Clinical risk scores for the early prediction of severe outocomes in patients hospitalized for COVID-19: comment
| Autor: | Rossio R., Tettamanti M., Nobili A., Harari S., Mannucci P. M., Bandera A., Peyvandi F., Bosari S., Scudeller L., Fusetti G., Rusconi L., Dell'Orto S., Prati D., Valenti L., Giovannelli S., Manunta M., Lamorte G., Ferrari F., Gori A., Muscatello A., Mangioni D., Alagna L., Bozzi G., Lombardi A., Ungaro R., Ancona G., Zuglian G., Bolis M., Iannotti N., Ludovisi S., Comelli A., Renisi G., Biscarini S., Castelli V., Palomba E., Fava M., Fortina V., Peri C. A., Saltini P., Viero G., Itri T., Ferroni V., Pastore V., Massafra R., Liparoti A., Muheberimana T., Giommi A., Bianco R., De Azevedo R. M., Chitani G. E., Gualtierotti R., Ferrari B., Boasi N., Pagliaro E., Massimo C., De Caro M., Giachi A., Montano N., Vigone B., Bellocchi C., Carandina A., Fiorelli E., Melli V., Tobaldini E., Blasi F., Aliberti S., Spotti M., Terranova L., Misuraca S., D'Adda A., Fiore S. D., Di Pasquale M., Mantero M., Contarini M., Ori M., Morlacchi L., Rossetti V., Gramegna A., Pappalettera M., Cavallini M., Buscemi A., Vicenzi M., Rota I., Costantino G., Solbiati M., Furlan L., Mancarella M., Colombo G., Fanin A., Passarella M., Monzani V., Canetta C., Rovellini A., Barbetta L., Billi F., Folli C., Accordino S., Maira D., Hu C. M., Motta I., Scaramellini N., Fracanzani A. L., Lombardi R., Cespiati A., Cesari M., Lucchi T., Proietti M., Calcaterra L., Mandelli C., Coppola C., Cerizza A., Pesenti A. M., Grasselli G., Galazzi A., Monti I., Galbussera A. A., Crisafulli E., Girelli D., Maroccia A., Gabbiani D., Busti F., Vianello A., Biondan M., Sartori F., Faverio P., Pesci A., Zucchetti S., Bonfanti P., Rossi M., Beretta I., Spolti A., Elia D., Cassandro R., Caminati A., Cipollone F., Guagnano M. T., D'Ardes D., Rossi I., Vezzani F., Spanevello A., Cherubino F., Visca D., Contoli M., Papi A., Morandi L., Battistini N., Moreo G. L., Iannuzzi P., Fumagalli D., Leone S. |
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| Přispěvatelé: | Rossio, R, Tettamanti, M, Nobili, A, Harari, S, Mannucci, P, Bandera, A, Peyvandi, F, Bosari, S, Scudeller, L, Fusetti, G, Rusconi, L, Dell'Orto, S, Prati, D, Valenti, L, Giovannelli, S, Manunta, M, Lamorte, G, Ferrari, F, Gori, A, Muscatello, A, Mangioni, D, Alagna, L, Bozzi, G, Lombardi, A, Ungaro, R, Ancona, G, Zuglian, G, Bolis, M, Iannotti, N, Ludovisi, S, Comelli, A, Renisi, G, Biscarini, S, Castelli, V, Palomba, E, Fava, M, Fortina, V, Peri, C, Saltini, P, Viero, G, Itri, T, Ferroni, V, Pastore, V, Massafra, R, Liparoti, A, Muheberimana, T, Giommi, A, Bianco, R, De Azevedo, R, Chitani, G, Gualtierotti, R, Ferrari, B, Boasi, N, Pagliaro, E, Massimo, C, De Caro, M, Giachi, A, Montano, N, Vigone, B, Bellocchi, C, Carandina, A, Fiorelli, E, Melli, V, Tobaldini, E, Blasi, F, Aliberti, S, Spotti, M, Terranova, L, Misuraca, S, D'Adda, A, Fiore, S, Di Pasquale, M, Mantero, M, Contarini, M, Ori, M, Morlacchi, L, Rossetti, V, Gramegna, A, Pappalettera, M, Cavallini, M, Buscemi, A, Vicenzi, M, Rota, I, Costantino, G, Solbiati, M, Furlan, L, Mancarella, M, Colombo, G, Fanin, A, Passarella, M, Monzani, V, Canetta, C, Rovellini, A, Barbetta, L, Billi, F, Folli, C, Accordino, S, Maira, D, Hu, C, Motta, I, Scaramellini, N, Fracanzani, A, Lombardi, R, Cespiati, A, Cesari, M, Lucchi, T, Proietti, M, Calcaterra, L, Mandelli, C, Coppola, C, Cerizza, A, Pesenti, A, Grasselli, G, Galazzi, A, Monti, I, Galbussera, A, Crisafulli, E, Girelli, D, Maroccia, A, Gabbiani, D, Busti, F, Vianello, A, Biondan, M, Sartori, F, Faverio, P, Pesci, A, Zucchetti, S, Bonfanti, P, Rossi, M, Beretta, I, Spolti, A, Elia, D, Cassandro, R, Caminati, A, Cipollone, F, Guagnano, M, D'Ardes, D, Rossi, I, Vezzani, F, Spanevello, A, Cherubino, F, Visca, D, Contoli, M, Papi, A, Morandi, L, Battistini, N, Moreo, G, Iannuzzi, P, Fumagalli, D, Leone, S |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
Outcome Assessment Disease 030204 cardiovascular system & hematology Respiratory failure 0302 clinical medicine Risk Factors Epidemiology Early prediction Outcome Assessment Health Care 030212 general & internal medicine Framingham Risk Score Respiration Area under the curve Middle Aged Hospitalization Survival Rate Italy Artificial Emergency Medicine Female Clinical risk factor 2019-20 coronavirus outbreak medicine.medical_specialty Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Ce - Letter to the Editor MEDLINE Risk Assessment 03 medical and health sciences Predictive Value of Tests Internal medicine Internal Medicine medicine Intubation Intratracheal Humans In patient Derivation COVID-19 Risk prediction model SARS-CoV 2 Selection (genetic algorithm) Aged Retrospective Studies SARS-CoV-2 business.industry Retrospective cohort study Respiration Artificial Im - Original Health Care Intratracheal ROC Curve Intubation business |
| Zdroj: | Internal and Emergency Medicine |
| Popis: | Coronavirus disease of 2019 (COVID-19) is associated with severe acute respiratory failure. Early identification of high-risk COVID-19 patients is crucial. We aimed to derive and validate a simple score for the prediction of severe outcomes. A retrospective cohort study of patients hospitalized for COVID-19 was carried out by the Italian Society of Internal Medicine. Epidemiological, clinical, laboratory, and treatment variables were collected at hospital admission at five hospitals. Three algorithm selection models were used to construct a predictive risk score: backward Selection, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. Severe outcome was defined as the composite of need for non-invasive ventilation, need for orotracheal intubation, or death. A total of 610 patients were included in the analysis, 313 had a severe outcome. The subset for the derivation analysis included 335 patients, the subset for the validation analysis 275 patients. The LASSO selection identified 6 variables (age, history of coronary heart disease, CRP, AST, D-dimer, and neutrophil/lymphocyte ratio) and resulted in the best performing score with an area under the curve of 0.79 in the derivation cohort and 0.80 in the validation cohort. Using a cut-off of 7 out of 13 points, sensitivity was 0.93, specificity 0.34, positive predictive value 0.59, and negative predictive value 0.82. The proposed score can identify patients at low risk for severe outcome who can be safely managed in a low-intensity setting after hospital admission for COVID-19. |
| Databáze: | OpenAIRE |
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