Effectiveness and Safety of Intrathecal Morphine for Pediatric Patients Undergoing Scoliosis Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Adolescent idiopathic scoliosis (AIS) often necessitates spinal fusion surgery in pediatric patients, posing significant challenges in postoperative pain management. Standard care involves the administration of intravenous opioids perioperatively, often requiring high doses to achieve adequate analgesia following an operation. This increases the risk of adverse events, may delay recovery and prolong hospital stay, and increases the likelihood of future abuse and dependence. In this systematic review and meta-analysis, we assess the safety and effectiveness of intrathecal morphine (ITM) in pediatric patients undergoing posterior spinal fusion. Ovid Embase and MEDLINE were searched in October 2023 for articles that directly compared ITM use with standard pain management approaches for pediatric patients undergoing posterior spinal fusion. Our primary outcome was postoperative pain scores. Secondary outcomes included opioid usage details, adverse events, and blood loss. Of the 384 unique studies identified, nine studies (one randomized control trial, one prospective review, and seven retrospective reviews) met the inclusion criteria. The total number of patients within the ITM and control groups were 1384 and 676, respectively. Meta-analysis revealed significantly lower pain scores in the ITM group (standardized mean difference (SMD): -1.30 (-2.29, -0.31); p = 0.01). Similarly, ITM patients had significantly lower opioid usage, both intraoperatively (mean difference (MD): -0.71 mg/kg (-0.99, -0.44); p < 0.00001) as well as postoperatively (SMD: -2.10 (-3.48, -0.73); p = 0.003), and significantly lower blood loss (MD: -0.88 L (-1.34, -0.43); p = 0.0001). The occurrence of adverse events was similar across both groups. Our analysis of the available data demonstrates that a low to moderate dose of ITM is a safe and effective adjunct to improve standard postoperative care without increasing the risk of respiratory depression. When compared to control, ITM patients had superior analgesia while using fewer opioids had significantly reduced intraoperative blood loss when ITM was administered before spinal fusion, and had a similar complication profile. While further studies are warranted to establish optimal dosing, these findings underscore the potential of ITM as a valuable addition to multimodal pain management.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".