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. 2020 Nov 26;10(1):20731.
doi: 10.1038/s41598-020-77698-4.

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Mattia Bellan  1   2 , Giuseppe Patti  1   2 , Eyal Hayden  1   2 , Danila Azzolina  1 , Mario Pirisi  1   2 , Antonio Acquaviva  1   2 , Gianluca Aimaretti  1   2 , Paolo Aluffi Valletti  1   2 , Roberto Angilletta  3 , Roberto Arioli  1   2 , Gian Carlo Avanzi  1   2 , Gianluca Avino  1   2 , Piero Emilio Balbo  2 , Giulia Baldon  1   2 , Francesca Baorda  1   4 , Emanuela Barbero  1   2 , Alessio Baricich  1   2 , Michela Barini  2 , Francesco Barone-Adesi  1 , Sofia Battistini  1   2 , Michela Beltrame  1   2 , Matteo Bertoli  1   2 , Stephanie Bertolin  1   2 , Marinella Bertolotti  3 , Marta Betti  3 , Flavio Bobbio  2 , Paolo Boffano  1   2 , Lucio Boglione  1   4 , Silvio Borrè  4 , Matteo Brucoli  1   2 , Elisa Calzaducca  1   2 , Edoardo Cammarata  1   2 , Vincenzo Cantaluppi  1   2 , Roberto Cantello  1   2 , Andrea Capponi  2 , Alessandro Carriero  1   2 , Francesco Giuseppe Casciaro  1   2 , Luigi Mario Castello  1   2 , Federico Ceruti  1   2 , Guido Chichino  3 , Emilio Chirico  1   2 , Carlo Cisari  1   2 , Micol Giulia Cittone  1   2 , Crizia Colombo  1   2 , Cristoforo Comi  1   4 , Eleonora Croce  1   4 , Tommaso Daffara  1   2 , Pietro Danna  1   2 , Francesco Della Corte  1   2 , Simona De Vecchi  1   2 , Umberto Dianzani  1   2 , Davide Di Benedetto  1   2 , Elia Esposto  1   2 , Fabrizio Faggiano  1 , Zeno Falaschi  1   2 , Daniela Ferrante  1 , Alice Ferrero  1   2 , Ileana Gagliardi  1   2 , Gianluca Gaidano, Alessandra Galbiati  1   2 , Silvia Gallo  1   4 , Pietro Luigi Garavelli  2 , Clara Ada Gardino  1   2 , Massimiliano Garzaro  1   2 , Maria Luisa Gastaldello  1   2 , Francesco Gavelli  1   2 , Alessandra Gennari  1   2 , Greta Maria Giacomini  1   2 , Irene Giacone  1   4 , Valentina Giai Via  1   2 , Francesca Giolitti  1   2 , Laura Cristina Gironi  1   2 , Carla Gramaglia  1   2 , Leonardo Grisafi  1   2 , Ilaria Inserra  1   2 , Marco Invernizzi  1   2 , Marco Krengli  1   2 , Emanuela Labella  1   2 , Irene Cecilia Landi  1   2 , Raffaella Landi  1   2 , Ilaria Leone  1   2 , Veronica Lio  1   2 , Luca Lorenzini  1   2 , Antonio Maconi  3 , Mario Malerba  1   4 , Giulia Francesca Manfredi  1   2 , Maria Martelli  1   2 , Letizia Marzari  1   2 , Paolo Marzullo  1   2 , Marco Mennuni  2 , Claudia Montabone  1   4 , Umberto Morosini  1   2 , Marco Mussa  3 , Ilaria Nerici  1   2 , Alessandro Nuzzo  1   2 , Carlo Olivieri  4 , Samuel Alberto Padelli  1   4 , Massimiliano Panella  1 , Andrea Parisini  3 , Alessio Paschè  1   2 , Alberto Pau  1   2 , Anita Rebecca Pedrinelli  1   2 , Ilaria Percivale  1   2 , Roberta Re  4 , Cristina Rigamonti  1   2 , Eleonora Rizzi  1   2 , Andrea Rognoni  2 , Annalisa Roveta  3 , Luigia Salamina  2 , Matteo Santagostino  2 , Massimo Saraceno  1   2 , Paola Savoia  1   2 , Marco Sciarra  3 , Andrea Schimmenti  3 , Lorenza Scotti  1 , Enrico Spinoni  1   2 , Carlo Smirne  1   2 , Vanessa Tarantino  1   2 , Paolo Amedeo Tillio  1   4 , Rosanna Vaschetto  1   2 , Veronica Vassia  1   2 , Domenico Zagaria  1   2 , Elisa Zavattaro  2 , Patrizia Zeppegno  1   2 , Francesca Zottarelli  1   2 , Pier Paolo Sainaghi  5   6
Affiliations

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Mattia Bellan et al. Sci Rep. .

Abstract

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The figure details the selection of the study population.
Figure 2
Figure 2
Histogram frequency plot for days until death from hospitalization (panel A) or symptoms onset (panel B).
Figure 3
Figure 3
In-hospital survival curve. The median in-hospital survival time is equal to 8 days (95% CI 7; 11).
Figure 4
Figure 4
Random forest variable importance plot. The variables have been ranked in order of relevance in predicting in-hospital mortality. The importance measure considered for the analysis is the mean decrease in accuracy computed via Random Forest Classification Algorithm. The Random forest model accuracy is equal to 82.5% achieved with 1000 trees and 3 mtry.
See this image and copyright information in PMC

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