The Impact of Prefracture and Hip Fracture Characteristics on Mortality in Older Persons in Brazil
Bibliographic record
Abstract
BACKGROUND: Hip fractures in the elderly are common and associated with considerable mortality and disability. Although well known in industrialized countries, the factors associated with mortality after hip fractures are not reported frequently in developing countries and little is known regarding risk factors in Latin America. QUESTIONS/PURPOSE: We investigated the rate of 1-year mortality and prefracture and fracture characteristics associated with mortality after a hip fracture in elderly Brazilian patients in a large metropolitan area. METHODS: Two hundred forty-six persons 60 years and older admitted to four hospitals in Rio de Janeiro were included after experiencing fractures and were followed for 1 year. Data were collected on sociodemographic, health, and functional status; type of surgery; length of stay; and complications after surgery. Cox regression analyses were conducted to investigate factors associated with 1-year mortality after hip fracture. RESULTS: Of the 246 patients, 86 died (35%). Of those 86, 22 died in the hospital (25.6%) and 64 (74.4%) died after discharge. Functional status before fracture, older age, male gender, and higher surgical risk increased the risk of mortality, whereas the use of antibiotics and the use of physical therapy after surgery decreased the risk. CONCLUSIONS: Our mortality rate was higher than those reported from industrialized countries. The use of antibiotics and physical therapy are potentially modifiable factors to improve patients' survival after fracture in Brazil. LEVEL OF EVIDENCE: Level II, prognostic study. See the Guidelines for Authors for a complete description of the levels of evidence.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".