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. 2025 Feb;14(2):447-461.
doi: 10.1007/s40121-024-01107-w. Epub 2025 Jan 21.

Predictors of COVID-19 Readmission Among Patients Previously Hospitalized for SARS-CoV-2

Marta Colaneri #  1 , Marta Canuti #  2 , Ginevra Torrigiani  3   4 , Lucia Dall'Olio  5 , Chiara Bobbio  6 , Sante L Baldi  5 , Alessandro Nobili  7 , Massimo Puoti  8 , Giulia Marchetti  9 , Simone Piva  10 , Pierluigi Plebani  11 , Mario Raviglione  5 , Andrea Gori  12 , Danilo Cereda  13 , Olivia Leoni  13 , Ida Fortino  13 , Maria Luisa Ojeda-Fernandez  4 , Marta Baviera  4 , Mauro Tettamanti  14 , Alessandra Bandera  6   15
Affiliations

Predictors of COVID-19 Readmission Among Patients Previously Hospitalized for SARS-CoV-2

Marta Colaneri et al. Infect Dis Ther. 2025 Feb.

Abstract

Introduction: Predictors of coronavirus disease 2019 (COVID-19)-related rehospitalization remain underexplored. This study aims to identify the main risk factors associated with rehospitalizations due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfections among residents of Lombardy, northern Italy.

Methods: A retrospective observational study was conducted using two linked administrative databases covering demographic data, comorbidities, hospital records, and COVID-19 data of Lombardy residents. The study population included patients hospitalized for COVID-19 between February 2020 and August 2021. Rehospitalization was defined as a second COVID-19-related hospitalization occurring at least 90 days after the first admission. The Fine-Gray subdistribution hazard model was used to identify risk factors, accounting for death as a competing risk.

Results: Out of 98,369 patients hospitalized for COVID-19 between February 1, 2020 and August 31, 2021, 72,593 were alive 90 days after admission and 610 of these (0.8%) were rehospitalized. A higher rehospitalization risk was observed in older male patients with multiple comorbidities. Renal failure, liver disease, and use of diuretics were significantly associated with rehospitalization risk, while female biological sex and the use of lipid-lowering drugs were associated with a lower risk.

Conclusions: This is the first study conducted on regional administrative databases to investigate COVID-19 rehospitalizations. Through the availability of a huge cohort, it provides a groundwork for optimizing care for individuals at higher risk for COVID-19-related rehospitalizations. It underlines the need for patient-management approaches that extend beyond the initial recovery. This stresses the importance of ongoing monitoring and personalized interventions for those at heightened risk not only of SARS-CoV-2 reinfection but also related rehospitalizations.

Keywords: Administrative databases; COVID-19; Regional health; Rehospitalization; SARS-CoV-2.

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Conflict of interest statement

Declarations. Conflict of Interest: Alessandra Bandera has received a grant from Gilead for data publication. Alessandra Bandera reports honoraria and payments from AstraZeneca-Biomeriux, Qiagen-Jassen Cilag, and Nordic-Pharma for lectures, presentations, speakers bureaus, manuscript writing, and educational events. Alessandra Bandera has received support for attending meetings and travel from Pfizer-AstraZeneca. Additionally, Alessandra Bandera has participated on Data Safety Monitoring Boards or Advisory Boards for ViiV, Sobi, and Gilead. Pierluigi Plebani has received grants from the European Commission (Horizon Europe Project TEADAL, grant agreement no. 101070186), the Italian Ministry of Health (Health Big Data Project), and the MADE Competence Center for the supervision of the Data Analytics and Cybersecurity area in MADE. Pierluigi Plebani reports honoraria as the Director of the Masters in Cloud and Data Engineering at Cefriel for lectures, presentations, manuscript writing, and educational events. Pierluigi Plebani has provided expert testimony for ATM Spa related to the analysis of their information systems. Additionally, Pierluigi Plebani has held a leadership role as Chair of IFIP WG 2.14/6.12/8.10 from 2017 to 2023. Marta Colaneri, Marta Canuti, Ginevra Torrigiani, Lucia Dall’Olio, Chiara Bobbio, Sante L. Baldi, Alessandro Nobili, Massimo Puoti, Giulia Marchetti, Simone Piva, Mario Raviglione, Andrea Gori, Danilo Cereda, Olivia Leoni, Ida Fortino, Maria Luisa Ojeda-Fernandez, Marta Baviera, and Mauro Tettamanti have no conflict of interest to declare. Ethical Approval: According to Italian law, studies using retrospective aggregated data from administrative databases that do not involve direct access by investigators to individual patient data do not require approval, notification from an Ethics Committee/institutional review board, or patient informed consent.

Figures

Fig. 1
Fig. 1
Study flow chart and timeline. The graph illustrates the number of patients included in the study and in each sub-group (A) and the follow-up timeline for each patient (B)
Fig. 2
Fig. 2
Adjusted hazard ratios (HZ) and 95% confidence intervals (CI 95%) of being rehospitalized (model 1) for COVID-19 at least 90 days after the first admission. Abbreviations. ICU intensive care unit, VTE venous thromboembolism, ACE-I angiotensin-converting enzyme inhibitors, ARBs angiotensin II receptor agonist blockers
Fig. 3
Fig. 3
Adjusted hazard ratios (HZ) and 95% confidence intervals (CI 95%) of being rehospitalized (model 2) for COVID-19 at least 90 days after the first admission. Abbreviations. ICU intensive care unit, ACE-I angiotensin-converting enzyme inhibitors, ARBs angiotensin II receptor agonist blockers
See this image and copyright information in PMC

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