Opioid Prescription Patterns for Children Following Laparoscopic Appendectomy
Bibliographic record
Abstract
OBJECTIVE: To describe variability in and consequences of opioid prescriptions following pediatric laparoscopic appendectomy. SUMMARY BACKGROUND DATA: Postoperative opioid prescribing patterns may contribute to persistent opioid use in both adults and children. METHODS: We included children <18 years enrolled as dependents in the Military Health System Data Repository who underwent uncomplicated laparoscopic appendectomy (2006-2014). For the primary outcome of days of opioids prescribed, we evaluated associations with discharging service, standardized to the distribution of baseline covariates. Secondary outcomes included refill, Emergency Department (ED) visit for constipation, and ED visit for pain. RESULTS: Among 6732 children, 68% were prescribed opioids (range = 1-65 d, median = 4 d, IQR = 3-5 d). Patients discharged by general surgery services were prescribed 1.23 (95% CI = 1.06-1.42) excess days of opioids, compared with those discharged by pediatric surgery services. Risk of ED visit for constipation (n = 61, 1%) was increased with opioid prescription [1-3 d, risk ratio (RR) = 2.46, 95% CI = 1.31-5.78; 4-6 d, RR = 1.89, 95% CI = 0.83-4.67; 7-14 d, RR = 3.75, 95% CI = 1.38-9.44; >14 d, RR = 6.27, 95% CI = 1.23-19.68], compared with no opioid prescription. There was similar or increased risk of ED visit for pain (n = 319, 5%) with opioid prescription [1-3 d, RR = 1.00, 95% confidence interval (CI) = 0.74-1.32; 4-6 d, RR = 1.31, 95% CI = 0.99-1.73; 7-14 d, RR = 1.52, 95% CI = 1.00-2.18], compared with no opioid prescription. Likewise, need for refill (n = 157, 3%) was not associated with initial days of opioid prescribed (reference 1-3 d; 4-6 d, RR = 0.96, 95% CI = 0.68-1.35; 7-14 d, RR = 0.91, 95% CI = 0.49-1.46; and >14 d, RR = 1.22, 95% CI = 0.59-2.07). CONCLUSIONS: There was substantial variation in opioid prescribing patterns. Opioid prescription duration increased risk of ED visits for constipation, but not for pain or refill.
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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 | 0.000 | 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".