The effect of numbness on outcome from total knee replacement
Bibliographic record
Abstract
INTRODUCTION Some patients report continuing pain and functional limitations after total knee replacement (TKR). While numbness around the TKR scar is common, the impact of numbness is less clear. One particular activity that could be influenced by numbness is kneeling. The aim of this study was to explore the impact of numbness around TKR scars on health related quality of life and kneeling ability. METHODS Fifty-six patients were recruited one year after primary TKR. Sensation around the knee was assessed through patient self-reporting, monofilament testing and vibration, and patients’ distress was measured on a visual analogue scale. Patient reported outcome measures (PROMs) including the Western Ontario and McMaster Universities (WOMAC ® ) index, the Knee injury and Osteoarthritis Outcome Score (KOOS), the painDETECT ® (Pfizer, Berlin, Germany) questionnaire and the EQ-5D™ (EuroQol, Rotterdam, Netherlands) questionnaire were used. Participants were also asked about kneeling ability. RESULTS While 68% of patients reported numbness around their TKR scar, there was no statistically significant correlation between numbness and distress at numbness (self-report: 0.23, p=0.08; monofilament: 0.15, p=0.27). Furthermore, numbness did not correlate significantly with joint specific PROMs (WOMAC ® : 0.21, p=0.13; KOOS: 0.18, p=0.19). However, difficulty with kneeling did correlate with both self-reported numbness (0.36, p=0.020) and worse PROM scores (WOMAC ® pain subscale: 0.62, p<0.001; KOOS: 0.64, p<0.001). CONCLUSIONS Numbness after knee replacement is common but is not associated with worse patient reported outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".