دورية أكاديمية
A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.
العنوان: | A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model. |
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المؤلفون: | Mercurio G; Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Gottardelli B; Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy., Lenkowicz J; Gemelli Generator RWD, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Patarnello S; Gemelli Generator RWD, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Bellavia S; 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., Scala I; 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., Rizzo P; 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., de Belvis AG; 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., Del Signore AB; 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., Maviglia R; Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Bocci MG; Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Olivi A; 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., Franceschi F; Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.; Catholic University of Sacred Heart, Rome, Italy., Urbani A; Catholic University of Sacred Heart, Rome, Italy.; Department of Laboratory and Infectious Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy., Calabresi P; 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., Valentini V; Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Università Cattolica del Sacro Cuore, Rome, Italy.; Catholic University of Sacred Heart, Rome, Italy., Antonelli M; Department of Emergency Science, Anesthesiology and Intensive Care, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.; Catholic University of Sacred Heart, Rome, Italy., Frisullo G; Department of Aging, Neurological, Orthopedic and Head and Neck Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. |
المصدر: | European journal of neurology [Eur J Neurol] 2024 Mar; Vol. 31 (3), pp. e16153. Date of Electronic Publication: 2023 Nov 28. |
نوع المنشور: | Observational Study; Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Wiley Country of Publication: England NLM ID: 9506311 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1468-1331 (Electronic) Linking ISSN: 13515101 NLM ISO Abbreviation: Eur J Neurol Subsets: MEDLINE |
أسماء مطبوعة: | Publication: <2014- > : Oxford : Wiley Original Publication: Oxford ; New York : Rapid Communications, [1994- |
مواضيع طبية MeSH: | Stroke*/epidemiology , Stroke*/therapy, Humans ; Retrospective Studies ; Risk Factors ; Hospitals ; Machine Learning |
مستخلص: | 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. (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.) |
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معلومات مُعتمدة: | The Italian Ministry for University and Research (MUR) under the Program PON |
فهرسة مساهمة: | Keywords: brain hemorrhage; discharge pathways; re-admission; risk score; stroke |
تواريخ الأحداث: | Date Created: 20231128 Date Completed: 20240209 Latest Revision: 20240727 |
رمز التحديث: | 20240727 |
مُعرف محوري في PubMed: | PMC11235732 |
DOI: | 10.1111/ene.16153 |
PMID: | 38015472 |
قاعدة البيانات: | MEDLINE |
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