Predictors and Prevalence of Persistent Pain after Total Knee Arthroplasty in One-Year Follow-up
Bibliographic record
Abstract
Background: Total knee arthroplasty (TKA) is one of the most common surgeries performed to reduce pain and disability in knee arthritis. Comprehension of the etiology and prevalence of persistent postoperative knee pain can help reduce this pain and identify the predictive factors leading to it. This study aimed to investigate the predictive factors and the prevalence of persistent pain after total knee arthroplasty in one-year follow-up. Materials and Methods: This was a prospective cohort study. Demographic data including age, sex, body mass index (BMI), hospital anxiety and depression scale (HADS), and comorbidities were collected. In 242 patients, preoperative and postoperative Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores were measured before and immediately after surgery and in 3-, 6-, and 12-month intervals during follow-up. Loosening of the prosthesis was also investigated by radiographic imaging in every postoperative visit. Result: = 22) at 6 and 12 months lower preoperative WOMAC (odd's ratio:2.8), loosening of the prosthesis (odd's ratio:1.9), higher HADS (odd's ratio:2.1) were main predictors for PPP in TKA patients as in rheumatoid arthritis (odd's ratio:1.2). Conclusion: Loosening of the prosthesis and higher preoperative WOMAC scores are key factors in persistent post-TKA pain. Depression and anxiety are more popular among patients with more pain after TKA. RA is more prevalent in patients with PPP after TKA.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".