Predicting in-hospital mortality from Coronavirus Disease 2019: A simple validated app for clinical use.
Adult
Aged
Aged, 80 and over
COVID-19
/ epidemiology
Cohort Studies
Female
Hospital Mortality
Hospitalization
/ statistics & numerical data
Humans
Italy
/ epidemiology
Male
Middle Aged
Mobile Applications
ROC Curve
Retrospective Studies
Risk Assessment
/ methods
Risk Factors
SARS-CoV-2
/ isolation & purification
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2021
2021
Historique:
received:
22
10
2020
accepted:
24
12
2020
entrez:
14
1
2021
pubmed:
15
1
2021
medline:
9
2
2021
Statut:
epublish
Résumé
Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19. We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07-1.09), male sex (HR 1.62, 95%CI 1.30-2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39-2.12), diabetes (HR 1.21, 95%CI 1.02-1.45), coronary heart disease (HR 1.40 95% CI 1.09-1.80), chronic liver disease (HR 1.78, 95%CI 1.16-2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002-1.0005). The AUC was 0.822 (95%CI 0.722-0.922) in the derivation cohort and 0.820 (95%CI 0.724-0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp). A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.
Sections du résumé
BACKGROUNDS
Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19.
METHODS AND FINDINGS
We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07-1.09), male sex (HR 1.62, 95%CI 1.30-2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39-2.12), diabetes (HR 1.21, 95%CI 1.02-1.45), coronary heart disease (HR 1.40 95% CI 1.09-1.80), chronic liver disease (HR 1.78, 95%CI 1.16-2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002-1.0005). The AUC was 0.822 (95%CI 0.722-0.922) in the derivation cohort and 0.820 (95%CI 0.724-0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp).
CONCLUSIONS
A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.
Identifiants
pubmed: 33444411
doi: 10.1371/journal.pone.0245281
pii: PONE-D-20-33218
pmc: PMC7808616
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0245281Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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