Opioid Use in Patients with Ankylosing Spondylitis Is Common in the United States: Outcomes of a Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence of chronic opioid use in patients with ankylosing spondylitis (AS), and to compare the characteristics of patients with and without chronic opioid use. METHODS: This was a retrospective cohort study of patients with AS identified in the Truven Health MarketScan Research database between January 1, 2012, and March 31, 2017. Commercial and Medicaid claims data were examined using both specific (720.0 and M45.x) and broader (720.x and M45.x) International Classification of Diseases (ICD) coding definitions. Patients were aged ≥ 18 years on the date of first qualifying ICD code occurrence (the index date). Demographics and clinical characteristics were assessed in the 12-month period preceding the index date. The 12-month followup period was used to assess prevalence and characteristics of chronic opioid use. RESULTS: Chronic opioid use was common among patients with commercial claims (23.5% of ICD 720.0 patients; 27.3% of ICD 720.x patients), and especially those with Medicaid claims (57.1% and 76.7%, respectively). The proportion of patients with claims for anti-tumor necrosis factor therapies during followup was often low, and for Medicaid patients was lower among those with chronic opioid use (29.6% of ICD 720.0 patients; 2.3% of ICD 720.x patients) than those without (47.1% and 7.1%, respectively). Among chronic opioid users in all cohorts, the cumulative supply of opioids was typically high (≥ 270 days in the followup period); most opioids prescribed were Schedule II. CONCLUSION: Patients with AS receive opioids with disturbing frequency. The infrequent prescription of recommended therapies to these patients reflects a need to optimize treatment further through education of patients and healthcare professionals alike.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".