Prospective evaluation of preferences and quality of life in women with hip fractures.
Bibliographic record
Abstract
OBJECTIVE: Hip fractures are a major cause of morbidity for older women, which result in impaired health related quality of life (HRQOL). Few studies have prospectively evaluated the effect of hip fractures in women on HRQOL with different health state preference measures. We compared how 4 different preference measures change in women post-hip fracture and evaluated the responsiveness of the preference measures. We also compared HRQOL in women with recent hip fractures to a control sample at baseline and to normative Canadian data at followup. METHODS: Health status measures [the Medical Outcomes Study Short Form-36 (SF-36)] and preferences (direct and indirect) of women over age 50 years with hip fractures were measured at baseline and at 3 and 9 months. Baseline preferences [Health Utilities Index (HUI), Feeling Thermometer, Standard Gamble, and SF-36] were obtained from women without hip fractures for comparison. Independent sample t tests were used to compare baseline scores of fracture and nonfracture controls. Correlations between preference and health status measures were assessed and repeated measures ANOVA was used to assess change in health status and preferences over time. RESULTS: Health status and preference measures were lower in women with hip fractures in comparison to nonfracture controls. After 9 months, the SF-36, HUI, Feeling Thermometer, and SF-6D scores improved significantly. Values for the SF-36 remained lower than an age-matched normative sample. The HUI and SF-6D were sensitive to change over time, but the Standard Gamble was not. CONCLUSION: HRQOL and preference measures improve over time in women with recent hip fractures, with the majority of the change occurring in the initial 3 months. Our results suggest that the HUI and SF-6D are valid measures to assess change over time post-hip fracture.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".