Weight changes after total knee arthroplasty in Chinese patients: a matched cohort study regarding predictors and outcomes
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to compare 2-year BMI changes between patients undergoing simultaneous bilateral total knee arthroplasty (TKA), staged bilateral TKA, and unilateral TKA. We also sought to determine the predictors of weight change and whether clinically meaningful weight changes affected outcomes. PATIENTS AND METHODS: This retrospective, single-institution study included 202 Chinese patients who received simultaneously bilateral TKA, staged bilateral TKA, or unilateral TKA from 2008 to 2015. There were 49 simultaneous bilateral TKAs, 52 staged bilateral TKAs, and a matched 101 unilateral TKAs. RESULTS: 66.8% (135/202) of patients lost weight after TKA surgery. However, 20.7% (42/202) of patients experienced clinically meaningful weight loss (a BMI decrease of more than 5%). Paired t test showed that 2-year BMI was significantly lower than preoperative BMI (p < 0.001). Weight loss was significantly different between the surgical strategy (p < 0.001). Preoperative BMI and age were predictive of clinically significant weight loss or gain (p < 0.05). Multiple linear regression showed that post-operative weight loss was associated with better Western Ontario and McMaster Universities Osteoarthritis Index and SF-36 scores (p < 0.001). CONCLUSION: Patients after TKA experience weight loss. Age and preoperative BMI predict clinically meaningful weight change. Simultaneous bilateral TKA is associated with higher likelihood of weight loss. Clinically meaningful weight loss experiences better patient-reported outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".