3-OR: Severe Hypoglycemia among Older Adults with Diabetes (iNPHORM, USA)
Bibliographic record
Abstract
Despite an aging US diabetes population, little is known about the real-world frequency of iatrogenic severe hypoglycemia (SH) among older adults. We analyzed iNPHORM data to address this gap. People ≥60-year-old with T1DM or T2DM on insulin and/or secretagogues were recruited from a probability-based internet panel. Data on SH were obtained via a screener, baseline, and 12 monthly follow-ups. Crude SH incidence rates (IRs) and proportions (IPs) were calculated overall, and by diabetes type, medication type, and mode of SH recovery. N=307 were analyzed (T1DM: 8.5%; age: 67.5 [SD:5.5] years; male: 54.1%; retention rate: 81.8%). Among T2DM respondents, 39.9% used insulin without secretagogues, 50.2% secretagogues without insulin, and 10.0% insulin and secretagogues. The overall IP of SH was 19.9 (95%CI: 15.8-24.7)%, and the IR was 0.89 (95%CI: 0.62-1.27) events per person-year (EPPY). People with T1DM had a higher total IP (42.3 [95%CI: 25.5-61.1]%) and IR (2.07 [95%CI: 0.98-4.38] EPPY) than those with T2DM (IP: 17.8 [95%CI: 13.8-22.7]%; IR: 0.78 [95%CI: 0.52-1.15] EPPY), including insulin without secretagogue users (1.09 [95%CI: 0.66-1.80] vs. 0.61 [95%CI: 0.26 to 1.45] [insulin with secretagogues] and 0.50 [95%CI: 0.23 to 1.05] [secretagogues without insulin] EPPY). Emergency care and hospitalization constituted 3.6% (T1DM: 0%; T2DM: 6.7%) and 1.8% (T1DM: 0%; T2DM: 2.2%) of SH (n=224), respectively. Paramedical/hospital-based SH was more common in T2DM (0.06 [95%CI: 0.02-0.19]) than T1DM (0 EPPY) with IRs highest among insulin without secretagogue users (0.11 [95%CI: 0.03-0.47] EPPY). This is the first US prospective study on SH frequency in older adults with diabetes. Most (96.4%) events occurred at-home, underscoring the need for self-reported SH capture. Overall IPs and IRs were greater in T1DM than T2DM; but those with T2DM had more healthcare-based events. To mitigate undue health and economic costs, it is imperative clinicians remain vigilant to preventing SH in this vulnerable and growing population. 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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".