CREED study: Hypoglycaemia during Ramadan in individuals with Type 2 diabetes mellitus from three continents
Bibliographic record
Abstract
AIMS: To describe diabetes treatment and hypoglycaemia in individuals with Type 2 diabetes mellitus during Ramadan. METHODS: A multi-country, retrospective, observational study with data captured before, during, and after Ramadan. We report on a cohort of people (N=3250) with Type 2 diabetes mellitus in four culturally distinct regions: Asia, North Africa, Europe, and the Middle East. RESULTS: During Ramadan, the proportion of participants on oral anti-diabetic medication alone ranged from 68.4% (Middle East) to 80.5% (Asia); the proportion on insulin alone ranged from 3.7% (Middle East) to 8.6% (Europe). The average number of days fasted for individuals with an American Diabetes Association (ADA) risk status of very high was 27 (Middle East), 25.7 (Asia), 25.4 (North Africa), and 21 (Europe). The incidence of hypoglycaemia according to an ADA risk status of very high was 5.6% (n=1/18, Europe), 6.1% (n=2/33, Middle East), 8.7% (n=4/46, Asia), and 38% (n=10/26, North Africa). The incidence of hypoglycaemia, during Ramadan, for the entire cohort was 16.8% with insulin treatment and 5.3% with oral anti-diabetic medication. Having an episode of hypoglycaemia before Ramadan was associated with hypoglycaemia during Ramadan (odds ratio 7.80; 95% confidence interval 5.31-11.45). CONCLUSIONS: Approaches to the management of Type 2 diabetes mellitus during Ramadan varied across regions. Episodes of hypoglycaemia and insulin therapy predicted risk of hypoglycaemia during Ramadan and identified individuals who required Ramadan-specific education.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".