The healthcare burden of non-compliance to pharmacotherapeutic escalation recommendations for COPD
Bibliographic record
Abstract
To describe the healthcare burden associated with not escalating patients with COPD managed with LAMA or LABA monotherapy or LAMA/LABA dual therapy to ICS/LAMA/LABA following a moderate or severe exacerbation. This observational study utilised medical claims from the Quebec Provincial Health Insurance administrative database. Included were patients ≥40 years of age with an incident diagnosis of COPD (during 2002–2011) receiving a respiratory medicine within 2 weeks of a COPD claim and treated with a LAMA, LABA or LAMA/LABA without a preceding moderate or severe exacerbation. Multivariate-adjusted outcomes included incidence density rates for moderate or severe COPD exacerbations and healthcare utilisation, stratified by escalation to ICS/LAMA/LABA triple therapy following an exacerbation. Overall, 19,198 (49.5%) patients experienced COPD exacerbations. Of these, 1,136 (5.9%) were escalated to triple therapy following an exacerbation. Compared with patients switched to triple therapy, those not escalated experienced increased mean incidence density rates (per 100 person-years) for future exacerbations (any: 0.21 vs 0.18, p<0.001; moderate: 0.10 vs 0.07, p<0.001), ER visits (0.11 vs 0.10, p<0.05), and greater use of antibiotics, oral corticosteroids and rescue medications (0.94 vs 0.79, 0.76 vs 0.66, 1.08 vs 0.50; p<0.001). Hospitalisation rates were higher among patients treated with triple therapy (0.16 vs 0.14; p<0.01). Other outcomes were similar between groups. Failure to escalate to ICS/LAMA/LABA triple therapy following an exacerbation results in increased exacerbations, ER visits and concomitant medication use in patients with COPD. Funded by GSK: HO-13-14097.
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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 | 0.003 | 0.023 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".