Effect of a Continuous Peripheral Nerve Block on the Inflammatory Response in Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Experimental nerve block in animals inhibits the inflammatory response. The purpose of this study was to determine to what extent a 48-hour local anesthetic block of all afferent and efferent nerve fibers of the knee area has an impact on postoperative inflammatory response. METHODS: Twelve patients scheduled for primary total knee arthroplasty received spinal anesthesia, and then were randomly allocated to either patient-controlled analgesia with morphine (n = 6) or a combination of continuous lumbar plexus and sciatic nerve blocks (continuous peripheral nerve block; CPNB) with ropivacaine 0.2% for 48 hours. Blood samples were collected before surgery and at 3, 8, 24, and 48 hours after surgical incision to measure plasma glucose, serum insulin and cortisol, C-reactive protein, interleukin-6, and leukocyte count. Pain visual analog scale at rest and on knee flexion were recorded and complications classified. RESULTS: Visual analog scale was lower in the CPNB group at rest and on knee flexion on postoperative days 1 and 2 (P < .05). There were no differences in circulating levels of glucose, insulin, and cortisol. C-reactive protein and leukocyte count were lower in the CPNB group (P < .05). There was a positive correlation between the peak leukocyte count and the inflammatory markers (P < .03). Three patients in the patient-controlled analgesia group and one in the CPNB group had complications requiring conservative management. CONCLUSIONS: Continuous lumbar plexus and sciatic nerve blocks with ropivacaine contribute to the attenuation of the postoperative inflammatory response.
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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".