Pain Management for Nonsyndromic Craniosynostosis: Adequate Analgesia in a Pediatric Cohort?
Bibliographic record
Abstract
BACKGROUND: Postoperative pain following open craniosynostosis repair has not been studied extensively and is sometimes thought to be inconsequential. The purpose of this study was to assess postoperative pain in this pediatric population. METHODS: We performed a retrospective chart review of patients (n = 54) undergoing primary open craniosynostosis repair from 2010 to 2016. Demographics, length of stay (LOS), pain scores, emesis events, and perioperative analgesics were reviewed. Multivariable regression models were designed to assess for independent predictors of LOS and emesis. RESULTS: A high proportion had moderate to severe pain on postoperative day 0 (56.5%) and day 1 (60.9%). Opioid administered in postoperative period was 1.40 mg/kg/d in morphine milligram equivalent (MME) (±1.07 mg/kg/d MME). Majority of patients transitioned to enteral opioids on postoperative day 1 (24.5%) or day 2 (49.1%). Ketorolac was administered to 11.1% (n = 6). Emesis was documented in 50% of patients. LOS revealed a positive association with age (P = 0.006), weight (P = 0.009), and day of transition to enteral opioids (P < 0.001); association with emesis was trending toward significance (P = 0.054). There was no association between overall LOS and amount of opioids administered postoperatively (P = 0.68). Postoperative emesis did not have any significant association with age, sex, weight, total amount of postoperative opioid administered, use of ketorolac, or intraoperative steroid use. CONCLUSION: Open craniosynostosis repair is associated with high levels of pain and low utilization of nonopioid analgesics. Strategies to improve pain, decrease emesis and LOS include implementation of multimodal analgesia period and avoidance of enteral medications in the first 24 hours after surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".