Factors Associated With Frequent Opioid Use in Children With Acute Recurrent and Chronic Pancreatitis
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to understand the association of frequent opioid use with disease phenotype and pain pattern and burden in children and adolescents with acute recurrent (ARP) or chronic pancreatitis (CP). METHODS: Cross-sectional study of children <19 years with ARP or CP, at enrollment into the INSPPIRE cohort. We categorized patients as opioid "frequent use" (daily/weekly) or "nonfrequent use" (monthly or less, or no opioids), based on patient and parent self-report. RESULTS: Of 427 children with ARP or CP, 17% reported frequent opioid use. More children with CP (65%) reported frequent opioid use than with ARP (41%, P = 0.0002). In multivariate analysis, frequent opioid use was associated with older age at diagnosis (odds ratio [OR] 1.67 per 5 years, 95% confidence interval [CI] 1.13-2.47, P = 0.01), exocrine insufficiency (OR 2.44, 95% CI 1.13-5.24, P = 0.02), constant/severe pain (OR 4.14, 95% CI 2.06-8.34, P < 0.0001), and higher average pain impact score across all 6 functional domains (OR 1.62 per 1-point increase, 95% CI 1.28-2.06, P < 0.0001). Children with frequent opioid use also reported more missed school days, hospitalizations, and emergency room visits in the past year than children with no frequent use (P < 0.0002 for each). Participants in the US West and Midwest accounted for 83% of frequent opioid users but only 56% of the total cohort. CONCLUSIONS: In children with CP or ARP, frequent opioid use is associated with constant pain, more healthcare use, and higher levels of pain interference with functioning. Longitudinal and prospective research is needed to identify risk factors for frequent opioid use and to evaluate nonopioid interventions for reducing pain and disability in these children.
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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".