The Effect of Sensory Deficit After Total Knee Arthroplasty on Patient Satisfaction and Kneeling Ability
Bibliographic record
Abstract
BACKGROUND: Skin numbness after total knee arthroplasty is a common complication. The incidence in the literature is variable from 27% to 100%. However, there is conflicting evidence about the consequences of this complication. The purpose of this study was to evaluate if postoperative numbness influenced patient satisfaction or kneeling ability. METHODS: We recruited patients who underwent a total knee arthroplasty for osteoarthritis one to 5 years before the study. Sensation was measured using a Semmes-Weinstein, 10-gram monofilament. Measurements were taken in several zones around the incision, and overall sensory status was classified as full numbness, partial numbness, and no numbness. Patients completed a questionnaire evaluating their subjective numbness, overall satisfaction, and kneeling ability. We evaluated the effect of numbness on satisfaction and function. RESULTS: A total of 96 patients were enrolled. Thirty-four patients were classified as no sensory deficit, 29 as partial deficit, and 33 as full deficit. There were no differences in demographics. Out of all the patients that were found to have a sensory deficit, 54.8% of them did not report any subjective numbness. Average patient-reported satisfaction scores were 8.76/10, 8.97/10, and 8.48/10 for no numbness, partial numbness, and full numbness, respectively. Eleven out of 96 patients noted an inability to kneel. There was no statistical difference for satisfaction scores or kneeling ability between the groups. CONCLUSION: Sensory deficit after total knee arthroplasty is a frequently reported complication. However, the majority of the patients do not report subjective sensory deficits. Postoperative numbness does not appear to affect patient satisfaction or kneeling ability.
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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 | 0.005 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".