Bibliographic record
Abstract
In this issue of the Canadian Respiratory Journal, Blais et al (pages 27 to 32) publish an interesting study of the use of inhaled steroids in chronic obstructive pulmonary disease (COPD). Using the Quebec provincial database from the years 1990 to 1996, they found that these medications were given to more and more patients during the period of the study, and that the patients tended to be sicker than those who were not given inhaled steroids: they saw more physicians, including specialists; took more bronchodilators; and had more exacerbations. This is the result that I would have predicted if asked and is therefore not surprising. What surprised me is the fact that patients did not continue to use inhaled steroids once they had been started on them; of those given these drugs for the first time, one‐half stopped them after approximately 18 months, and after five years, approximately only 20% were still taking them. Further, as the number of patients given inhaled steroids increased, persistence decreased. What are we to make of this? One could argue that the dates covered by the study of Blais et al preceded the clinical trials (1) showing that inhaled steroids reduced exacerbations in COPD and that they were not prescribed with the conviction that present‐day physicians would employ. On the other hand, it seems unlikely that COPD patients were given these medications as a temporary expedient; presumably, most prescriptions for inhaled steroids were for chronic maintenance therapy. It is therefore unlikely that the prescribing physicians told COPD patients to take the drugs until they felt better and then discontinue them. It is also possible that inhaled steroids were unique respiratory drugs in that they were expensive and that this impacted persistence negatively. Although these patients had provincial drug insurance coverage, it was probably on a reimbursement basis, as in Manitoba, and inhaled steroids presented a cash flow problem.
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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 | 0.011 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".