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Mercurio G, Gottardelli B, Lenkowicz J, Patarnello S, Bellavia S, Scala I, Rizzo P, de Belvis AG, Del Signore AB, Maviglia R, Bocci MG, Olivi A, Franceschi F, Urbani A, Calabresi P, Valentini V, Antonelli M, Frisullo G. A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model. Eur J Neurol 2024; 31:e16153. [PMID: 38015472 DOI: 10.1111/ene.16153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/29/2023] [Accepted: 10/31/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND The 30-day hospital re-admission rate is a quality measure of hospital care to monitor the efficiency of the healthcare system. The hospital re-admission of acute stroke (AS) patients is often associated with higher mortality rates, greater levels of disability and increased healthcare costs. The aim of our study was to identify predictors of unplanned 30-day hospital re-admissions after discharge of AS patients and define an early re-admission risk score (RRS). METHODS This observational, retrospective study was performed on AS patients who were discharged between 2014 and 2019. Early re-admission predictors were identified by machine learning models. The performances of these models were assessed by receiver operating characteristic curve analysis. RESULTS Of 7599 patients with AS, 3699 patients met the inclusion criteria, and 304 patients (8.22%) were re-admitted within 30 days from discharge. After identifying the predictors of early re-admission by logistic regression analysis, RRS was obtained and consisted of seven variables: hemoglobin level, atrial fibrillation, brain hemorrhage, discharge home, chronic obstructive pulmonary disease, one and more than one hospitalization in the previous year. The cohort of patients was then stratified into three risk categories: low (RRS = 0-1), medium (RRS = 2-3) and high (RRS >3) with re-admission rates of 5%, 8% and 14%, respectively. CONCLUSIONS The identification of risk factors for early re-admission after AS and the elaboration of a score to stratify at discharge time the risk of re-admission can provide a tool for clinicians to plan a personalized follow-up and contain healthcare costs.
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Affiliation(s)
- Giovanna Mercurio
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Benedetta Gottardelli
- Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Jacopo Lenkowicz
- Gemelli Generator RWD, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Stefano Patarnello
- Gemelli Generator RWD, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Simone Bellavia
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Irene Scala
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Pierandrea Rizzo
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Antonio Giulio de Belvis
- Department of Life Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, Rome, Italy
- Clinical Pathways and Outcome Evaluation Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Anna Benedetta Del Signore
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Global Medical Department-Primary Care Unit, Angelini Pharma, Rome, Italy
| | - Riccardo Maviglia
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Maria Grazia Bocci
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Alessandro Olivi
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Francesco Franceschi
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Andrea Urbani
- Catholic University of Sacred Heart, Rome, Italy
- Department of Laboratory and Infectious Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Paolo Calabresi
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Vincenzo Valentini
- Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Massimo Antonelli
- Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Catholic University of Sacred Heart, Rome, Italy
| | - Giovanni Frisullo
- Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
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