The Impact of Frailty on the Effectiveness and Safety of Intensive Glucose Control and Blood Pressure–Lowering Therapy for People With Type 2 Diabetes: Results From the ADVANCE Trial
Bibliographic record
Abstract
OBJECTIVE To develop a frailty index (FI) and explore the relationship of frailty to subsequent adverse outcomes on the effectiveness and safety of more intensive control of both blood glucose and blood pressure (BP), among participants with type 2 diabetes in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. RESEARCH DESIGN AND METHODS Cox proportional hazard models were used to estimate the effectiveness and safety of intensive glucose control and BP intervention according to frailty (defined as FI >0.21) status. The primary outcomes were macro- and microvascular events. The secondary outcomes were all-cause mortality, cardiovascular mortality, severe hypoglycemia, and discontinuation of BP treatment due to hypotension/dizziness. RESULTS There were 11,140 participants (mean age, 65.8 years; 42.5% women, 25.7% frail). Frailty was an independent predictor of all primary outcomes and secondary outcomes. The effect of intensive glucose treatment on primary outcomes showed some evidence of attenuation in the frail: hazard ratios for combined major macro- and microvascular events 1.03 (95% CI 0.90–1.19) in the frail versus 0.84 (95% CI 0.74–0.94) in the nonfrail (P = 0.02). A similar trend was observed with BP intervention. Severe hypoglycemia rates (per 1,000 person-years) were higher in the frail: 8.39 (6.15–10.63) vs. 4.80 (3.84–5.76) in nonfrail (P < 0.001). There was no significant difference in discontinuation of BP treatment between frailty groups. CONCLUSIONS It was possible to retrospectively estimate frailty in a trial population, and this FI identified those at higher risk of poor outcomes. Participants with frailty had some attenuation of benefit from intensive glucose-lowering and BP-lowering treatments.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".