Periarticular Injection in Knee Arthroplasty Improves Quadriceps Function
Bibliographic record
Abstract
BACKGROUND: The postoperative analgesic potential of periarticular anesthetic infiltration (PAI) after TKA is unclear as are the complications of continuous femoral nerve block on quadriceps function. QUESTIONS/PURPOSES: We asked (1) whether PAI provides equal or improved postoperative pain control in comparison to a femoral nerve block in patients who have undergone TKA; and (2) if so, whether PAI improves early postoperative quadriceps control and facilitates rehabilitation. METHODS: We randomized 60 patients to receive either PAI or femoral nerve block. During the first 5 days after TKA, we compared narcotic consumption, pain control, quadriceps function, walking distance, knee ROM, capacity to perform a straight leg raise, and active knee extension. Medication-related side effects, complications, operating room time, and hospitalization duration were compared. RESULTS: Opioid consumption was lower in the PAI group during the first 8 postoperative hours (12.5 mg versus 18.7 mg morphine), as was reported pain at rest (1.7 versus 3.5 on a 10-point VAS). Thereafter, narcotic consumption and reported pain were similar up to 120 hours. More subjects in the femoral nerve block group experienced quadriceps motor block (37% versus 0% in the PAI group). On Days 1 to 3, subjects in the PAI group experienced better capacity to perform the straight leg raise, active knee extension, and had longer walking distances. CONCLUSIONS: PAI provided pain control equivalent to that of a femoral nerve block while avoiding a motor block and its negative functional impacts. The data suggest it should be considered an alternative to a femoral nerve block. LEVEL OF EVIDENCE: Level I, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".