371-P: Sex, Age, and Diabetes Type—Dissecting Patterns of Real-World Level 3 Hypoglycemia (iNPHORM, USA)
Bibliographic record
Abstract
Introduction and Objective: Large-scale, real-world data on age- and sex-specific Level 3 hypoglycemia rates in type 1 or 2 diabetes (T1D, T2D) remain critically sparse. We aimed to address this gap using prospective data from the iNPHORM study. Methods: Adults (≥18 years) with T1D or T2D on insulin and/or secretagogues recruited from a US-wide probability-based internet panel completed an online screener, baseline, and up to 12 monthly follow-up questionnaires. For complete cases with ≥1 follow-up, we calculated annualized Level 3 hypoglycemia rates overall and by age, sex (assigned-at-birth), and diabetes type. Results: N=978 participants were analyzed; Table 1 reports overall and group-specific Level 3 hypoglycemia rates. Across diabetes types, adults aged 18-39 years—particularly males—reported the highest event rates, which sharply dropped after age 39, regardless of sex. In T1D, females aged 40-49 years had higher rates than males (p=0.04), a trend that persisted (non-significantly) in cohorts aged ≥60 years. In T2D, males had higher Level 3 hypoglycemia rates than females until after age 59, when increasing female rates surpassed (non-significantly) declining male rates. Conclusion: Our results reveal age- and sex-based disparities in Level 3 hypoglycemia, suggesting that younger males and older females are key at-risk groups. Targeted prevention strategies are crucial to ensure equitable outcomes across diverse populations with diabetes. Disclosure A. Ratzki-Leewing: Other Relationship; Abbott, Dexcom, Inc. Consultant; Sanofi. Other Relationship; Sanofi. Consultant; Sanofi-Aventis U.S. Advisory Panel; Sanofi-Aventis U.S. J.E. Black: None. A. Kahkoska: None. K. Gandhi: None. B.L. Ryan: None. G. Zou: None. S.B. Harris: Advisory Panel; Abbott. Consultant; Abbott. Research Support; Boehringer-Ingelheim. Advisory Panel; Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Canadian Institutes of Health Research. Advisory Panel; Eli Lilly and Company. Research Support; Eli Lilly and Company. Consultant; Medscape. Advisory Panel; Novo Nordisk. Research Support; Novo Nordisk, Novartis Pharmaceuticals Corporation. Advisory Panel; Sanofi. Consultant; Sanofi. Funding The iNPHORM study was funded through an investigator-initiated grant from Sanofi Global.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".