Use of an extended KDIGO definition to diagnose acute kidney injury in patients with COVID-19: A multinational study using the ISARIC–WHO clinical characterisation protocol

Abstract

Background Acute kidney injury (AKI) is one of the most common and significant problems in patients with Coronavirus Disease 2019 (COVID-19). However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional Kidney Disease Improving Global Outcomes (KDIGO) definition can fail to identify patients for whom hospitalisation coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesised that an extended KDIGO (eKDIGO) definition, adapted from the International Society of Nephrology (ISN) 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI (CA-AKI) with similarly poor outcomes as previously reported in this population. Methods and findings All individuals recruited using the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC)–World Health Organization (WHO) Clinical Characterisation Protocol (CCP) and admitted to 1,609 hospitals in 54 countries with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection from February 15, 2020 to February 1, 2021 were included in the study. Data were collected and analysed for the duration of a patient’s admission. Incidence, staging, and timing of AKI were evaluated using a traditional and eKDIGO definition, which incorporated a commensurate decrease in sCr. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristics and outcomes—intensive care unit (ICU) admission, invasive mechanical ventilation, and in-hospital death—were compared for all 3 groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. A total of 75,670 patients were included in the final analysis cohort. Median length of admission was 12 days (interquartile range [IQR] 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7% versus 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% versus 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% versus 23%) invasive ventilation (45% versus 15%), and increased mortality (38% versus 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted odds ratio: 1.78, 95% confidence interval: 1.71 to 1.80, p-value < 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% versus 50% death and 35% versus 70% ICU admission) but significantly higher when compared to patients with no AKI (25% versus 19% death and 35% versus 23% ICU admission) (all p-values <5 × 10−5). Limitations include ad hoc sCr sampling, exclusion of patients with less than 2 sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis. Conclusions An extended KDIGO definition of AKI resulted in a significantly higher detection rate in this population. These additional cases of AKI occurred early in the hospital admission and were associated with worse outcomes compared to patients without AKI.

COVID-19 and Kidney Disease: Progress in Health Inequity From Low-Income Settings

“…A recent introduction of the Extended Kidney Disease Improving Global Outcome (eKDIGO) AKI criteria was adopted by the International Society of Nephrology (ISN) AKI 0by25 studies for COVID-19. The new definition includes the decrement of serum creatinine of 26.5umol/L in 48 hours or fall by 1.5 times from the baseline in 7 days, which identified twice as many cases of AKI as compared to the traditional criteria (31.7% versus 16.8%) [56] . This classification has significant logistic challenges if implemented in LLMICs as it requires frequent measurement of serum creatinine even in stable cases, which is prohibitive due to cost.…”

Outcomes of COVID-19 patients with acute kidney injury and longitudinal analysis of laboratory markers during the hospital stay: A multi-center retrospective cohort experience from Pakistan

“…Other potential limitations include lack of determining urinary markers for renal injury like proteinuria as outlined by Lombardi et al in their study. [ 41 ] We relied upon serum markers and KDIGO classification, [ 11 ] for AKI determination but without documenting the categorization of patients into stages of AKI which is been frequently reported in the literature. However, we were not aiming the external validity for staging AKI because of the main objectives revolved around the determination of AKI with respect to symptomology, clinical profiles, and laboratory markers in our cohort.…”

“…AKI was determined based on extended KDIGO classification of renal injury in COVID-19 patients exclusively, as previously published. [ 11 ] Staging of the kidney injury was also established with KDIGO/AKIN criteria. Further, acute on chronic kidney injury was also determined based on worsening of renal markers during the COVID-19 disease course.…”

Preregistered analytic plan: the gut microbiome and acute kidney injury in sepsis

“…We defined and staged AKI using the Kidney Disease Improving Global Outcomes (KDIGO) consortium definition of AKI, which defines AKI onset as a ≥ 50% increase in baseline serum creatinine within seven days of admission 24 . The KDIGO definition of AKI builds upon prior RIFLE 25 and AKIN 26 criteria for defining and staging AKI and has been used successfully in numerous studies.…”