Impact of Aging on Risk of Hypoglycemia in Patients with Type 1 Diabetes
Bibliographic record
Abstract
Background: As T1D patients routinely reach older age, more information is needed to understand the impact of aging on the risk of hypoglycemia and its interaction with other age-related issues. Methods: We evaluated 2 groups of patients with T1D: older (age >65 years) and younger (age 18-35 years). All patients were subjected to either blinded CGM for 2 weeks or assessment of personal CGM. A hypoglycemia fear survey (HFS II), and a Clarke hypoglycemia unawareness survey were completed. Patients were also assessed for cognitive function by the Montreal Cognitive Assessment (MoCA). Glycemic control was measured by A1C. Results: We evaluated 56 patients with T1D; 23 in the older and 33 in the younger group. The average age was 70 vs. 28 years; diabetes duration 36 vs. 14 years; A1C 8.0% vs. 7.9%, respectively. Clinically significant hypoglycemia (glucose ?54 mg/dL for > 15 mins/episode) occurred equally in 91% of older (mean 28 minutes/day) and 88% of younger (mean 23 mins/day) patients. Older patients reported hypoglycemia unawareness more (39% vs. 30%), with similar scores on HSF II (34 vs. 33). However, 61% of older patients had cognitive impairment (MoCA score <26) compared to 12% in younger adults. There was a higher comorbidity burden in older patients (average number of comorbidities 4 vs. 1), with a higher number of daily medications (10 vs. 4). Conclusion: The risk of hypoglycemia is similar in older and younger patients with T1D. However, higher incidence of comorbidities including cognitive dysfunction and polypharmacy may increase the risk of poor outcomes due to hypoglycemia. Disclosure M. Munshi: Consultant; Self; Sanofi. C. Slyne: None. A. Atakov-Castillo: None. J. Greenberg: None. T. Greaves: None. S.P. Carl: None. E. Toschi: None.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".