The Effect of Hypoglycemia on Health-Related Quality of Life: Canadian Results from a Multinational Time Trade-off Survey
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the impact of hypoglycemia according to severity and time of onset on health-related quality of life (HRQoL) in a Canadian population. METHODS: Time trade-off (TTO) methodology was used to estimate health utilities associated with hypoglycemic events in a representative sample of the Canadian population. A global analysis conducted in the United Kingdom, Canada, Germany and Sweden has been published. The present Canadian analysis focuses on 3 populations: general, type 1 and type 2 diabetes. Using a web-based survey, participants (>18 years) assessed the utility of 13 different health states (severe, non-severe, daytime and nocturnal hypoglycemia at different frequencies) using a scale from 1 (perfect health) to 0 (death). The average disutility value for each type of event was calculated. RESULTS: Of 2258 participants, 1696 completers were included in the analysis. A non-severe nocturnal hypoglycemic event was associated with a significantly greater disutility than a non-severe daytime event (-0.0076 vs. -0.0056, respectively; p=0.05), while there was no statistically significant difference between severe nocturnal and severe daytime events (-0.0616 vs. -0.0592; p=0.76). Severe hypoglycemia was associated with greater disutility than non-severe hypoglycemia (p<0.0001). Similar trends were reported in participants with diabetes. CONCLUSIONS: The findings presented here show that any form of hypoglycemia had a negative impact on HRQoL in a Canadian population. Nocturnal and/or severe hypoglycemia had a greater negative impact on HRQoL compared with daytime and/or non-severe events. This highlights the importance of preventing the development and nocturnal manifestation of hypoglycemia in patients with diabetes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".