Noninvasive detection of silent coronary artery disease in patients with essential hypertension, alone or associated with type 2 diabetes mellitus, using dipyridamole stress 99mtechnetium-sestamibi myocardial perfusion imaging.
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease (CAD) is the leading cause of morbidity and mortality in hypertensive and diabetic patients. Early diagnosis of CAD and identification of high-risk subgroups, followed by appropriate therapy, may therefore enhance survival. OBJECTIVES: To prospectively establish the prevalence of silent CAD in asymptomatic patients with essential hypertension (EH), and to establish to what extent type 2 diabetes mellitus (DM) modifies the prevalence and severity of silent CAD in these patients. METHODS: The study population consisted of 543 patients 45 years of age and older with EH (n=321) or EH with type 2 DM (n=222), without typical angina or known CAD, selected according to criteria defined by the American Diabetes Association. All patients underwent dipyridamole stress and rest 99mtechnetium sestamibi myocardial single-photon emission computed tomography imaging. The stress and rest myocardial images were divided into 20 segments and blindly scored by two experienced observers. The summed stress score and summed rest score were obtained by adding the scores of the 20 segments of the stress and rest sestamibi images, respectively. The difference between the summed stress score and the summed rest score was defined as the summed difference score, representing reversible ischemia. RESULTS: There was a significant difference (P=0.001) between the percentage of EH patients with (41.4%) and without (27.7%) DM, with regard to abnormal summed stress scores. Moreover, hypertensive, diabetic patients had a significantly greater incidence of moderate to severe ischemia (P=0.011). In addition, a significantly greater proportion of hypertensive patients with DM showed reversible ischemia compared with EH patients without DM (39.6% versus 24.6%; P<0.0001). Proteinuria and dyspnea were significant predictors of silent ischemia in EH patients with DM. CONCLUSIONS: In this high-risk population screened according to the American Diabetes Association criteria with dipyridamole sestamibi myocardial single-photon emission computed tomography imaging, the prevalence of silent ischemia was 28% in EH patients. It is noteworthy that the prevalence (41%) and severity of silent ischemia were significantly greater in EH patients with DM.
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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) | 0.001 | 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".