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Updated: Jul 16, 2026

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Frailty as a prognostic indicator of outcomes after brain tumor surgery: a meta-analysis
Mingfeng Zhao1, Wenzhu Yang1, Zhiguo Han1
1Department of Neurosurgery, First Hospital of Jilin University, Changchun, Jilin, China.
Background:
Frailty, a state of diminished physiological reserve, may influence outcomes after brain tumor surgery. This meta-analysis synthesized evidence on the association between preoperative frailty and postoperative outcomes in patients with brain tumors.
Methods:
We systematically searched Cochrane Library, Embase, Google Scholar, OVID, and PubMed from inception to December 2025. Studies using validated multi-domain frailty instruments in patients undergoing brain tumor surgery were eligible. Two reviewers independently screened studies, extracted data, and assessed risk of bias using QUIPS. Pooled odds ratios (ORs) or mean differences (MDs) with 95% confidence intervals (CIs) were calculated using random-effects models. Heterogeneity was quantified using I2 and explored through subgroup analyses. GRADE assessed certainty of evidence.
Results:
Seventeen studies comprising 68,954 patients (19,659 frail, 49,295 nonfrail) were included. Frailty was associated with higher mortality (OR 1.77; 95% CI 1.14-2.76), complications (OR 2.10; 95% CI 1.60-2.76), non-routine discharge (OR 2.09; 95% CI 1.39-3.14), and longer hospital stay (MD 4.60 days; 95% CI 0.64-8.56). No association was found with readmission (OR 1.01; 95% CI 0.80-1.28). Extreme heterogeneity (I2 90-99%) limits interpretability of pooled estimates. Subgroup analyses showed variation in effect sizes, but residual heterogeneity remained unexplained. GRADE certainty was low to very low for all outcomes except readmission (moderate).
Conclusions:
Frailty is consistently associated with adverse outcomes after brain tumor surgery, but extreme heterogeneity precludes precise quantitative risk prediction. Subgroup analyses attempting to compare slow-growing versus aggressive tumor types predominantly revealed an absence of stratified reporting in the primary literature.

