Identifying Key Factors Influencing Hospital Stay After Spine Surgery: A Comprehensive Predictive Model.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 40168554.
- Also identified by DOI 10.1177/21925682251331451 and PMC identifier 11962937.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.