Prevalence of opioid dispensings and concurrent gastrointestinal medications in an elderly population from Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Although opioid analgesics are effective therapeutic agents, gastrointestinal (GI) side effects represent a challenging consequence of treatment. In an elderly population, age-related physiological changes, such as decreased GI functioning and dehydration, may compound the adverse effects of opioids; therefore, appropriate prophylactic treatment, utilizing laxatives and/or acid suppressants, is particularly important in an elderly population. AIM: This study describes the prevalence of outpatient opioid dispensings and the concomitant dispensing of opioids and GI medications in a population 65 years or older enrolled in the Ontario Drug Benefit Program in 2005. METHODS: Using a retrospective cohort design, dispensings of opioids, laxatives, and acid suppressants were identified using claims reimbursement data. Concurrent dispensings were defined as having at least one "GI medication-dispensed day" overlapping an "opioid-dispensed day". RESULTS: More than 18 percent of the elderly, drug plan population was dispensed an opioid in 2005. Women had more opioid dispensings and were dispensed opioids for extended periods of time as compared with men. Approximately half of patients with an opioid dispensing were concomitantly dispensed a GI medication; these medications were dispensed nearly twice as frequently among people with chronic opioid dispensings when compared with people with nonchronic opioid dispensings. CONCLUSIONS: Although laxatives are commonly recommended in patients taking opioids, only half of the older adults in Ontario who were dispensed an opioid also received a concomitant GI medication dispensing. As the elderly are more likely to develop opioid-induced constipation, the prophylactic use of laxatives and/or acid suppressant medications is often necessary to mitigate the side effects associated with their 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".