Geographic patterns in patient demographics and insulin use in 18 countries, a global perspective from the multinational observational study assessing insulin use: understanding the challenges associated with progression of therapy (MOSAIc)
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Bibliographic record
Abstract
BACKGROUND: Among patients with type 2 diabetes, insulin intensification to achieve glycemic targets occurs less often than clinically indicated. Barriers to intensification are not well understood. We present patients' baseline characteristics from MOSAIc, a study investigating patient-, physician-, and healthcare environment-based factors affecting insulin intensification and subsequent health outcomes. METHODS: MOSAIc is a longitudinal, observational study following patients' diabetes care in 18 countries: United Arab Emirates (UAE), Argentina, Brazil, Canada, China, Germany, India, Israel, Italy, Japan, Mexico, Russia, Saudi Arabia, South Korea, Spain, Turkey, United Kingdom, United States. Eligible patients are age ≥ 18, have type 2 diabetes, and have used insulin for ≥ 3 months with/without other antidiabetic medications. Extensive baseline demographic, clinical, and psychosocial data are collected at baseline and regular intervals during the 24-month follow-up. We conducted descriptive analyses of baseline data. RESULTS: Four thousand three hundred forty one patients met eligibility criteria. Patients received their type 2 diabetes diagnosis 12 ± 8 years prior to baseline visit, yet patients in developing countries were younger than in developed countries (e.g., UAE, 55 ± 10; Germany = 70 ± 10). Saudi Arabians had the highest HbA1c values (9.0 ± 2.2) and Germany (7.5 ± 1.4) among the lowest. Most patients in 5 (28%) of the 18 countries did not use an oral antidiabetic drug. Over half of patients in fourteen (78 %) countries exclusively used basal insulin; most Indian and Chinese patients exclusively used mixed insulin. CONCLUSIONS: MOSAIc's baseline data highlight differences in patient characteristics across countries. These patterns, along with physician and healthcare environment differences, may contribute to the likelihood of insulin intensification and subsequent clinical outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it