Neurochirurgie. 2026 Jan 30;72(2):101779. doi: 10.1016/j.neuchi.2026.101779. Online ahead of print.
ABSTRACT
BACKGROUND AND OBJECTIVES: Unplanned 30-day readmission after elective treatment of unruptured intracranial aneurysms (UCAs) represents a significant clinical and economic burden. Reported readmission rates vary significantly, and the predictors of early rehospitalization remain elusive. This meta-analysis evaluates the prevalence of 30-day unplanned readmission and identifies predictors associated with increased readmission risk.
METHODS: Following PRISMA guidelines, databases were searched through October 2025, reporting 30-day unplanned readmission after microsurgical clipping or endovascular treatment of UCAs. Random-effects models were applied. Risk ratios (RR) were used for dichotomous variables, mean differences (MD) for continuous variables, and pooled prevalence estimates were produced using a generalized linear mixed model.
RESULTS: Our analysis included 70,463 patients treated for UCAs across seven studies; 3,655 experienced a 30-day unplanned readmission. The prevalence of readmission was 4.8% (95% CI, 3.0-7.5%), and rates did not differ significantly between microsurgical and endovascular treatment (5.9% vs 3.4%; P = 0.26). Several comorbidities were significantly associated with increased readmission risk, including hypertension, hyperlipidemia, diabetes mellitus, and anticoagulant use. Length of index hospital stay was also associated with higher readmission risk. Age, sex, smoking status, and antiplatelet use were not significant predictors.
CONCLUSION: This meta-analysis identified a 4.8% prevalence of unplanned 30-day readmission following elective treatment of UCAs. These findings suggest the need for careful risk stratification and preoperative comorbidity management for patients undergoing UCA repair, particularly among those with cardiometabolic comorbidities and complicated index hospitalizations. Implementing these strategies in high-risk patients may help reduce preventable readmissions and improve healthcare resource utilization.
PMID:41619421 | DOI:10.1016/j.neuchi.2026.101779