Effect of Obesity on Pain and Functional Recovery Following Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: While obesity may be a risk factor for complications following total knee arthroplasty, data remain sparse on the impact of the degree of obesity on patient-reported outcomes following this procedure. Our objective was to determine the extent to which obesity level affects the trajectory of recovery as well as patient-reported pain, function, and satisfaction with surgery following total knee arthroplasty. METHODS: We followed a cohort of patients who underwent total knee arthroplasty at 1 of 4 medical centers. Patients were ≥40 years of age with a primary diagnosis of osteoarthritis. We stratified patients into 5 groups according to the World Health Organization classification of body mass index (BMI). We assessed the association between BMI group and pain and function over the time intervals of 0 to 3, 3 to 6, and 6 to 24 months using a piecewise linear model. We also assessed the association between BMI group and patient-reported outcomes at 24 months. Multivariable models adjusted for age, sex, race, diabetes, musculoskeletal functional limitations index, pain medication use, and study site. RESULTS: Of the 633 participants included in our analysis, 19% were normal weight (BMI of <25 kg/m), 32% were overweight (BMI of 25 to 29.9 kg/m), 27% were class-I obese (BMI of 30 to 34.9 kg/m), 12% were class-II obese (BMI of 35 to 39.9 kg/m), and 9% were class-III obese (BMI of ≥40 kg/m). Study participants with a higher BMI had worse preoperative WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) pain and function scores and had greater improvement from baseline to 3 months. The mean change in pain and function from 3 to 6 and from 6 to 24 months was similar across all BMI groups. At 24 months, participants in all BMI groups had similar levels of pain, function, and satisfaction. CONCLUSIONS: Because of the differential trajectory of recovery in the first 3 months following total knee arthroplasty, the participants in the higher BMI groups were able to attain absolute pain and function scores similar to those in the nonobese and class-I obese groups. These data can help surgeons discuss expectations of pain relief and functional improvement with total knee arthroplasty candidates with higher BMI. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".