The Effect of Age on Pain, Function, and Quality of Life After Total Hip and Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: As utilization rates for total joint arthroplasty increase, there is a hesitancy to perform this surgery on very old patients. The objective of this prospective study was to compare pain, functional, and health-related quality-of-life outcomes after total hip and total knee arthroplasty in an older patient group (> or =80 years) and a representative younger patient group (55-79 years). METHODS: In an inception community-based cohort within a Canadian health care system, 454 patients who received primary total hip arthroplasty (n = 197) or total knee arthroplasty (n = 257) were evaluated within a month prior to surgery and 6 months postoperatively. Pain, function, and health-related quality of life were evaluated with the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index and the 36-Item Short-Form Health Survey (SF-36). RESULTS: There were no age-related differences in joint pain, function, or quality-of-life measures preoperatively or 6 months postoperatively. Furthermore, after adjusting for potential confounding effects, age was not a significant determinant of pain or function. Although those in the older and younger groups had comparable numbers of comorbid conditions and complications, those in the older group were more likely to be transferred to a rehabilitation facility than younger patients. Regardless of age, patients did not achieve comparable overall physical health when matched with the general population for age and sex. CONCLUSIONS: With increasing life expectancy and elective surgery improving quality of life, age alone is not a factor that affects the outcome of joint arthroplasty and should not be a limiting factor when considering who should receive this surgery.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".