Impact of hypoglycaemia on patient-reported outcomes from a global, 24-country study of 27,585 people with type 1 and insulin-treated type 2 diabetes
Bibliographic record
Abstract
AIMS: Data on the impact of hypoglycaemia on patients' daily lives and diabetes self-management, particularly in developing countries, are lacking. The aim of this study was to assess fear of, and responses to, hypoglycaemia experienced by patients globally. MATERIALS AND METHODS: This non-interventional, multicentre, 4-week prospective study using self-assessment questionnaires and patient diaries consisted of 27,585 patients, ≥18years, with type 1 diabetes (n=8022) or type 2 diabetes (n=19,563) treated with insulin for >12months, at 2004 sites in 24 countries worldwide. RESULTS: Increased blood glucose monitoring (69.7%) and seeking medical assistance (62.0%) were the most common responses in the 4weeks following hypoglycaemic events for patients with type 1 diabetes and type 2 diabetes, respectively. Approximately 44% of patients with type 1 diabetes or type 2 diabetes increased calorie intake in response to a hypoglycaemic episode. Following hypoglycaemia, 3.9% (type 1 diabetes) and 6.2% (type 2 diabetes) of patients took leave from work or study. Regional differences in fear of, and responses to, hypoglycaemia were evident - in particular, a lower level of hypoglycaemic fear and utilisation of healthcare resources in Northern Europe and Canada. CONCLUSIONS: Hypoglycaemia has a major impact on patients and their behaviour. These global data for the first time reveal regional variations in response to hypoglycaemia and highlight the importance of patient education and management strategies.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".