Evidence map›Paper›PMID 34585270›Full record

ArticleIntensive care medicine2021

External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals.

Yannis Lombardi, Loris Azoyan, Piotr Szychowiak, Ali Bellamine, Guillaume Lemaitre, Mélodie Bernaux, Christel Daniel, Judith Leblanc, Quentin Riller, Olivier Steichen and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Intensive care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
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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

43 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Yannis LombardiFaculty of Medicine, AP-HP, Sorbonne Université, Paris, France.
Loris Azoyan *Faculty of Medicine, AP-HP, Sorbonne Université, Paris, France.
Piotr Szychowiak *Médecine Intensive-Réanimation, Centre Hospitalier Régional Universitaire de Tours, Tours, France.
Ali BellamineWIND Department, TAL group, AP-HP, Paris, France.
Guillaume LemaitreParis Saclay University, INRIA, CEA, Palaiseau, France.
Mélodie BernauxStrategy and Transformation Department, AP-HP, Paris, France.
Christel DanielWIND Department, AP-HP, Paris, France.
Judith LeblancInstitut Pierre Louis d'Épidémiologie et de Santé Publique, UMR-S 1136 , Sorbonne Université, INSERM, Paris, France.
Quentin RillerFaculty of Medicine, AP-HP, Sorbonne Université, Paris, France.
Olivier SteichenInstitut Pierre Louis d'Épidémiologie et de Santé Publique, UMR-S 1136 , Sorbonne Université, INSERM, Paris, France. olivier.steichen@aphp.fr.ORCID http://orcid.org/0000-0002-1185-0372
AP-HP/Universities/INSERM COVID-19 Research Collaboration AP-HP COVID CDR Initiative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19.

methodsWe used "COVID-19 Evidence Alerts" (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer.

resultsWe included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome.

conclusionSeven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients.

Indexed as

COVID-19AdultCohort StudiesHospitals, UniversityHumansParisPrognosisRetrospective StudiesSARS-CoV-2Cohort studiesCOVID-19Intensive care unitsMortalityPrognosisSARS-CoV-2

Identifiers

PMID34585270
PMCPMC8478265

What OpenQuestion holds

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Registered trials

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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.