Why the study?
The study was conducted to evaluate how well the Duke Treadmill Score predicts coronary artery disease severity in diabetic and non-diabetic individuals.
Does the Duke Treadmill Score predict coronary artery disease severity in diabetic and non-diabetic patients?
Does the Duke Treadmill Score predict coronary artery disease severity in diabetic and non-diabetic patients?
The Duke Treadmill Score is a useful clinical tool for predicting the severity of angiographic coronary artery disease in both diabetic and non-diabetic patients.
Coronary artery disease (CAD) is a significant cause of mortality and morbidity on a global scale. The Duke Treadmill Score (DTS) is a clinical evaluation that uses exercise stress testing to determine the severity of coronary artery disease (CAD). Objective: This study was to see how well DTS predicted the severity of CAD in diabetic and non-diabetic individuals. Methods: A prospective cohort study was conducted in the Department of Cardiology, PIMS, Islamabad, from March 2023 to September 2023. Total 450 patients were separated into diabetes (225) and non-diabetic (225) groups. Diabetes was diagnosed using American Diabetes Association criteria. The validated DTS scores exercise duration, ST-segment deviation, and angina symptoms to predict severe CAD. -11 or above is high risk, -10 to +4 is moderate, and +5 or more is low risk. Results: A study of 450 patients comprised 282 (62.6%) male and 168 (37.3%) female, with an average age of 58.4±13.2years. On coronary angiography, 170 diabetics (75.6%) and 130 non-diabetics (57.8%) had substantial CAD. Hypertension was 52.9% in diabetics and 49.3% in non-diabetics (p=0.920). Diabetics had 10.6% dyslipidemia and non-diabetics 9.3% (p=0.058). Conclusions: DTS may predict CAD severity in diabetics and non-diabetics, according to one study. Diabetes is a key risk factor for CAD, and DTS may aid in risk estimation. DTS findings and CAD risk assessment may potentially be affected by patient characteristics, exercise capacity, and treadmill technique.
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Khalil et al. (2023) studied this question.
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