Adverse Effects of Increased Body Mass Index and Weight on Survivorship of Total Knee Arthroplasty and Subsequent Outcomes of Revision TKA
Bibliographic record
Abstract
To investigate the effects of increased weight and body mass index (BMI) on total knee arthroplasty (TKA) survivorship and on functional outcomes and quality of life following revision TKA, a prospective cohort study of 291 consecutive revision TKA patients was performed. Average patient BMI was 32.3 +/- 7.7, and 57% of patients were obese (BMI > or = 30). The obese group was not significantly different from the nonobese group regarding reasons for prosthesis failure; however, they were more likely to experience certain comorbidities. Body mass index and weight were both significant predictors of survivorship of primary TKA (regression coefficient BMI = -1.852, P = .004; regression coefficient weight = -0.405, P = .000) in multivariate regression. At 6-month follow-up, improvement of Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) stiffness, WOMAC difficulty of function, and Knee Society Score (KSS) function scales at 6 months after revision TKA was significantly lower (at the 0.001 level, two tailed) in patients with higher BMI, weight, or both. In regression analysis, BMI was a significant predictor of Short Form-36, WOMAC difficulty of function, and KSS. Weight and BMI have deleterious effects on the longevity of primary TKA and functional and quality of life outcomes following revision TKA. These findings indicate a need for more effective management of these patients.
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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 | 0.001 |
| 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 | 0.001 |
| 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".