Use of Continuous Glucose Monitoring System in the Management of Severe Hypoglycemia
Bibliographic record
Abstract
BACKGROUND: Severe hypoglycemia can have a dramatic impact on daily life for people with diabetes. Hypoglycemia is quantifiable by the HYPO-Score derived from the frequency of severe hypoglycemia over a year and a component based on 4 weeks of glucose records. The latter gives a modified HYPO-Score as a short-term measure of hypoglycemia. We used a continuous glucose monitoring system (CGMS) in patients with severe hypoglycemia to assess if we could decrease hypoglycemia as measured by the modified HYPO-Score. METHODS: Sixteen type 1 diabetes subjects, 52.0 +/- 2.3 years old with a diabetes duration of 29.4 +/- 2.8 years having problematic hypoglycemia were enrolled. All used multiple daily insulin injections, and the glycosylated hemoglobin level was 8.4 +/- 0.3%. After a month of gathering hypoglycemia information for baseline modified HYPO-Score, subjects wore the CGMS for 2 months, and a modified HYPO-Score was repeated. To assess long-term benefit, CGMS was then discontinued for 3 months, and a final modified HYPO-Score was determined. RESULTS: The modified HYPO-Score decreased from 857 +/- 184 to 444 +/- 92 (P = 0.055) (intention-to-treat basis). Further analysis of the modified HYPO-Score when the CGMS was actually functioning showed it decreased from 857 +/- 184 to 366 +/- 86 (P = 0.023). Severe hypoglycemia episodes dropped from 16 at baseline to three when wearing the CGMS. The number of hypoglycemia episodes <3.0 mmol/L dropped from 8.6 +/- 1.5 to 4.7 +/- 0.9 (P = 0.01). Subjects expressed less fear of hypoglycemia with CGMS. In 11 who completed modified Final Month HYPO-Scores, the number of severe hypoglycemic events rose to six. At study end, 13 of 16 subjects elected to continue using the CGMS. CONCLUSIONS: When the CGMS was worn and functioning there was a significant decrease in the modified HYPO-Score and number of hypoglycemic values <3.0 mmol/L.
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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 | 0.000 |
| 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".