Risk of recurrent severe hypoglycemia remains associated with a past history of severe hypoglycemia up to 4 years: Results from a large prospective contemporary pediatric cohort of the DPV initiative
Bibliographic record
Abstract
OBJECTIVES: In a contemporary cohort of youth with type 1 diabetes, we examined the interval between episodes of severe hypoglycemia (SH) as a risk factor for recurrent SH or hypoglycemic coma (HC). METHODS: This was a large longitudinal observational study. Using the DPV Diabetes Prospective follow-up data, we analyzed frequency and timing of recurrent SH (defined as requiring assistance from another person) and HC (loss of consciousness or seizures) in 14 177 youths with type 1 diabetes aged <20 years and at least 5 years of follow-up. RESULTS: Among 14 177 patients with type 1 diabetes, 72% (90%) had no, 14% (6.8%) had 1 and 14% (3.2%) >1 SH (HC). SH or HC in the last year of observation was highest with SH in the previous year (odds ratio [OR] 4.7 [CI 4.0-5.5]/4.6 [CI 3.6-6.0]), but remained elevated even 4 years after an episode (OR 2.0 [CI 1.6-2.7]/2.2 [CI 1.5-3.1]). The proportion of patients who experienced SH or HC during the last year of observation was highest with SH/HC recorded during the previous year (23% for SH and 13% for HC) and lowest in those with no event (4.6% for SH and 2% for HC) in the initial 4 years of observation. CONCLUSIONS: Even 4 years after an episode of SH/HC, risk for SH/HC remains higher compared to children who never experienced SH/HC. Clinicians should continue to regularly track hypoglycemia history at every visit, adjust diabetes education and therapy in order to avoid recurrences.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".