Femoral Nerve Block Improves Analgesia Outcomes after Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Femoral nerve blockade (FNB) is a common method of analgesia for postoperative pain control after total knee arthroplasty. We conducted a systematic review to compare the analgesia outcomes in randomized controlled trials that compared FNB (with and without sciatic nerve block) with epidural and patient-controlled analgesia (PCA). METHODS: We identified 23 randomized controlled trials that compared FNB with PCA or epidural analgesia. These studies included 1,016 patients, 665 with FNB, 161 with epidural, and 190 with PCA alone. RESULTS: All 10 studies of single-shot FNB (SSFNB) used concurrent PCA opioids. SSFNB was found to reduce PCA morphine consumption at 24 h (-19.9 mg, 95% credible interval [CrI]: -35.2 to -4.6) and 48 h (-38.0 mg, 95% CrI: -56.0 to -19.7), pain scores with activity (but not at rest) at 24 and 48 h (-1.8 visual analog pain scale, 95% CrI: -3.3 to -0.02 at 24 h; -1.5 visual analog pain scale, 95% CrI: -2.9 to -0.02 at 48 h) and reduce the incidence of nausea (0.37 odds ratio, 95% CrI: 0.1 to 0.9) compared with PCA alone. SSFNB had similar morphine consumption and pain scores compared with SSFNB plus sciatic nerve block, and SSFNB plus continuous FNB. CONCLUSIONS: SSFNB or continuous FNB (plus PCA) was found to be superior to PCA alone for postoperative analgesia for patients having total knee arthroplasty. The impact of adding a sciatic block or continuous FNB to a SSFNB needs to be studied further.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".