Trends in Drug Claims for Non‐Specific Low Back Pain in Québec, 1997 to 2018
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to describe temporal trend of drugs claims after an episode of non-specific low back pain in Québec between 1997 and 2018, by pharmacological class. METHODS: Data came from the PROspective Québec study on work and health (PROQ), the Régie de l'assurance maladie du Québec (RAMQ) and Québec hospital services (Med-Echo). RAMQ common denomination codes were used to identify the types of medication claimed for an episode of non-specific low back pain. Multivariate log-binomial regression models were used to evaluate temporal trends in claims for the main pharmacological classes, taking into account dependence between multiple episodes. RESULTS: A total of 5214 episodes of non-specific low back pain were identified in 1658 people between 1997 and 2018. The mean age at the first medical service for low back pain was 64.1 years (standard deviation: 8.3 years). Results show a significant increase in opioid claims between 1997 and 1998 (4.1%) and 2009-2010 (12.7%) (p for trend = 0.0008), anticonvulsants between 1997 and 1998 (0.0%) and 2011-2012 (10.5%) (p for trend = 0.0002), and myorelaxants between 1997 and 1998 (2.0%) and 2009-2010 (8.8%) (p for trend < 0.0001), but no significant change in claims for antidepressants between 1997 and 1998 (0.5%) and 2016-2017 (2.6%) (p for trend = 0.5508). CONCLUSION: Claims for opioids, anticonvulsants and myorelaxants for non-specific low back pain showed significant upward changes between 1997 and 2018 in Québec, in contrast to antidepressants. These temporal variations in claims were different for each group of drugs, with a greater variation for anticonvulsants.
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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 | 0.001 | 0.001 |
| 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".