Family physicians step therapy up in symptomatic COPD patients differently than respiratory specialists
Bibliographic record
Abstract
On December 6, 2011, Health Canada approved Indacaterol, a once a day long acting beta-antagonist (LABA) for COPD. Physicians are challenged to reassess their prescribing behaviors and usage of LABA/ICS combination. Aim: To compare physician current and anticipated usage of Indacaterol, its place in therapy, and level of comfort toward this non ICS therapy. Methods: 45 minutes online survey of family physicians (n= 75) and respirologists (n=40) across Canada. Results: 92% of family physicians were aware of Indacaterol, 2 years after approval. This correlated with an estimated current 4% share of treatment and an anticipated 8% within 6 months, as per intention to prescribe. Respirologists awareness was slightly higher 97%, with current estimated share of treatment 6% and an anticipated 9% within the next 6 months. Both groups position Indacaterol as a COPD add-on therapy to a LAMA. Attitude towards LABA/ICS FDC is the main difference amongst the 2 groups. Study found that 13 % of FP estimated that LABA/ICS should be the 1st step up therapy compared to 5% for respirologists. Another 35 % of FPs legitimized ICS use as a means to proactively manage inflammation in COPD compared to only 5% of respirologists. Conclusion: Clearly, education on inflammation in the pathogenesis of COPD is necessary to differentiate the condition vs. asthma. This will be crucial to ensure the proper use of ICS in COPD, ie., in frequent exacerbators. It will also establish, as per our Canadian Thoracic Society guidelines, that an ICS-sparing treatment, such as Indacaterol, would be a superior and safer step up after LAMA therapy for persistent COPD symptoms in non-exacerbating patients than ICS/LABA FDC.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.007 | 0.001 |
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".