ABSTRACT
Background: Depression is associated with an increased risk of death in patients with coronary heart disease (CHD). This study aimed to explore the factors influencing depression in elderly patients with CHD and to construct a prediction model for early identification of depression in this patient population. Materials and methods: We used propensity-score matching to identify 1,065 CHD patients aged ≥65 years from four hospitals in Chongqing between January 2015 and December 2021. The patients were divided into a training set (n = 880) and an external validation set (n = 185). Univariate logistic regression, multivariate logistic regression, and least absolute shrinkage and selection operator regression were used to determine the factors influencing depression. A nomogram based on the multivariate logistic regression model was constructed using the selected influencing factors. The discrimination, calibration, and clinical utility of the nomogram were assessed by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) and clinical impact curve (CIC), respectively. Results: The predictive factors in the multivariate model included the lymphocyte percentage and the blood urea nitrogen and low-density lipoprotein cholesterol levels. The AUC values of the nomogram in the training and external validation sets were 0.762 (95% CI = 0.722-0.803) and 0.679 (95% CI = 0.572-0.786), respectively. The calibration curves indicated that the nomogram had strong calibration. DCA and CIC indicated that the nomogram can be used as an effective tool in clinical practice. For the convenience of clinicians, we used the nomogram to develop a web-based calculator tool (https://cytjt007.shinyapps.io/dynnomapp_depression/). Conclusion: Reductions in the lymphocyte percentage and blood urea nitrogen and low-density lipoprotein cholesterol levels were reliable predictors of depression in elderly patients with CHD. The nomogram that we developed can help clinicians assess the risk of depression in elderly patients with CHD.
ABSTRACT
OBJECTIVE: Many studies have analyzed the association between the catechol-O-methyltransferase (COMT) Val158Met polymorphism and Parkinson's disease (PD), which yield inconsistent results. This meta-analysis was designed to determine the possible association between the COMT Val158Met polymorphism and the risk of PD in different populations. METHODS: The PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure and Chinese Biology Medicine databases were used for literature searching up to May 2018. The association between the COMT Val158Met polymorphism and the risk of PD was evaluated by calculating the pooled odds ratio (OR) and 95% confidence intervals (CIs). RESULTS: A total of 27 studies including 10,239 PD patients and 15,538 controls were screened out. In the overall population, COMT Val158Met polymorphism was not significantly associated with the risk of PD. In the subgroup analysis stratified by ethnicity, a significant association between COMT Val158Met polymorphism and PD risk was detected in Japan (LL vs. HH: OR = 1.48, 95% CI = 1.04-2.11; LL vs. HH+HL: OR = 1.54, 95% CI = 1.10-2.15) and India (LL+HL vs. HH: OR = 1.48, 95% CI = 1.14-1.91). CONCLUSION: This study indicated a significantly closer association between COMT Val158Met polymorphism and PD in the Japanese and Indian populations compared with other ethnicities. Ethnicity seems to play an important role in the genetic association of PD.
