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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".