Impact of adherence to treatment with tiotropium co-administered with fluticasone propionate/salmeterol combination in COPD patients
Bibliographic record
Abstract
Introduction: Poor adherence to treatment has been considered a major factor contributing to sub-optimal COPD management. Objective: To assess the association between adherence to treatment and health care resource utilization (HCRU) in COPD patients treated with tiotropium (TIO) co-administered with fluticasone propionate / salmeterol combination (FSC). Methods: A retrospective observational cohort study utilizing administrative databases of the Quebec provincial health insurance of patients (age ≥40 years) with a diagnosis of COPD and ≥2 pharmacy claims for TIO + FSC dispensed from 1/1/2001 to 12/31/2010. Adherence to treatment was ascertained as compliance (medication possession ratio ≥80%) and persistence (no absence of treatment gap ≥30 days). Outcomes assessed were moderate exacerbations (ME), severe exacerbations (SE) and COPD HCRU. Multivariate logistic regression analyses (MLRA) were used to adjust for baseline characteristics. Results: A total of 11,148 subjects, proportions of compliant and persistent patients with TIO+FSC were 63% and 45% respectively. MLRA showed that adherence to TIO+FSC were associated with a significant (p<0.001) reduction in risk of ME and SE. The adjusted Odds Ratio for compliant patients were: TIO (ME = 0.449, SE = 0.570) and FSC (ME = 0.546; SE = 0.749). Similar results were seen for persistence. Compliance and persistence with TIO+FSC were also associated with significant (p<0.001) reduction in HCRU including rescue medication use and hospitalizations Conclusion: This study suggests that improved adherence to treatment with TIO+FSC is associated with decreased risk for exacerbations and lower HCRU in COPD patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".