Subclinical perfusion deficits in patients with Type 2 diabetes detectable with Cardiovascular Magnetic Resonance Imaging
Bibliographic record
Abstract
An estimated 200 million people worldwide have type 2 diabetes. Type 2 diabetes is recognized as an independent risk factor for adverse cardiac events, such as myocardial infarction. Cardiovascular disease is the leading cause of death amongst diabetic patients. The subclinical pathophysiology of diabetic heart disease predicts global microvascular disease, prior to the onset of overt ischemic heart disease. Non-invasive screening methods are therefore important for risk stratification of asymptomatic patients. Cardiovascular Magnetic Resonance Imaging (CMR) is a valuable tool for the assessment of subclinical microvascular function in this high-risk population. To assess the degree of cardiac microvascular dysfunction in individuals type 2 diabetes (T2D) without coronary disease or hypertension, compared to healthy, non-diabetic controls. This cross sectional pilot data included 2 groups of subjects: Patients diagnosed with type 2 diabetes (Hb A1c 7.5-9.9%; mean age 59.3±7.17; n=6), and healthy, non-diabetic age-matched controls (mean age 51.9±10.3; n=10). Medical history and ECG were reviewed to rule out ischemic heart disease. Qualified patients underwent a CMR-Adenosine stress perfusion, Subendocardial perfusion delays were observed in 4 out of 6 diabetic patients, and 0 of 10 healthy controls (p < 0.05). Importantly, the T2D patients exhibited primarily diffuse or circumferential perfusion deficits (Figure 1 ). Controls were normotensive (125.3/79.7 mmHg ± 6.1/2.8 mmHg), and patients had controlled blood pressure (mean 132.2/79.8 mmHg ± 8.5/5.2 mmHg), primarily through ACE inhibitors. Patients and controls had normal systolic function (LV EF 57.7 ± 3.01 and 57.8 ± 5.4, respectively). Stress perfusion image from patient diagnosed with a type 2 diabetes in 2009. Note circumferential subendocardial perfusion delay. The observed perfusion abnormality supports previous nuclear imaging findings and pathophysiological research of diabetic heart disease and may indicate more diffuse patterns of microvascular disease. Further studies are required to assess the pathophysiologic context and prognostic impact of these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".