Health-related quality of life, rehabilitation and mortality in a nursing home population.
Bibliographic record
Abstract
BACKGROUND: Health-related quality of life (HRQOL) in nursing home residents is generally low. The purpose of this study was to investigate the associations between HRQOL and two clinically relevant outcome measures, all-cause mortality and successful rehabilitation, in a nursing home population. METHODS: In an observational prospective cohort study in a nursing home population, HRQOL was assessed with the RAND-36. A total of 184 patients were included, 159 (86%) completed the RAND-36 and were included in the study. A Cox proportional hazard model was used to investigate the independent association between HRQOL, rehabilitation and mortality with adjustment for confounders. Risk prediction capabilities were assessed with Harrell's C statistics and the proportion of explained variance (R2). RESULTS: The median age (interquartile range) was 79 (75-85) years. The health dimensions vitality (HR 0.88 (95% CI 0.77-0.99)) and mental health (HR 0.86 (95% CI 0.75-0.98)) were inversely associated and role functioningphysical (HR 1.08 (95%CI 1.02-1.15)) was positively associated with mortality. The Harrell's C value and the R2 were ≤ 0.02 and ≤ 0.03 higher in the adjusted models with the dimensions role functioning- physical, mental health or vitality compared with the models without these dimensions. None of the health dimensions or summary scales were related to successful rehabilitation. CONCLUSION: HRQOL was significantly associated with mortality for three dimensions, but partly in opposite directions. Additional value of HRQOL in mortality prediction is very limited. There were no independent associations between HRQOL and successful rehabilitation. Although HRQOL is an important outcome, this study did not provide evidence for an association between HRQOL and successful rehabilitation.
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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 | 0.003 |
| 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 | 0.000 | 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".