The Effect of Intensive Diabetes Treatment on Resting Heart Rate in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Cardiovascular disease is a major cause of morbidity and mortality in individuals with type 1 diabetes. Resting heart rate (RHR) is a risk factor for cardiovascular disease in the general population, and case-control studies have reported a higher RHR in individuals with type 1 diabetes. In individuals with type 1 diabetes, there is a positive correlation between A1C and RHR; however, no prospective studies have examined whether a causal relationship exists between A1C and RHR. We hypothesized that intensive diabetes treatment aimed to achieve normal A1C levels has an effect on RHR in individuals with type 1 diabetes. RESEARCH DESIGN AND METHODS: A total of 1,441 individuals with type 1 diabetes who participated in the Diabetes Control and Complications Trial (DCCT) had their RHR measured biennially by an electrocardiogram during the DCCT and annually for 10 years during the Epidemiology of Diabetes Interventions and Complications (EDIC) follow-up study. RESULTS: During the DCCT, intensive treatment was associated with lower mean RHR than conventional treatment, both in adolescents (69.0 vs. 72.0 bpm [95% CI 62.8-75.7 and 65.7-78.9, respectively], P = 0.013) and adults (66.8 vs. 68.2 [65.3-68.4 and 66.6-69.8, respectively], P = 0.0014). During follow-up in the EDIC, the difference in RHR between the treatment groups persisted for at least 10 years (P < 0.0001). CONCLUSIONS: Compared with conventional therapy, intensive diabetes management is associated with lower RHR in type 1 diabetes. The lower RHR with intensive therapy may explain, in part, its effect in reducing cardiovascular disease, recently demonstrated in type 1 diabetes.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".