Incidence and associated factors of elderly mortality following hip fracture in Brazil: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Hip fractures are an important health problem worldwide, and several factors are associated with the mortality. This study aimed to investigate the factors associated with hip fractures in the elderly, based on studies on the population residing in Brazil, and the relationship of fractures with mortality. Method Prospective and retrospective primary observational studies including hospitalized men and/or women aged 60 or older presenting hip fracture due to bone fragility were selected on the Databases. Independent researchers conducted the study selection process and data extraction. A meta-analysis was performed to determine the hospital mortality rate at 90 days, six months, and one year. The Newcastle-Ottawa scale (NOS) was used to assess the quality of the included studies, and the meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Result Twenty-five studies totalizing 3,949 patients were included in the systematic review. The population was mainly composed of women (2,680/67.86%). Most patients were in the age group of 70 to 80 years old. Meta-analysis findings: 1) hospital mortality (19 studies, n = 3,175), 10.22% (95% CI 7.27–14.17%; I 2 88%); 2) 90-day mortality (3 studies, n = 543), 9.74% (95% CI 3.44–24.62%; I 2 90%); 3) six-month mortality (3 studies, n = 205), 24.78% (95% CI 17.07–34.51%; I 2 51%); 4) one-year mortality (13 studies, n = 2,790), 21.88% (95% CI 17.5–26.99%; I 2 88%). The factors most related to mortality in the studies were: 1) demographic: Older age, male sex; 2) Attributed to clinical conditions: high scoring in preoperative risk scores, comorbidities, neurological/cognitive disorders, functional status; and 3) hospital factors: preoperative period and infections. Conclusion This review identified variables, including functional status and cognitive changes, related to hip fracture mortality. Knowing these predictors allows for early intervention and planning to adapt health systems to the growing demands of the elderly population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.031 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".