Long‐Term Mortality of Patients With Osteoarthritis After Joint Replacement: Prognostic Value of Preoperative and Postoperative Pain and Function
Bibliographic record
Abstract
OBJECTIVE: To investigate whether osteoarthritis (OA)-specific assessment values (i.e., Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]) and generic pain and function (visual analog scale, Hanover Functionality Status Questionnaire) measured before and 12 months after arthroplasty are associated with the risk of long-term mortality in a cohort of patients with advanced OA of the hip or knee. METHODS: The Ulm Osteoarthritis Study was a prospective cohort study of OA patients with unilateral total hip or knee replacement between January 1995 and December 1996. Correlation coefficients were calculated to describe the agreement between the different assessments. Mortality was assessed during the follow-up period (last update July 2019). Cox proportional regression models were used to estimate hazard ratios (HRs) for mortality after adjusting for covariates. RESULTS: Arthroplasty was accompanied by a clear reduction in pain and improved function throughout all assessments in the 706 included patients. The results of the adjusted Cox models showed no relationship between baseline and follow-up joint-specific WOMAC assessments and long-term mortality. However, an independent increased risk of mortality was found with generic function assessments. In the final adjusted model, the HR for the 12-month follow-up value was 1.79 (95% confidence interval 1.24-2.60) in the group with clinically relevant impairment versus the reference group. CONCLUSION: Poor function based on the generic assessment was associated with increased long-term mortality, suggesting that functional impairments in daily life activities may be more important for long-term survival than OA-specific impairments in this patient group.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".