Heart Failure Is a Risk Factor for Orthopedic Fracture
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is associated with factors that may contribute to accelerated bone loss and subsequent fractures. Whether it leads to an increased fracture risk is unknown. METHODS AND RESULTS: A population-based cohort of consecutive patients >/=65 years of age with cardiovascular disease presenting to all emergency rooms between 1998 and 2001 in Alberta, Canada (n=16294 patients), was used. The 2041 patients with a new diagnosis of HF were compared with a control group of 14 253 patients with non-HF cardiovascular diagnoses. The primary outcome was any orthopedic fracture requiring hospital admission in the year after the emergency room visit. Patients with HF had a median age of 78 years (interquartile range, 72 to 84 years), and 51.9% were female; control subjects had a median age of 73 years (interquartile range, 68 to 79 years), and 53.2% were female. In the first year after the emergency room visit, 4.6% of the HF cohort (n=93) and 1.0% of patients without HF (n=147) sustained an orthopedic fracture (P<0.001). Hip fractures occurred in 26 HF patients (1.3%) and 18 patients (0.1%) without HF (P<0.001). After multivariable adjustment, HF was independently associated with a greater risk of any orthopedic fracture (adjusted odds ratio, 4.0; 95% CI, 2.9 to 5.3) or hip fracture (adjusted odds ratio, 6.3; 95% CI, 3.4 to 11.8). CONCLUSIONS: HF is associated with an increased risk of subsequent orthopedic fracture, particularly hip fracture. This suggests that screening for and treatment of osteoporosis to reduce fracture risk need to be considered in those with HF.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".