Availability of Inhaled Insulin Promotes Greater Perceived Acceptance of Insulin Therapy in Patients With Type 2 Diabetes
Bibliographic record
Abstract
Inhaled insulin (INH, Exubera) is under investigation for preprandial treatment of patients with type 1 and type 2 diabetes (1–3). This dry-powder insulin formulation is delivered by aerosol, permitting the noninvasive administration of rapid-acting insulin (4). Preliminary studies have shown that INH provides reproducible and effective control of glycemia (1,5–7). This randomized controlled trial examined the extent to which the availability of INH affects the perceived acceptability of insulin therapy among patients with type 2 diabetes who failed to achieve target glycemia on current therapy. Male or female participants ( n = 779) aged 35–80 years with at least 3 months duration of type 2 diabetes and a HbA1c >8%, despite current therapy, were recruited from seven countries. Permitted current therapy included dietary measures and/or oral antidiabetic agents (OADs). Patients receiving insulin injections, smokers, or those who had significant pulmonary diseases were excluded. All patients gave informed consent, and local research ethics review boards approved the study. Participants were randomly assigned to receive either educational information about the potential risks and benefits of all currently licensed treatment options only (OADs and/or subcutaneous insulin, n = 388) or information about the potential risks and benefits of licensed treatments and INH ( n = 391). …
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".