Severe (level 3) hypoglycaemia occurrence in a real‐world cohort of adults with type 1 or 2 diabetes mellitus ( <scp>iNPHORM</scp> , United States)
Bibliographic record
Abstract
AIMS: Among adults with insulin- and/or secretagogue-treated diabetes in the United States, very little is known about the real-world descriptive epidemiology of iatrogenic severe (level 3) hypoglycaemia. Addressing this gap, we collected primary, longitudinal data to quantify the absolute frequency of events as well as incidence rates and proportions. MATERIALS AND METHODS: iNPHORM is a US-wide, 12-month ambidirectional panel survey (2020-2021). Adults with type 1 diabetes mellitus (T1DM) or insulin- and/or secretagogue-treated type 2 diabetes mellitus (T2DM) were recruited from a probability-based internet panel. Participants completing ≥1 follow-up questionnaire(s) were analysed. RESULTS: Among 978 respondents [T1DM 17%; mean age 51 (SD 14.3) years; male: 49.6%], 63% of level 3 events were treated outside the health care system (e.g. by family/friend/colleague), and <5% required hospitalization. Following the 12-month prospective period, one-third of individuals reported ≥1 event(s) [T1DM 44.2% (95% CI 36.8%-51.8%); T2DM 30.8% (95% CI 28.7%-35.1%), p = .0404, α = 0.0007]; and the incidence rate was 5.01 (95% CI 4.15-6.05) events per person-year (EPPY) [T1DM 3.57 (95% CI 2.49-5.11) EPPY; T2DM 5.29 (95% CI 4.26-6.57) EPPY, p = .1352, α = 0.0007]. Level 3 hypoglycaemia requiring non-transport emergency medical services was more common in T2DM than T1DM (p < .0001, α = 0.0016). In total, >90% of events were experienced by <15% of participants. CONCLUSIONS: iNPHORM is one of the first long-term, prospective US-based investigations on level 3 hypoglycaemia epidemiology. Our results underscore the importance of participant-reported data to ascertain its burden. Events were alarmingly frequent, irrespective of diabetes type, and concentrated in a small subsample.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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".