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Objective: The primary objective of this study is to assess the diagnostic value of treadmill exercise electrocardiographic test (EET) for coronary artery disease (CAD) in the aged population, emphasizing the need for improved diagnostic criteria due to the limitations of traditional EET in accurately diagnosing CAD among elderly patients. This focus is critical as the aged population has a higher prevalence of CAD, and early and accurate diagnosis is essential for effective management and treatment.

Methods: This study comprised two stages. Initially, we retrospectively analyzed data from patients aged > 60 years who underwent treadmill EET within two weeks of coronary angiography (CAG) during hospitalization from June 1, 2014, to May 31, 2017. We evaluated the diagnostic value of treadmill EET using both the standard criterion (ST depression > 0.1 mV) and a modified criterion (the ratio of ST depression to metabolic equivalent [STdmax/MET]), explaining our choice of the modified criterion as it potentially offers a more nuanced assessment by considering the patient's exercise capacity. A subgroup analysis was also conducted. Subsequently, a prospective study to further investigate the modified criterion was carried out.

Results: In the retrospective analysis, 190 patients were enrolled, with 71.5% confirmed to have CAD. The sensitivity, specificity, and accuracy of the standard criterion were 66.2%, 42.6%, and 59.5%, respectively. With a cut-off value for STdmax/MET set at 0.255 mV·W/m2, these metrics improved to 79.4%, 55.7%, and 72.4%, respectively, for the modified criterion. The prospective study, involving 47 patients, confirmed significant improvements in sensitivity (85.7% vs. 64.3%, P = .041) and specificity (68.4% vs. 31.6%, P = .046) when applying the modified criterion.

Conclusions: The introduction of the novel modified diagnostic criterion, STdmax/MET, significantly enhances the diagnostic value of treadmill EET for detecting CAD in elderly patients. The adoption of this modified criterion could potentially improve clinical outcomes by facilitating more accurate and timely diagnosis of CAD in this high-risk group.

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