Nocturnal hypoglycemia is underdiagnosed in older people with insulin‐treated type 2 diabetes: The <scp>HYPOAGE</scp> observational study
Bibliographic record
Abstract
BACKGROUND: There is a lack of real-life data regarding the frequency and predictive factors of hypoglycemia in older patients with type 2 diabetes (T2D). This study aimed to determine the frequency and predictors of hypoglycemia in older patients with insulin-treated T2D. METHODS: This prospective multicenter study included 155 insulin-treated T2D patients aged 75 years and older with ≥2 self-monitoring of blood glucose (SMBG) daily controls. Participants underwent a geriatric and diabetic assessment and received ambulatory blinded continuous glucose monitoring (CGM) for 28 consecutive days with FreeStyle Libre Pro® sensor. Study population (n = 141) has >70% CGM active time. Multivariable logistic regressions were used to identify factors associated with SMBG confirmed hypoglycemia (≥70 mg/dL) and with nocturnal level 2 time below range (glucose concentration <54 mg/dL during ≥15 consecutive min between 0.00 and 6.00 am). RESULTS: was 7.9% ± 1.0%. After geriatric assessment, 102 participants (72.3%) were considered as complex and 39 (27.7%) as healthy. The primary endpoint (confirmed SMBG <70 mg/dL) occurred in 37.6% patients. In multivariable analysis, the risk of SMBG-confirmed hypoglycemia was positively associated with a longer duration of diabetes (OR (+1 year) =1.04, (1.00-1.08), p = 0.04) and glycemic variability assessed by CGM (CV %) (OR (+1%) = 1.12, [1.05-1.19], p = <0.001). Nighty-two patients (65.2%) experienced nocturnal time in hypoglycemia (i.e., <54 mg/dL during ≥15 consecutive min between midnight and 6 a.m.). In multivariable analyses, cognitive impairment (OR: 9.31 [2.59-33.4]), heart failure (OR: 4.81 [1;48-15.6]), and depressive disorder (OR: 0.19 [0.06-0.53]) were associated with nocturnal time in hypoglycemia. CONCLUSION: Nocturnal hypoglycemia is very common and largely underdiagnosed in older patients with insulin-treated T2D. CGM is a promising tool to better identify hypoglycemia and adapt diabetes management in this population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".