| Autor: |
Marina Davoli, Giuseppe Mancia, Salvatore Scondotto, Nello Martini, Massimo Galli, Federico Rea, Giovanni Corrao, Vito Lepore, Danilo Fusco, Adele Lallo, Flavia Carle, Paolo Francesconi, Antonio Lora, Olivia Leoni, Aldo Maggioni, Chiara Marinacci, Francesco Avossa, Rinaldo Zanini, Carlo Piccinni, Alessandra Allotta, Antonio D'Ettorre, Cinzia Tanzarella, Patrizia Vittori, Sabrina Abena, Marica Iommi, Liana Spazzafumo, Michele Ercolanoni, Roberto Blaco, Simona Carbone, Cristina Giordani, Dario Manfellotto, Donata Bellentani, Carla Ceccolini, Angela De Feo, Rosanna Mariniello, Modesta Visca, Natalia Magliocchetti, Giovanna Romano, Paola Pisanti, Edlira Skrami, Anna Cantarutti, Matteo Monzio Compagnoni, Pietro Pugni, Mirko Di Martino, Giuliana Vuillermin, Alfonso Bernardo, Anna Frusciante, Laura Belotti, Rossana De Palma, Andrea Di Lenarda, Marisa Prezza, Simone Pizzi, Lolita Gallo, Ettore Attolini, Giovanni De Luca, Carla Rizzuti, Silvia Vigna, Letizia Dondi, Antonella Pedrini, Mimma Cosentino, Maria Grazia Marvulli |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
BMJ Open, Vol 11, Iss 11 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2044-6055 |
| DOI: |
10.1136/bmjopen-2021-053281 |
| Popis: |
Objectives To develop a population-based risk stratification model (COVID-19 Vulnerability Score) for predicting severe/fatal clinical manifestations of SARS-CoV-2 infection, using the multiple source information provided by the healthcare utilisation databases of the Italian National Health Service.Design Retrospective observational cohort study.Setting Population-based study using the healthcare utilisation database from five Italian regions.Participants Beneficiaries of the National Health Service, aged 18–79 years, who had the residentship in the five participating regions. Residents in a nursing home were not included. The model was built from the 7 655 502 residents of Lombardy region.Main outcome measure The score included gender, age and 29 conditions/diseases selected from a list of 61 conditions which independently predicted the primary outcome, that is, severe (intensive care unit admission) or fatal manifestation of COVID-19 experienced during the first epidemic wave (until June 2020). The score performance was validated by applying the model to several validation sets, that is, Lombardy population (second epidemic wave), and the other four Italian regions (entire 2020) for a total of about 15.4 million individuals and 7031 outcomes. Predictive performance was assessed by discrimination (areas under the receiver operating characteristic curve) and calibration (plot of observed vs predicted outcomes).Results We observed a clear positive trend towards increasing outcome incidence as the score increased. The areas under the receiver operating characteristic curve of the COVID-19 Vulnerability Score ranged from 0.85 to 0.88, which compared favourably with the areas of generic scores such as the Charlson Comorbidity Score (0.60). A remarkable performance of the score on the calibration of observed and predicted outcome probability was also observed.Conclusions A score based on data used for public health management accurately predicted the occurrence of severe/fatal manifestations of COVID-19. Use of this score may help health decision-makers to more accurately identify high-risk citizens who need early preventive or treatment interventions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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