Prognostic models in COVID-19 infection that predict severity: a systematic review.
Biomarkers
COVID-19
ICU
Mortality
Prediction models
Systematic review
Journal
European journal of epidemiology
ISSN: 1573-7284
Titre abrégé: Eur J Epidemiol
Pays: Netherlands
ID NLM: 8508062
Informations de publication
Date de publication:
Apr 2023
Apr 2023
Historique:
received:
29
03
2022
accepted:
28
01
2023
medline:
11
4
2023
pubmed:
26
2
2023
entrez:
25
2
2023
Statut:
ppublish
Résumé
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.
Identifiants
pubmed: 36840867
doi: 10.1007/s10654-023-00973-x
pii: 10.1007/s10654-023-00973-x
pmc: PMC9958330
doi:
Types de publication
Systematic Review
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
355-372Subventions
Organisme : Horizon 2020
ID : 101017915
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
ID : #320030_176216
Informations de copyright
© 2023. The Author(s).
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