Persistent pain after joint replacement: Prevalence, sensory qualities, and postoperative determinants
Bibliographic record
Abstract
Persistent postsurgical pain is a prevalent but underacknowledged condition. The aim of this study was to assess the prevalence, sensory qualities, and postoperative determinants of persistent pain at 3 to 4years after total knee replacement (TKR) and total hip replacement (THR). Patients completed a questionnaire with included the Western Ontario and McMaster Universities Index of Osteoarthritis (WOMAC) Pain Scale, PainDetect Questionnaire, Short-Form McGill Pain Questionnaire, and questions about general health and socioeconomic status. A total of 632 TKR patients and 662 THR patients completed a questionnaire (response rate of 73%); 44% of TKR patients and 27% of THR patients reported experiencing persistent postsurgical pain of any severity, with 15% of TKR patients and 6% of THR patients reporting severe-extreme persistent pain. The persistent pain was most commonly described as aching, tender, and tiring, and only 6% of TKR patients and 1% of THR patients reported pain that was neuropathic in nature. Major depression and the number of pain problems elsewhere were found to be significant and independent postoperative determinants of persistent postsurgical pain. In conclusion, this study found that persistent postsurgical pain is common after joint replacement, although much of the pain is mild, infrequent, or an improvement on preoperative pain. The association between the number of pain problems elsewhere and the severity of persistent postsurgical pain suggests that patients with persistent postsurgical pain may have an underlying vulnerability to pain. A small percentage of patients have severe persistent pain after joint replacement, and this is associated with depression and the number of pain problems elsewhere.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".