Evidence map›Paper›PMID 35442972›Full record

ArticlePLoS medicine2022

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.

Marina Wainstein, Samual MacDonald, Daniel Fryer, Kyle Young, Valeria Balan, Husna Begum, Aidan Burrell, Barbara Wanjiru Citarella, J Perren Cobb, Sadie Kelly and 12 more

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Electronic Phenotype for Detection, Staging, and Subtyping of Acute Kidney Injury.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026
    Article
  5. Observational
  6. Positive fluid balance is associated with earlier acute kidney injury in COVID-19 patients.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2026
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Anti-Anaerobic Antibiotics, Gut Microbiota, and Sepsis-associated Acute Kidney Injury.American journal of respiratory and critical care medicine · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Observational
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 12 institutions in 8 countries.

Marina WainsteinFaculty of Medicine, University of Queensland, Brisbane, Australia.ORCID 0000-0002-5915-6101
Samual MacDonaldSchool of Mathematics and Physics, University of Queensland, Brisbane, Australia.ORCID 0000-0002-7199-815X
Daniel FryerSchool of Mathematics and Physics, University of Queensland, Brisbane, Australia.ORCID 0000-0001-6032-0522
Kyle YoungSchool of Mathematics and Physics, University of Queensland, Brisbane, Australia.ORCID 0000-0001-6911-8216
Valeria BalanInternational Severe Acute Respiratory and emerging Infection Consortium, Centre for Tropical Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-5458-7124
Husna BegumAustralian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Australia.
Aidan BurrellAustralian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Australia.ORCID 0000-0001-8430-9678
Barbara Wanjiru CitarellaISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-8968-0708
J Perren CobbUniversity of Southern California, Los Angeles, California, United States of America.ORCID 0000-0003-1335-7124
Sadie KellyInfectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-1691-6147
Kalynn KennonInfectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-3531-0298
James LeeCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4360-7326
Laura MersonInfectious Diseases Data Observatory, Centre for Global Health and Tropical Medicine, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4168-1960
Srinivas MurthyFaculty of Medicine, University of British Columbia, Vancouver, Canada.ORCID 0000-0002-9476-839X
Alistair NicholThe Alfred Hospital, Intensive Care Unit, Melbourne, Australia.
Malcolm G SempleNIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom.ORCID 0000-0001-9700-0418
Samantha StrudwickInfectious Diseases Data Observatory (IDDO), University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-2946-8366
Steven A WebbAustralian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Australia.
Patrick RossignolUniversité de Lorraine, INSERM, Centre d'Investigations Cliniques-Plurithématique 14-33, INSERM U1116, CHRU Nancy, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France.ORCID 0000-0001-8009-3873
Rolando Claure-Del GranadoDivision of Nephrology, Hospital Obrero No 2-CNS, Cochabamba, Bolivia.ORCID 0000-0002-8163-3779
Sally ShrapnelCentre for Health Services Research, University of Queensland, Brisbane, Australia.ORCID 0000-0001-8407-7176
ISARIC Clinical Characterisation Group
The University of Queensland · AUOpen Data Institute · GBUniversity of Oxford · GBAustralian and New Zealand Intensive Care Society · AUAngkor Hospital for Children · KHInserm · FRThe Alfred Hospital · AUUniversidad Mayor de San Simón · BOUniversity College Dublin · IEUniversity of British Columbia · CAUniversity of Liverpool · GBUniversity of Southern California · US

Funding

CIHR OV2170359Department of Health 200907Medical Research Council MC_PC_19025Medical Research Council MC_PC_19059Wellcome TrustWellcome Trust 215091/Z/18/ZWellcome Trust 222410/Z/21/Z
6 · The paper itself

Abstract

backgroundAcute 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

findingsAll 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 two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis.

conclusionsAn 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.

Indexed as

Acute Kidney InjuryCOVID-19FemaleHospital MortalityHumansIntensive Care UnitsKidneyMaleRetrospective StudiesRisk FactorsSARS-CoV-2World Health Organization

Identifiers

PMID35442972
PMCPMC9067700
OpenAlexW4224213628

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.