| Institution: | 1. Centre Hospitalier Régional Universitaire de Nancy, 54511 Vandoeuvre-lès-Nancy, France;2. Université de Paris, PARCC, INSERM, 75015 Paris, France;3. Nouvel Hopital Civil, Centre Hospitalier Régional Universitaire de Strasbourg, 67000 Strasbourg, France;4. Centre Hospitalier Universitaire de Dijon, 21000 Dijon, France;5. Hôpital Européen Georges-Pompidou, Université de Paris, 75015 Paris, France;6. Centre Hospitalier Universitaire d’Amiens-Picardie, 80000 Amiens, France;7. Centre Hospitalier Universitaire de Marseille, 13005 Marseille, France;8. GCS-Groupement des Hôpitaux de l’Institut Catholique de Lille, Faculté de Médecine et de Maïeutique, Université Catholique de Lille, 59800 Lille, France;9. Centre Hospitalier Universitaire de Toulouse, 31400 Toulouse, France;10. Centre Hospitalier Universitaire de Caen-Normandie, 14000 Caen, France;11. Centre Hospitalier Universitaire de Reims, 51100 Reims, France;12. Institut Mutualiste Montsouris, 75014 Paris, France;13. Institut Cardiovasculaire Paris Sud, 91300 Massy, France;14. Centre Hospitalier Universitaire de Rouen, FHU REMOD-VHF, 76000 Rouen, France;15. Centre Hospitalier Universitaire de Bordeaux, 33076 Bordeaux, France;p. Clinique Saint-Gatien, 37540 Saint-Cyr-sur-Loire, France;q. Centre Hospitalier Intercommunal Fréjus-Saint-Raphaël, 83600 Fréjus, France;r. Centre Hospitalier Régional de Orléans, 45100 Orléans, France;s. Centre Hospitalier Annecy Genevois, 74370 Épagny-Metz-Tessy, France;t. Hôpital Bichat-Claude-Bernard, AP–HP, Université de Paris, 75018 Paris, France;u. Université Paris-Saclay, Inserm, UMR-S 1180, 92296 Chatenay-Malabry, France;v. Hôpital Lariboisière, AP–HP, Université de Paris, 75010 Paris, France;w. Hôpital Saint-Antoine, 75012 Paris, France |
| Abstract: | BackgroundThe evolution of patients hospitalized with coronavirus disease 2019 (COVID-19) is still hard to predict, even after several months of dealing with the pandemic.AimsTo develop and validate a score to predict outcomes in patients hospitalized with COVID-19.MethodsAll consecutive adults hospitalized for COVID-19 from February to April 2020 were included in a nationwide observational study. Primary composite outcome was transfer to an intensive care unit from an emergency department or conventional ward, or in-hospital death. A score that estimates the risk of experiencing the primary outcome was constructed from a derivation cohort using stacked LASSO (Least Absolute Shrinkage and Selection Operator), and was tested in a validation cohort.ResultsAmong 2873 patients analysed (57.9% men; 66.6 ± 17.0 years), the primary outcome occurred in 838 (29.2%) patients: 551 (19.2%) were transferred to an intensive care unit; and 287 (10.0%) died in-hospital without transfer to an intensive care unit. Using stacked LASSO, we identified 11 variables independently associated with the primary outcome in multivariable analysis in the derivation cohort (n = 2313), including demographics (sex), triage vitals (body temperature, dyspnoea, respiratory rate, fraction of inspired oxygen, blood oxygen saturation) and biological variables (pH, platelets, C-reactive protein, aspartate aminotransferase, estimated glomerular filtration rate). The Critical COVID-19 France (CCF) risk score was then developed, and displayed accurate calibration and discrimination in the derivation cohort, with C-statistics of 0.78 (95% confidence interval 0.75–0.80). The CCF risk score performed significantly better (i.e. higher C-statistics) than the usual critical care risk scores.ConclusionsThe CCF risk score was built using data collected routinely at hospital admission to predict outcomes in patients with COVID-19. This score holds promise to improve early triage of patients and allocation of healthcare resources. |
