Effect of inhaled insulin on patient-reported outcomes and treatment preference in patients with type 1 diabetes
Bibliographic record
Abstract
OBJECTIVE: To compare patient-reported outcomes and treatment preference between preprandial inhaled insulin and preprandial subcutaneous (SC) insulin in the context of a clinical trial of crossover design with a primary objective of comparing HbA(1C) between groups. RESEARCH DESIGN AND METHODS: Multi-center, randomized, open-label, two-arm crossover trial conducted in the US and Canada with two 12-week periods comparing preference between preprandial human insulin inhalation powder (HIIP; AIR inhaled insulin) and preprandial SC insulin (regular human insulin or insulin lispro) in patients with type 1 diabetes. Patients received HIIP plus insulin glargine during period 1 and SC insulin plus insulin glargine during period 2, or the reverse sequence. MAIN OUTCOME MEASURES: SF-36 Vitality Subscale, Diabetes Symptom Checklist-Revised subscales, Diabetes Treatment Satisfaction Questionnaire, Insulin Delivery System Questionnaire, HIIP-specific questionnaire, preference question. RESULTS: Of 137 patients entered, 119 completed the study (54% female, mean age 40.9 +/- 12.4 years, mean HbA(1C) 8.1 +/- 1.0%). Patients had significantly greater treatment satisfaction and more positive evaluation of their insulin delivery system (easier to control blood sugar, less lifestyle impact) with HIIP than with SC insulin (all p < 0.01). Patients preferring HIIP (80%) were significantly more confident about (p = 0.005) and comfortable with (p = 0.003) using the system than those preferring SC insulin. Results may not be generalizable to all patients with type 1 diabetes. CONCLUSIONS: Some patients desire alternatives to insulin injection. In this study 80% preferred HIIP to injected insulin. Other patients feel more comfortable with familiar insulin delivery. Healthcare providers should help patients find insulin delivery that corresponds to individual preferences.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".