The Association of Frailty With Adverse Outcomes After Multisystem Trauma: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Frailty strongly predicts adverse outcomes in a variety of clinical settings; however, frailty-related trauma outcomes have not been systematically reviewed and quantitatively synthesized. Our objective was to systematically review and meta-analyze the association between frailty and outcomes (mortality-primary; complications, health resource use, and patient experience-secondary) after multisystem trauma. METHODS: After registration (CRD42018104116), we applied a peer-reviewed search strategy to MEDLINE, EMBASE, and Comprehensive Index to Nursing and Allied Health Literature (CINAHL) from inception to May 22, 2019, to identify studies that described: (1) multisystem trauma; (2) participants ≥18 years of age; (3) explicit frailty instrument application; and (4) relevant outcomes. Excluded studies included those that: (1) lacked a comparator group; (2) reported isolated injuries; and (3) reported mixed trauma and nontrauma populations. Criteria were applied independently, in duplicate to title/abstract and full-text articles. Risk of bias was assessed using the Risk of Bias in Nonrandomized Studies-of Interventions (ROBINS-I) tool. Effect measures (adjusted for prespecified confounders) were pooled using random-effects models; otherwise, narrative synthesis was used. RESULTS: Sixteen studies were included that represented 5198 participants; 9.9% of people with frailty died compared to 4.2% of people without frailty. Frailty was associated with increased mortality (adjusted odds ratio [OR], 1.53; 95% confidence interval [CI], 1.37-1.71), complications (adjusted OR, 2.32; 95% CI, 1.72-3.15), and adverse discharge (adjusted OR, 1.78; 95% CI, 1.29-2.45). Patient function, experience, and resource use outcomes were rarely reported. CONCLUSIONS: The presence of frailty is significantly associated with mortality, complications, and adverse discharge disposition after multisystem trauma. This provides important prognostic information to inform discussions with patients and families and highlights the need for trauma system optimization to meet the complex needs of older patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, not a consensus.
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".