Prognostic Value of Frailty for Outcome Following Traumatic Brain Injury: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Frailty is a known predictor of negative health outcomes. The role of frailty in predicting outcomes after traumatic brain injury (TBI), however, is unclear. This systematic review aimed to evaluate the association between frailty and adverse outcomes in patients with TBI. We identified relevant articles that investigated the relationship between frailty and outcomes in patients with TBI by searching PubMed/MEDLINE, Web of Science, Scopus, and EMBASE from inception until 23 March 2023. To evaluate the risk of bias in the included studies, we utilized the Newcastle-Ottawa Scale (NOS). In addition, quantitative synthesis and meta-analyses were performed. We identified 12 studies that met our inclusion criteria; three were prospective. Of included studies, eight had low risk, three had moderate risk, and one had high risk of bias. Frailty was significantly associated with death in five studies, with an increased risk of in-hospital death and complications observed in frail patients. Frailty was associated with longer hospital stays and unfavorable outcome measured by the Extended Glasgow Outcome Scale (GOSE) in four studies. The meta-analysis found that higher frailty significantly increased the odds of non-routine discharge and unfavorable outcome as measured by GOSE scores of 4 or lower. The pooled odds ratio (OR) for non-routine discharge, was 1.80, with a 95% confidence interval (CI) of 1.15-2.84; and for unfavorable outcome, it was 1.91, with a 95% CI of 1.09-3.36. The analysis, however, did not find a significant predictive role for frailty on death (30-day or in-hospital death). The OR for higher frailty and death was 1.42 with a 95% CI of 0.92-2.19. Frailty should be considered in the evaluation of patients with TBI to identify those who may be at increased risk of negative outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.023 | 0.014 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".