Examining the Role of Perioperative Nerve Blocks in Hip Arthroscopy: A Systematic Review
Bibliographic record
Abstract
PURPOSE: This systematic review examined the efficacy of perioperative nerve blocks for pain control after hip arthroscopy. METHODS: The databases Embase, PubMed, and Medline were searched on June 2, 2015, for English-language studies that reported on the use of perioperative nerve blocks for hip arthroscopy. The studies were systematically screened and data abstracted in duplicate. RESULTS: Nine eligible studies were included in this review (2 case reports, 2 case series, 3 non-randomized comparative studies, and 2 randomized controlled trials). In total, 534 patients (534 hips), with a mean age of 37.2 years, who underwent hip arthroscopy procedures were administered nerve blocks for pain management. Specifically, femoral (2 studies), fascia iliaca (2 studies), lumbar plexus (3 studies), and L1 and L2 paravertebral (2 studies) nerve blocks were used. All studies reported acceptable pain scores after the use of nerve blocks, and 4 studies showed significantly lower postoperative pain scores acutely with the use of nerve blocks over general anesthesia alone. The use of nerve blocks also resulted in a decrease in opioid consumption in 4 studies and provided a higher level of patient satisfaction in 2 studies. No serious acute complications were reported in any study, and long-term complications from lumbar plexus blocks, such as local anesthetic system toxicity (0.9%) and long-term neuropathy (2.8%), were low in incidence. CONCLUSIONS: The use of perioperative nerve blocks provides effective pain management after hip arthroscopy and may be more effective in decreasing acute postoperative pain and supplemental opioid consumption than other analgesic techniques. LEVEL OF EVIDENCE: Level IV, systematic review of Level I to Level IV studies.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".