Identifying Risk Indicators of Cardiovascular Disease in Fasa Cohort Study (FACS): An Application of Generalized Linear Mixed-Model Tree.

BACKGROUND: Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. METHODS: We used data from the baseline phase of the Fasa Cohort Study (FACS). The outcome variable was the presence of CVD. The ordinary Tree and generalized linear mixed models (GLMM) were fitted to the data and their predictive power for detecting CVD was compared with the obtained results from the GLMM tree. Statistical analysis was performed using the RStudio software. RESULTS: Data of 9499 participants aged 35‒70 years were analyzed. The results of the multivariable mixed-effects logistic regression model revealed that participants' age, total cholesterol, marital status, smoking status, glucose, history of cardiac disease or myocardial infarction (MI) in first- and second-degree relatives, and presence of other diseases (like hypertension, depression, chronic headaches, and thyroid disease) were significantly related to the presence of CVD (P<0.05). Fitting the ordinary tree, GLMM, and GLMM tree resulted in area under the curve (AUC) values of 0.58 (0.56, 0.61), 0.81 (0.77, 0.84), and 0.80 (0.76, 0.83), respectively, among the study population. In addition, the tree model had the best specificity at 81% but the lowest sensitivity at 65% compared to the other models. CONCLUSION: Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.

Virtual reality-based medical education versus lecture-based method in teaching start triage lessons in emergency medical students: Virtual reality in medical education.

INTRODUCTION: Epidemics such as the recent one, COVID-19, have caused a change in education and its methods. Virtual simulation is one of the types of technology used in medical education and related sciences. Virtual simulation provides practical and clinical medical education in a safe, cost-effective, reproducible, and flexible learning environment where students can practice over and over in a standard environment. This study was conducted to compare the effect of virtual-based medical education versus lecture-based method in teaching start triage lessons in emergency medical students in educational and medical centers affiliated to Birjand University of Medical Sciences Ferdows, Paramedical School, in 2020. METHODS: This is a quasi-experimental study. َAll 44 students of emergency medicine registered for triage course participated in the study. They were divided into two homogenous groups which were matched based on their grade point average. The simple triage and rapid transport (START) triage course was taught in the traditional way- lecture based- from the beginning of the semester to the middle of the semester; then, the other group (simulation-based) was trained in the second half of the same semester using virtual simulation. RESULTS: The students' rate of learning was measured by their scores at the end of the course exam in both groups. The mean scores of virtual simulation-based education were slightly higher than those of the lecture-based education, but it was not statistically significant (P>0.05). The students were more satisfied with virtual simulation-based education than the lecture-based and the difference between the mean scores of satisfaction was statistically significant (P>0.05). CONCLUSION: The results of this study suggest that VR can effectively improve knowledge in undergraduate emergency student's education, but it was not more effective than traditional educational methods. More experimental studies with a larger sample size are needed to confirm that virtual simulation-based education can more effectively improve knowledge in teaching practical lessons such as triage.

Clinical evaluation of SARS-CoV-2 lung HRCT and RT-PCR Techniques: Towards risk factor based diagnosis of infectious diseases.

This study uses image analysis techniques for comparative analysis of the lung HRCT features and RT-PCR of 325 suspected patients to COVID-19 pneumonia. Our findings propose more caution in the interpretation of RT-PCR data, promoting, instead, also the quantification of age and sex-based risk factors using HRCT images. Statistical analysis of our methodology reveals a direct relation between intensity, skewness and kurtosis of the radiological features and the gender of patients. Moreover, we investigate the effect of the age of patients on the appearance of COVID-19 pneumonia in the HRCT images. We have also applied our methodology to investigate the effect of time on the severity of COVID-19 pneumonia within the lungs. Subsequently, we find a strong relationship between image analysis and the informed medical diagnosis asserted by the radiologists. Additionally, our results also indicate increase in the severity of lung infection in the first and second week after the onset of the SARS-CoV-2 symptoms. Thereafter, a gradual decrease in the lung damage is observed during the third week. The proposed image analysis methodology can be used as a simple complementary tool for infectious disease diagnostics as demonstrated in this study with an example of SARS-CoV-2 to provide better understanding of the disease for drug and vaccine development.

The effect of melatonin on treatment of patients with non-alcoholic fatty liver disease: a randomized double blind clinical trial.

OBJECTIVES: Many factors implicated in the pathogenesis of non-alcoholic fatty liver disease (NAFLD) are including oxidative stress, insulin resistance and abnormal production of adipokines. The aim of this clinical trial was to evaluate the effect of melatonin supplement on some important biochemical markers and signs related to NAFLD. DESIGN: A randomized double-blind, placebo-controlled, clinical trial. SETTING: Twenty-four participants in the melatonin group and 21 participants in the placebo group completed the study. INTERVENTION: Participants received 6 mg melatonin or placebo daily, 1 h before bedtime. The intervention period was 12 weeks. MAIN OUTCOME MEASURES: Anthropometric measurements, systolic and diastolic blood pressure, liver enzymes, high sensitive C­reactive protein (hs-CRP), fatty liver grade, also leptin and adiponectin serum levels, were measured at the baseline and the end of intervention. RESULTS: A significant improvement was observed in weight (p = 0.043), waist circumference (p = 0.027), abdominal circumference (p = 0.043), systolic (p = 0.039), and diastolic (p = 0.015) blood pressure, leptin serum levels (p = 0.032), hs-CRP (p = 0.024), alanine aminotransferase (p = 0.011), aspartate aminotransferase (p = 0.034), also the grade of fatty liver (p = 0.020) in melatonin treated group compared with the placebo. CONCLUSIONS: Administration of 6 mg/day melatonin had improvement effect on many factors related to NAFLD such as liver enzymes, hs-CRP, anthropometric measurements, blood pressure, leptin serum levels and the grade of fatty liver.

The diagnostic precision of apparent diffusion coefficient (ADC) in grading of malignant endometrial lesions compared with histopathological findings.

OBJECTIVE: The present study aimed to extract apparent diffusion coefficient (ADC) values from the diffusion-weighted imaging (DWI) sequence of endometrial lesions and compare them with tissue specimen results in order to determine the precision of ADC values in grading of malignant endometrial lesions. METHODS: The present prospective study was conducted on 22 patients complaining of abnormal vaginal bleeding or evidence for endometrial thickening or masses detected using the ultrasound. Sampling was performed for pathological examination. MRI T2W+DWI+T1W+Post Contrast T1W were performed for patients. The statistical analysis was performed in SPSS 20 and MedCalc. RESULTS: In this study, although the mean ADC value was lower in patients with endometrial cancer than those with benign endometrial lesions, the difference was not significant (0.86 ± 0.2 mm2/sec versus 1.33 ± 0.53 mm2/sec; P = 0.13). Using the cutoff point of 0.53, the sensitivity and specificity of ADC value for differentiating benign and malignant lesions, respectively, equaled 90.91 and 9.09, with an equal positive and negative predictive value of 50%. In patients with endometrioid adenocarcinoma, mean ADC value was 0.93 ± 0.15 in FIGO Grade I, and 0.76 ± 0.165 in FIGO Grade II. Based on the statistical test, no significant difference existed between the two groups in terms of ADC values. CONCLUSION: Results indicate that the use of a DWI sequence (ADC values) can prevent invasive measures in the diagnosis of benign endometrial lesions and the identification of malignant lesions with a high precision in many patients having accompanying diseases or other cases for which invasive measures cannot be used. Also, there is no significant difference in the mean ADC values between G1 and G2 of endometrioid carcinoma.