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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".