Polypharmacy and Excessive Polypharmacy Among Persons Living with Chronic Pain: A Cross-Sectional Study on the Prevalence and Associated Factors
Bibliographic record
Abstract
Purpose: Polypharmacy can be defined as the concomitant use of ≥5 medications and excessive polypharmacy, as the use of ≥10 medications. Objectives were to (1) assess the prevalence of polypharmacy and excessive polypharmacy among persons living with chronic pain, and (2) identify sociodemographic and clinical factors associated with excessive polypharmacy. Patients and Methods: This cross-sectional study used data from 1342 persons from the ChrOnic Pain trEatment (COPE) Cohort (Quebec, Canada). The self-reported number of medications currently used by participants (regardless of whether they were prescribed or taken over-the-counter, or were used for treating pain or other health issues) was categorized to assess polypharmacy and excessive polypharmacy. Results: Participants reported using an average of 6 medications (median: 5). The prevalence of polypharmacy was 71.4% (95% CI: 69.0-73.8) and excessive polypharmacy was 25.9% (95% CI: 23.6-28.3). No significant differences were found across gender identity groups. Multivariable logistic regression revealed that factors associated with greater chances of reporting excessive polypharmacy (vs <10 medications) included being born in Canada, using prescribed pain medications, and reporting greater pain intensity (0-10) or pain relief from currently used pain treatments (0-100%). Factors associated with lower chances of excessive polypharmacy were using physical and psychological pain treatments, reporting better general health/physical functioning, considering pain to be terrible/feeling like it will never get better, and being employed. Conclusion: Polypharmacy is the rule rather than the exception among persons living with chronic pain. Close monitoring and evaluation of the different medications used are important for all persons, especially those with limited access to care.
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 | 0.017 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".