Causes of Death in a Contemporary Cohort of Patients With Type 2 Diabetes and Atherosclerotic Cardiovascular Disease: Insights From the TECOS Trial
Bibliographic record
Abstract
OBJECTIVE We evaluated the specific causes of death and their associated risk factors in a contemporary cohort of patients with type 2 diabetes and atherosclerotic cardiovascular disease (ASCVD). RESEARCH DESIGN AND METHODS We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular (CV) safety trial adding sitagliptin versus placebo to usual care in patients with type 2 diabetes and ASCVD (median follow-up 3 years). An independent committee blinded to treatment assignment adjudicated each cause of death. Cox proportional hazards models were used to identify risk factors associated with each outcome. RESULTS A total of 1,084 deaths were adjudicated as the following: 530 CV (1.2/100 patient-years [PY], 49% of deaths), 338 non-CV (0.77/100 PY, 31% of deaths), and 216 unknown (0.49/100 PY, 20% of deaths). The most common CV death was sudden death (n = 145, 27% of CV death) followed by acute myocardial infarction (MI)/stroke (n = 113 [MI n = 48, stroke n = 65], 21% of CV death) and heart failure (HF) (n = 63, 12% of CV death). The most common non-CV death was malignancy (n = 154, 46% of non-CV death). The risk of specific CV death subcategories was lower among patients with no baseline history of HF, including sudden death (hazard ratio [HR] 0.4; P = 0.0036), MI/stroke death (HR 0.47; P = 0.049), and HF death (HR 0.29; P = 0.0057). CONCLUSIONS In this analysis of a contemporary cohort of patients with diabetes and ASCVD, sudden death was the most common subcategory of CV death. HF prevention may represent an avenue to reduce the risk of specific CV death subcategories.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".