Comparison of Genetic Susceptibility to Coronary Heart Disease in the Hungarian Populations: Risk Prediction Models for Coronary Heart Disease.

Background and Aim: It was evaluated whether the integration of genetic risk scores (GRS-unweighted, wGRS-weighted) into conventional risk factor (CRF) models for coronary heart disease or acute myocardial infarction (CHD/AMI) could improve the predictive ability of the models. Methods: Subjects and data collected in a previous survey were used to perform regression and ROC curve analyses as well as to examine the role of genetic components. Thirty SNPs were selected, and genotype and phenotype data were available for 558 participants (general: N = 279 and Roma: N = 279). Results: The mean GRS (27.27 ± 3.43 vs. 26.68 ± 3.51, p = 0.046) and wGRS (3.52 ± 0.68 vs. 3.33 ± 0.62, p = 0.001) were significantly higher in the general population. The addition of the wGRS to the CRF model yielded the strongest improvement in discrimination among Roma (from 0.8616 to 0.8674), while the addition of GRS to the CRF model yielded the strongest improvement in discrimination in the general population (from 0.8149 to 0.8160). In addition to that, the Roma individuals were likely to develop CHD/AMI at a younger age than subjects in the general population. Conclusions: The combination of the CRFs and genetic components improved the model's performance and predicted AMI/CHD better than CRFs alone.

Prognostic Modelling Studies of Coronary Heart Disease-A Systematic Review of Conventional and Genetic Risk Factor Studies.

This study aims to provide an overview of multivariable prognostic modelling studies developed for coronary heart disease (CHD) in the general population and to explore the optimal prognostic model by comparing the models' performance. A systematic review was performed using Embase, PubMed, Cochrane, Web of Science, and Scopus databases until 30 November 2019. In this work, only prognostic studies describing conventional risk factors alone or a combination of conventional and genomic risk factors, being developmental and/or validation prognostic studies of a multivariable model, were included. A total of 4021 records were screened by titles and abstracts, and 72 articles were eligible. All the relevant studies were checked by comparing the discrimination, reclassification, and calibration measures. Most of the models were developed in the United States and Canada and targeted the general population. The models included a set of similar predictors, such as age, sex, smoking, cholesterol level, blood pressure, BMI, and diabetes mellitus. In this study, many articles were identified and screened for consistency and reliability using CHARM and GRIPS statements. However, the usefulness of most prognostic models was not demonstrated; only a limited number of these models supported clinical evidence. Unfortunately, substantial heterogeneity was recognized in the definition and outcome of CHD events. The inclusion of genetic risk scores in addition to conventional risk factors might help in predicting the incidence of CHDs; however, the generalizability of the existing prognostic models remains open. Validation studies for the existing developmental models are needed to ensure generalizability, improve the research quality, and increase the transparency of the study.

Death risk among COVID-19 patients with diabetes mellitus.

Deaths from COVID-19 are increasing in patients with comorbidities. One of the most common comorbidities is diabetes mellitus. The researchers wanted to see how having diabetes affected the mortality rate of COVID-19 participants. This investigation is a case control observational analytical study. Different types of people, called "cases," and "controls," complete the research sample. Each group had 68 responders, for a grand total of 136. Medical records from COVID-19 patients treated at Airlangga University Hospital, Surabaya, between March 2020 and September 2021 serve as the study's secondary data source. The purpose of this study's data analysis is to calculate an odds ratio. Patients with COVID-19 with concomitant diabetes mellitus had an increased risk of death, and this risk increased with age, gender, and COVID-19 symptoms. In contrast, education, occupation, and laboratory results were not significantly related to mortality among COVID-19 individuals with concomitant diabetes mellitus (GDA status). The results of this study show that COVID-19 patients with concomitant diabetes mellitus are at a higher risk of death if they are over the age of 65, if they are male, and if they have severe symptoms.