Treating Pain With the Lidocaine Patch 5% After Total Knee Arthroplasty
Bibliographic record
Abstract
OBJECTIVE: To investigate the potential benefits of the lidocaine patch 5% for pain control during the postoperative period after a total knee arthroplasty (TKA). DESIGN/SETTING: A prospective cohort study in which we analyzed patients admitted to an inpatient rehabilitation unit after a TKA. PARTICIPANTS: Fifty-three consecutive patients who underwent a TKA and were admitted to an orthopedic rehabilitation unit. METHODS: Thirty-one patients received the lidocaine patch 5%, and 22 patients served as the control group. On the day of admission, the 24-item Western Ontario and McMaster Universities Arthritis Index (WOMAC) was used to evaluate each patient's pain and functional capacity before surgery. The Visual Analog Scale (VAS) was used to assess pain ratings every other day starting on rehabilitation day 1. The average end point of the study was rehabilitation day 11. MAIN OUTCOME MEASURES: The primary outcome measure was the change in VAS from day of admission. Secondary outcomes in the lidocaine patch 5% group consisted of length of use and a patient satisfaction survey. RESULTS: The lidocaine patch 5% and control group were demographically well matched. The average admission WOMAC score was 49.3 and 57.1 for the lidocaine patch 5% and control groups, respectively. The average length of stay was 13.2 ± 5.1 days for the lidocaine patch 5% group and 12.4 ± 3.7 days for the control group. A statistically significant difference in VAS was found on day 3 (P = .05) between the 2 groups, with the control group demonstrating better pain relief. However, both groups reported similar pain improvements by the end of their hospital stay. Of the 31 patients receiving lidocaine patch 5%, 94% of the patients reported satisfaction and attributed pain relief to its use. CONCLUSIONS: Overall, the concurrent use of lidocaine patch 5% in treating the postoperative pain of patients after TKA does not provide significant additional pain relief compared with control subjects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".