Association between hypoglycaemic drug de-intensification, mortality and hospital admission in older adults with type 2 diabetes: a cohort study emulating a target trial
Bibliographic record
Abstract
BACKGROUND: Hypoglycaemic drugs (sulfonylureas, glinides or insulins) are commonly prescribed for older adults with type 2 diabetes (T2D) but may carry risks of adverse events. Whether de-intensifying hypoglycaemic drugs is associated with clinical benefit in older adults remains unknown. OBJECTIVE: To evaluate the association between de-intensification of hypoglycaemic drugs and clinical outcomes in older adults with T2D. METHODS: Cohort study conducted with the target trial emulation approach, using data collected from 2000 French general practises between January 2010 and February 2019 (The Health Improvement Network-THIN database). Eligible participants were ≥75 years old, on stable hypoglycaemic drugs (no change in drug or dose) for at least 6 months, and had an HbA1c value <9%. Hypoglycaemic drug de-intensification (exposure) was defined as cessation or reduction of ≥50% of total dose. The primary outcome was a composite measure of all-cause death or hospital admissions within 3 months, and its association with exposure was assessed using multivariable logistic regression adjusted for potential baseline confounders. RESULTS: The study included 14 383 unique individuals corresponding to 177 314 trial emulation participants (mean age 80 years; 44.7% female). Of these, 6480 participants were allocated to de-intensification group, and 170 834 to the control group. At 3 months, the primary outcome occurred in 3.96% of the de-intensification group and 2.99% of controls [adjusted relative risk, 1.33 (95% CI, 1.22-1.43)]. Subgroup analyses showed consistent associations across most participants' profiles. CONCLUSIONS: In older adults with T2D, de-intensification of hypoglycaemic drugs was associated with a higher short-term risk of all-cause death or hospitalisation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".