Introduction: This study aimed to explore the associations between constitutions of traditional Chinese medicine (TCM) and coronary artery disease (CAD). Methods: A large-scale, community-based, cross-sectional study was performed to investigate the associations. A total of 3,748 participants were available for analysis in this study. The assessment of the constitution of TCM was based on recommendations by the Association for Chinese Medicine in China. In this study, a diagnosis of CAD was based on self-reported medical history. The associations were analyzed using univariate and multivariable logistic regression (MLR). Results: Univariate analysis showed Phlegm–dampness, Qi-deficiency, Yang-deficiency and Yin-deficiency constitutions were significantly associated with CAD, respectively ([Formula: see text] for Phlegm–dampness, [Formula: see text] for Qi-deficiency, [Formula: see text] for Yang-deficiency and [Formula: see text] for Yin-deficiency). Furthermore, MLR demonstrated significant associations among the four constitutions and CAD, after controlling for potential confounding factors (Phlegm–dampness: [Formula: see text], [Formula: see text]; Qi-deficient: [Formula: see text], [Formula: see text], Yang-Deficient: [Formula: see text], [Formula: see text]; Yin-deficient: [Formula: see text], [Formula: see text]). As compared with Neutral participants, participants with the four constitutions of TCM had higher prevalence of CAD. Conclusion: Our findings provided evidence that the four constitutions of TCM including Phlegm-dampness, Qi-deficiency, Yan-deficiency and Yin-deficiency were significantly associated with CAD, respectively. (This study was registered in clinicaltrials.gov with the ID: NCT02998944.)
Background: We developed clinical risk models for predicting diabetic cardiovascular autonomic neuropathy (DCAN) in Chinese diabetic patients. Methods: A Chinese cohort of 455 diabetic participants underwent a short heart rate variability (HRV) test which was recruited between 2011 and 2013. Clinical risk models were developed that included independent and significant risk factors by using multiple variable stepwise regressions. These clinical risk models were tested in another independent cohort of Chinese individuals. Results: The clinical risk models included age, fasting plasma glucose, 2-h plasma blood glucose, triglycerides, resting HRs, and duration of diabetes mellitus. The area under the receiver-operating characteristic (ROC) curve of the study group was 0.794. In the model with the continuous variables, the area under the ROC curve was 0.810. A cutoff score of 12.54 which produced the optimal sensitivity (68.20%) and specificity (76.80%) and identified the percentage (35.77%) of the population that required subsequent testing. Conclusions: The clinical risk models showed high sensitivity and specificity for the prediction of DCAN in Chinese diabetic patients.
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