Regional variations in definitions and rates of hypoglycaemia: findings from the global <scp>HAT</scp> observational study of 27 585 people with Type 1 and insulin‐treated Type 2 diabetes mellitus
Bibliographic record
Abstract
AIM: To determine participant knowledge and reporting of hypoglycaemia in the non-interventional Hypoglycaemia Assessment Tool (HAT) study. METHODS: HAT was conducted in 24 countries over a 6-month retrospective/4-week prospective period in 27 585 adults with Type 1 or insulin-treated Type 2 diabetes mellitus. Participants recorded whether hypoglycaemia was based on blood glucose levels, symptoms or both. RESULTS: Hypoglycaemia rates were consistently higher in the prospective compared with the retrospective period. Most respondents (96.8% Type 1 diabetes; 85.6% Type 2 diabetes) knew the American Diabetes Association/European Association for the Study of Diabetes hypoglycaemia definition, but there were regional differences in the use of blood glucose measurements and/or symptoms to define events. Confirmed symptomatic hypoglycaemia rates were highest in Northern Europe/Canada for Type 1 diabetes (63.9 events/year) and in Eastern Europe for Type 2 diabetes (19.4 events/year), and lowest in South East Asia (Type 1 diabetes: 6.0 events/year; Type 2 diabetes: 3.2 events/year). Unconfirmed symptomatic hypoglycaemia rates were highest in Eastern Europe for Type 1 diabetes (5.6 events/year) and South East Asia for Type 2 diabetes (4.7 events/year), and lowest for both in Russia (Type 1 diabetes: 2.1 events/year; Type 2 diabetes: 0.4 events/year). Participants in Latin America reported the highest rates of severe hypoglycaemia (Type 1 diabetes: 10.8 events/year; Type 2 diabetes 3.7 events/year) and severe hypoglycaemia requiring hospitalization (Type 1 diabetes: 0.56 events/year; Type 2 diabetes: 0.44 events/year). The lowest rates of severe hypoglycaemia were reported in South East Asia (Type 1 diabetes: 2.0 events/year) and Northern Europe/Canada (Type 2 diabetes: 1.3 events/year), and the lowest rates of severe hypoglycaemia requiring hospitalization were in Russia (Type 1 diabetes: 0.15 events/year; Type 2 diabetes: 0.09 events/year). The blood glucose cut-off used to define hypoglycaemia varied between regions (Type 1 diabetes: 3.1-3.6 mmol/l; Type 2 diabetes: 3.5-3.8 mmol/l). CONCLUSIONS: Under-reporting of hypoglycaemia rates in retrospective recall and regional variations in participant definitions of hypoglycaemia may contribute to the global differences in reported rates. Discrepancies between participant definitions and guidelines may highlight a need to redefine hypoglycaemia criteria. (Clinical Trials Registry No: NCT01696266).
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".