Validity of prognostic models of critical COVID-19 is variable. A systematic review with external validation

Gabriela Cárdenas-Fuentes, Magda Bosch de Basea, Inés Cobo, Isaac Subirana, Mario Ceresa, Ernest Famada, Elena Gimeno-Santos, Laura Delgado-Ortiz, Rosa Faner, María Molina-Molina, Àlvar Agustí, Xavier Muñoz, Oriol Sibila, Joaquim Gea, Judith Garcia-Aymerich

Research output: Indexed journal article Reviewpeer-review

2 Citations (Scopus)


Objectives: To identify prognostic models which estimate the risk of critical COVID-19 in hospitalized patients and to assess their validation properties. Study Design and Setting: We conducted a systematic review in Medline (up to January 2021) of studies developing or updating a model that estimated the risk of critical COVID-19, defined as death, admission to intensive care unit, and/or use of mechanical ventilation during admission. Models were validated in two datasets with different backgrounds (HM [private Spanish hospital network], n = 1,753, and ICS [public Catalan health system], n = 1,104), by assessing discrimination (area under the curve [AUC]) and calibration (plots). Results: We validated 18 prognostic models. Discrimination was good in nine of them (AUCs ≥ 80%) and higher in those predicting mortality (AUCs 65%–87%) than those predicting intensive care unit admission or a composite outcome (AUCs 53%–78%). Calibration was poor in all models providing outcome's probabilities and good in four models providing a point-based score. These four models used mortality as outcome and included age, oxygen saturation, and C-reactive protein among their predictors. Conclusion: The validity of models predicting critical COVID-19 by using only routinely collected predictors is variable. Four models showed good discrimination and calibration when externally validated and are recommended for their use.

Original languageEnglish
Pages (from-to)274-288
Number of pages15
JournalJournal of Clinical Epidemiology
Publication statusPublished - Jul 2023


  • COVID-19
  • Critical disease
  • Epidemiology
  • External validation
  • Intensive care unit
  • Prognostic models


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