387-P: High Incidences of Level 3 Severe Hypoglycemia Reported by T2DM Secretagogue-Users (iNPHORM, USA)
Bibliographic record
Abstract
In the US, >90% of people with T2DM on oral antihyperglycemics use secretagogues. The present analysis is the first to quantify the real-world, US frequency of Level 3 severe hypoglycaemia (SH) in this population. Longitudinal, prospective data were leveraged from the iNPHORM study. Adults (≥18 years old) with secretagogue-treated T2DM (not on insulin) were recruited from a US-wide, probability-based internet panel. Data on participant characteristics and Level 3 SH occurrence were captured across a screener, baseline and 12 monthly follow-ups. Multivariable negative binomial regression with cluster bootstrapping for repeated measures modelled the annualized rate of SH for individuals completing ≥1 follow-up(s). A repeated lasso regression ‘voting’ procedure selected all risk factors. Multiple imputation addressed missingness. Of the 353 respondents (male: 51.1%; age: 54.6 [SD: 13.2] years; diabetes duration: 10 [IQR: 12] years; retention rate: 84.4%), the incidence proportion of SH over follow-up was 21.8 (95% CI: 17.8-26.3)%, and the rate was 3.8 (95% CI: 2.5-5.7) events per person-year. Our final model included age, continuous/flash glucose monitoring use, corticosteroid use, number of healthcare visits, fear of hypoglycemia, number of past-year SH requiring hospital care, retinopathy, and other diabetes complications. The rate of annualized Level 3 SH statistically increased with younger age, more frequent healthcare visits, greater fear of hypoglycemia, higher number of past-year healthcare-related SH, and presence of retinopathy. Our results indicate disturbingly high incidences of Level 3 SH among secretagogue users. Whenever logical and feasible, clinicians should prioritize one of the many other available antihyperglycemics that confer little to no hypoglycemia risk. Else, other hypoglycemia prevention strategies—risk-tailored to this ubiquitous T2DM population—are urgently warranted. Disclosure A.Ratzki-leewing: Consultant; Novo Nordisk, Eli Lilly and Company, Research Support; Sanofi. J.E.Black: None. G.Zou: None. B.L.Ryan: None. S.B.Harris: Advisory Panel; Bayer Inc., AstraZeneca, Eli Lilly and Company, Dexcom, Inc., Novo Nordisk A/S, Novo Nordisk Canada Inc., Sanofi, Consultant; Abbott Diabetes, Janssen Pharmaceuticals, Inc., Other Relationship; American Diabetes Association, Research Support; Abvance Therapeutics, Canadian Institutes of Health Research. Funding 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".