Validation of a Bowel Function Diary for Assessing Opioid-Induced Constipation
Bibliographic record
Abstract
OBJECTIVES: Validated tools to assess opioid-induced constipation (OIC) are needed. The aim of this study was to validate a Bowel Function Diary (BF-Diary) that includes patient-reported outcomes (PROs) associated with OIC. METHODS: In a multicenter, observational study, opioid-naive or recently untreated (≥ 14 days) adults with nonmalignant, chronic pain who were prescribed oral opioid and usual care completed an electronic diary daily for 2 weeks. Test-retest reliability was assessed. Validity was evaluated for two composite end points--number of spontaneous bowel movements (SBM) and complete SBMs (SCBM)--and for other relevant PROs. RESULTS: Of 238 patients (mean age 54 years, 58% women), 63% reported constipation. The intraclass correlation coefficient for numbers of SBM and SCBM, and other BF-Diary PROs was ≥ 0.71 for all items except stool consistency. Mean (s.d.) number of SBM per week was significantly less in each week for patients with vs. without constipation (5.6 ± 4.3 and 7.3 ± 3.6, respectively over week 1, P=0.0012; similarly, P=0.0096 over week 2). Validity of individual items in the BF-Diary was supported (P<0.05, stool consistency; P<0.0001, all others). CONCLUSIONS: BF-Diary items are generally reliable and valid assessments for OIC research. Specifically, number of SBM is a valid measure for differentiating opioid-treated patients with and without constipation.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".