Coronary Artery Disease Is Common in Nonuremic, Asymptomatic Type 1 Diabetic Islet Transplant Candidates
Bibliographic record
Abstract
OBJECTIVE: Coronary artery disease (CAD) is the most common cause of death in patients with type 1 diabetes. Asymptomatic CAD is common in uremic diabetic patients, but its prevalence in nonuremic type 1 diabetic patients is unknown. The prevalence of CAD was determined by coronary angiography and the performance of noninvasive cardiac investigation evaluated in type 1 diabetic islet transplant (ITX) candidates with preserved renal function. RESEARCH DESIGN AND METHODS: A total of 60 consecutive type 1 diabetic ITX candidates (average age 46 years [mean 24-64], 23 men, and 47% ever smokers) underwent coronary angiography, electrocardiographic stress testing (EST), and myocardial perfusion imaging (MPI) in a prospective cohort study. CAD was indicated on angiography by the presence of stenoses >50%. Models to predict CAD were examined by logistic regression. RESULTS: Most subjects (53 of 60) had no history or symptoms of CAD; 23 (43%) of these asymptomatic subjects had stenoses >50%. CAD was associated with age, duration of diabetes, hypertension, and smoking. Although specific, EST and MPI were not sensitive as predictors of CAD on angiography (specificity 0.97 and 0.93, sensitivity 0.17 and 0.04, respectively) but helped identify two of three subjects requiring revascularization. EST and MPI did not enhance logistic regression models. A clinical algorithm to identify low-risk subjects who may not require angiography was highly sensitive but was applicable only to a minority (n = 8, sensitivity 1.0, specificity 0.27, negative predictive value 1.0). CONCLUSIONS: Nonuremic type 1 diabetic patients with hypoglycemic unawareness and/or metabolic lability referred for ITX are at high risk for asymptomatic CAD despite negative noninvasive investigations. Aggressive management of cardiovascular risk factors and further investigation into optimal cardiac risk stratification in type 1 diabetes are warranted.
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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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".