Cardiovascular Autonomic Neuropathy and Cardiovascular Outcomes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE To examine whether cardiovascular autonomic neuropathy (CAN) is an independent risk factor of cardiovascular disease (CVD) events during DCCT/EDIC. RESEARCH DESIGN AND METHODS Standardized cardiovascular autonomic reflex tests (R-R response to paced breathing, Valsalva maneuver, postural changes in blood pressure) were performed at DCCT baseline, every 2 years throughout DCCT, and at two time points in EDIC. CVD events were ascertained throughout the study and adjudicated by a review committee. Cox proportional hazards models were used to estimate the effect of CAN at DCCT closeout on subsequent CVD risk. RESULTS There were 299 adjudicated CVD events in 165 participants following the DCCT closeout assessment: 132 of 1,262 subjects (10%) without CAN at DCCT closeout who experienced 244 CVD events versus 33 of 131 subjects (25%) with CAN at DCCT closeout who experienced 55 events (hazard ratio 2.79, 95% CI 1.91–4.09 for time to first CVD event). The cumulative incidence of the first occurrence of any CVD event during EDIC was significantly higher in participants with CAN at DCCT closeout compared with those without CAN. The association remained marginally significant after adjustment for multiple risk factors, including the EDIC updated mean HbA1c. When analyzed as a continuous variable, R-R variation was significantly lower at DCCT closeout in participants who experienced a CVD event compared with those who did not (P = 0.0012). CONCLUSIONS In the DCCT/EDIC cohort, individuals diagnosed with CAN at DCCT closeout experienced a higher long-term risk of CVD events during follow-up in EDIC. This association was not independent of historic glycemic exposure and its metabolic memory effect, the principal determinant of both long-term CVD risk and CAN in type 1 diabetes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it