Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background/Introduction Recent studies suggest chronotropic incompetence is statistically correlated with poor cardiometabolic health, systemic inflammation, and heart structural abnormalities. All may lead to exercise intolerance, impaired quality of life, and death due to cardiovascular disease (CVD). Unfortunately, there’s still a lack of data regarding which factors are associated with chronotropic incompetence. Purpose The purpose of this study was to identify the cardiometabolic risk factors, electrocardiographic (ECG), and echocardiographic (Echo) parameters that associated with chronotropic incompetence. Methods All patients who underwent cardiac treadmill stress test, ECG, and Echo in our hospital were included in this study, enrolled from 2018 until 2020. Patients were separated into two groups, patients with chronotropic incompetence and those without chronotropic incompetence. Chronotropic incompetence is defined as a maximum heart rate that can’t reach 85% age-predicted maximum heart rate. SPSS version 21 was used for data analysis. Pearson chi-square test was used to compare categorical variables based on clinical baseline characteristic, and cardiometabolic risk factors. We are using the Mann-Whitney U test to evaluate the association between ECG and Echo findings with chronotropic incompetence. Results Among 136 subjects of this study, the mean age was 54.7 years, 71.3% were male and 37.5% had chronotropic incompetence. Baseline characteristics and cardiometabolic factors such as T2DM (PR 2.29; 95%CI 1.16–3.37), HbA1C (PR 3.13; 95%CI 2.31-4.22), dyslipidemia (PR 1.773; 95%CI 1.170–2.687), total cholesterol (PR 2.396; 95%CI 1.650-3;481), and LDL (PR 1.853, 95%CI 1.229-2.794) were significantly associated with chronotropic incompetence (all p-value <0.05), while other factors were not significantly related. In ECG and Echo parameters, patients with chronotropic incompetence were found to had high Cornell product (1823.6±429.6vs1476.9±273.8), lower LVIDd (42.8±0.89 vs 45.2±0.72, p=0.029), lower LVIDi (24.6±0.37 vs 25.5±0.31, p=0.025), higher left ventricular mass (175.6±3.27 vs 125.1±2.63, p<0.001), higher E/E’ ratio (17.3±0.29 vs 13±0.35, p<0.001), and higher LAVI (47±1.98 vs 31.6±1.09, p<0.001) compared with patients without chronotropic incompetence. Conclusion(s) There are association between chronotropic incompetence with cardiometabolic factors and structural abnormalities that indicate increased LV filling pressure. The development of chronotropic incompetence may be predicted by assessing these factors
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