, requiring patient-centered risk assessments and promotion of post-discharge AKI care to prevent AKI complications.