Dual Tunneled Epidural Wound Catheters for Postoperative Analgesia Following Posterior Spinal Fusion
Bibliographic record
Abstract
Pain management following posterior spinal fusion (PSF) in pediatric patients can present significant challenges for clinicians. Opioids continue as the primary modality for managing postoperative pain in these patients, despite well-known concerns regarding their adverse effect profile such as the risk of dependence or abuse. Therefore, there has been increased focus on multimodal analgesic approaches that incorporate non-opioid medications, non-pharmacologic techniques, and regional anesthesia. Commonly used non-opioid adjuncts include non-steroidal anti-inflammatory drugs, acetaminophen, gabapentin, ketamine, and intravenous lidocaine. Because of ongoing controversy and insufficient evidence regarding different analgesic strategies, no definitive optimum regimen has been established. We present a 14-year-old adolescent female patient with neuromuscular scoliosis scheduled for PSF. The anesthetic plan involved a unique combination of total intravenous anesthesia (TIVA) and the placement of dual epidural catheters by the orthopedic surgeon for postoperative analgesia. The basic tenets of perioperative pain management for PSF are presented, perioperative concerns are discussed, and previous reports of regional anesthesia as an adjunct to general anesthesia in pediatric patients with scoliosis are reviewed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".