The influence of sociodemographic, clinical and functional variables on the quality of life of elderly people with total hip arthroplasty.
Bibliographic record
Abstract
OBJECTIVES: To evaluate the health-related quality of life (HRQOL) of elderly people with total hip arthroplasty (THA) and to investigate the relationships and influences of the sociodemographic, clinical and functional variables of these subjects. METHODS: The HRQOL was evaluated by means of the Brazilian versions of the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36), a general instrument, and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), a specific instrument. Eighty-eight elderly people of both genders with primary unilateral THA were recruited. The data were subjected to descriptive analysss, univariate analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA) to investigate the influences of the variables studied in the dimensions of the SF-36 and WOMAC; and the Mann-Whitney and Kruskal-Wallis tests to compare instrument scores between the variables. RESULTS: There was a predominance of women in the study sample, and their mean age was 68.8 (+/- 7.4) years. Hip function, as assessed by the Harris Hip Score, had a significant influence on HRQOL from the perspective of both the general and the specific instruments. The use of accessories for locomotion, hip functions and satisfaction with the surgery were the main variables that demonstrated significant differences in the dimensions of the SF-36 and the WOMAC. CONCLUSIONS: Investments in functional and rehabilitation programs aimed towards the peculiarities of elderly people with THA can benefit this 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".