Francesco Langella, Francesca Barile, Pablo Bellosta-Lòpez, Federico Fusini, Domenico Compagnone, Daniele Vanni, Marco Damilano, Pedro Berjano
{"title":"Identifying Key Factors Influencing Hospital Stay After Spine Surgery: A Comprehensive Predictive Model.","authors":"Francesco Langella, Francesca Barile, Pablo Bellosta-Lòpez, Federico Fusini, Domenico Compagnone, Daniele Vanni, Marco Damilano, Pedro Berjano","doi":"10.1177/21925682251331451","DOIUrl":null,"url":null,"abstract":"<p><p>Study DesignRetrospective Cohort Study.ObjectivesTo develop and validate a multivariable predictive model for length of hospital stay (LOS) following spine surgery, incorporating sociodemographic characteristics, medical data, and self-reported patient outcomes.MethodsA retrospective analysis of 4583 patients from a spine surgery registry was conduct-ed. Predictors included age, sex, BMI, ASA score, surgical complexity, and patient-reported outcomes. Binary logistic regression was used to model LOS (<3 days vs ≥3 days).ResultsLower age, active work status, lower ASA scores, and specific surgical procedures were associated with shorter LOS. The model demonstrated good accuracy and dis-criminative ability.ConclusionsSociodemographic, medical, and patient-reported outcomes are valuable predictors of LOS. These findings can help improve preoperative planning and resource allocation in spine surgery.</p>","PeriodicalId":12680,"journal":{"name":"Global Spine Journal","volume":" ","pages":"21925682251331451"},"PeriodicalIF":2.6000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11962937/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Spine Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/21925682251331451","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Study DesignRetrospective Cohort Study.ObjectivesTo develop and validate a multivariable predictive model for length of hospital stay (LOS) following spine surgery, incorporating sociodemographic characteristics, medical data, and self-reported patient outcomes.MethodsA retrospective analysis of 4583 patients from a spine surgery registry was conduct-ed. Predictors included age, sex, BMI, ASA score, surgical complexity, and patient-reported outcomes. Binary logistic regression was used to model LOS (<3 days vs ≥3 days).ResultsLower age, active work status, lower ASA scores, and specific surgical procedures were associated with shorter LOS. The model demonstrated good accuracy and dis-criminative ability.ConclusionsSociodemographic, medical, and patient-reported outcomes are valuable predictors of LOS. These findings can help improve preoperative planning and resource allocation in spine surgery.
期刊介绍：
Global Spine Journal (GSJ) is the official scientific publication of AOSpine. A peer-reviewed, open access journal, devoted to the study and treatment of spinal disorders, including diagnosis, operative and non-operative treatment options, surgical techniques, and emerging research and clinical developments.GSJ is indexed in PubMedCentral, SCOPUS, and Emerging Sources Citation Index (ESCI).
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
