Comparison of side effects of the dose-1 of AstraZeneca and Sinopharm vaccines in patients with multiple sclerosis in Kermanshah, Iran (2021).

Background: Coronavirus 2019 (COVID-19) vaccination is recommended for people with multiple sclerosis (MS). This study evaluated the side effects of Sinopharm and AstraZeneca vaccines in MS patients. Methods: In this cross-sectional study among MS patients in Kermanshah province, Iran, who received Sinopharm or AstraZeneca vaccine, sampling was performed through convenience sampling according to the nationwide MS registry of Iran (NMSRI). Demographic and clinical information of the participants and data on the side effects of vaccines were collected by telephone after the first dose. The data were analyzed in SPSS software. Results: 264 vaccinated MS patients (217 with Sinopharm and 47 with AstraZeneca) were studied. In the Sinopharm and AstraZeneca groups, respectively, 58.5% and 73.3% of patients had side effects that were not significantly different between the 2 groups (P = 0.064). In the AstraZeneca group, the severity of side effects and prevalence of taking painkillers were significantly higher (P < 0.050) and the interval between vaccination and side effects onset was significantly shorter (P = 0.013). The most commonly experienced side effects in the Sinopharm group were fatigue (29.0%), myalgia (24.9%), fever (24.0%), and headache (21.7%), and in the AstraZeneca group were fever (59.6%), chills (51.1%), myalgia (40.4%), and fatigue (34.0%). Logistic regression by controlling for confounding variables showed that considering some factors as confounding factors did not show a significant difference between the 2 vaccines in the experience of side effects (P = 0.104). Conclusion: The AstraZeneca vaccine caused more severe side effects in MS patients than the Sinopharm vaccine. Most of the side effects were moderate in severity and transient.

Prevalence of Multiple sclerosis and its clinical and demographic characteristics in Kurdish populations in western Iran (2020).

BACKGROUND: Multiple Sclerosis (MS) is a costly burdensome nervous system disorder leading several disabilities in young and middle-aged people. Knowing MS clinical, epidemiologic and demographic characteristics may help to estimate and predict the required health services and medication facilities for the affected people. This study was aimed to determine the prevalence of MS and its demographic characteristic in about 2 million Kurdish populations in western Iran in 2020. METHODS: This cross-sectional study was conducted in 2020 on MS patients with Kurdish Ethnicity living in Kermanshah /western Iran which is a Mountainous area in. MS patients were registered and recruited to this study from several centers. The settings have been approved by the nationwide MS registry of Iran (NMSRI). Using two questioners, a questionnaire included sex, age, the age in which the MS symptoms onset, the age of diagnosis, family history of MS, and type of MS, and second one was the Expanded Disability Status Scale (EDSS) checklist. The demographic information of Kermanshah province was adopted from the Statistical Center of Iran. In addition to descriptive statistics, U-Mann-Whitney and Chi-square tests were also used. RESULTS: A total of 1557 MS patients with a mean age (±SD) of 38.66 ± 9.9 years were recruited in this study. Of them, 1216 (78.1%) were female. The majority of patients, 300 patients (19.3%), were in the age range 35-39 years, and the highest prevalence (184.82 per 100,000 populations) was observed in the age range 40-44 years. The prevalence of MS in Kermanshah province is estimated 79.50 per 100,000 people, 125.71 per 100,000 in female and 34.41 per 100,000 in male. This prevalence was higher in female (female to male was 3.65 to 1). The EDSS score was significantly higher in male than in female (3.06 ± 2.2 in male versus 2.42 ± 1.8 in female) (p = 0.001). The type of MS was significantly different between male and female, so that SPMS and PPMS were more common in male (31(10.3%), 22(7.3%)) than female (81(7.5%), 39(3.6%)) (p = 0.012). A positive family history of MS was found in 12.6% of patients. CONCLUSION: Given the information about prevalence of MS in Kermanshah (in 2012), the prevalence of MS in Kermanshah has increased during last decade. MS disabilities were more extensive in male rather than female.

Modeling the risk factors for dyslipidemia and blood lipid indices: Ravansar cohort study.

BACKGROUND: Lipid disorder is one of the most important risk factors for chronic diseases. Identifying the factors affecting the development of lipid disorders helps reduce chronic diseases, especially Chronic Heart Disease (CHD). The aim of this study was to model the risk factors for dyslipidemia and blood lipid indices. METHODS: This study was conducted based on the data collected in the initial phase of Ravansar cohort study (2014-16). At the beginning, all the 453 available variables were examined in 33 stages of sensitivity analysis by perceptron Artificial Neural Network (ANN) data mining model. In each stage, the variables that were more important in the diagnosis of dyslipidemia were identified. The relationship among the variables was investigated using stepwise regression. The data obtained were analyzed in SPSS software version 25, at 0.05 level of significance. RESULTS: Forty percent of the subjects were diagnosed with lipid disorder. ANN identified 12 predictor variables for dyslipidemia related to nutrition and physical status. Alkaline phosphatase, Fat Free Mass (FFM) index, and Hemoglobin (HGB) had a significant relationship with all the seven blood lipid markers. The Waist Hip Ratio was the most effective variable that showed a stronger correlation with cholesterol and Low-Density Lipid (LDL). The FFM index had the greatest effect on triglyceride, High-Density Lipid (HDL), cholesterol/HDL, triglyceride/HDL, and LDL/HDL. The greatest coefficients of determination pertained to the triglyceride/HDL (0.203) and cholesterol/HDL (0.188) model with nine variables and the LDL/HDL (0.180) model with eight variables. CONCLUSION: According to the results, alkaline phosphatase, FFM index, and HGB were three common predictor variables for all the blood lipid markers. Specialists should focus on controlling these factors in order to gain greater control over blood lipid markers.

Association between dyslipidemia and blood lipids concentration with smoking habits in the Kurdish population of Iran.

BACKGROUND: Smoking is the most preventable cause of most chronic diseases such as cardiovascular disease (CVD). Dyslipidemia is also an important risk factor for CVD. Yet, research has provided contradicting findings regarding the association between smoking and blood lipids. This paper examines the relationship between dyslipidemia and smoking based on the results of a cross-sectional sample of a Kurdish population in western Iran. METHODS: This population-based study was derived from the recruitment phase of Ravansar Non-Communicable Disease (RaNCD) cohort study. Logistic regression model adjusted by confounding variables was used to determine the relationship between smoking and blood lipid components. In addition, dose-response relationship between blood lipids and the number of smoked cigarettes was evaluated. RESULTS: For the purpose of this study, 7586 participants were examined. The lifetime prevalence of smoking was 19.9%, and 11.8% were current smokers. The prevalence of dyslipidemia in current smokers (54.9%) was higher than former smokers (43.9%) and in turn former smokers higher than non-smokers (38.0%). Current smokers had greater risk of abnormal HDL cholesterol [OR (95% CI), 2.28(1.98 -2.62)] and triglyceride [OR (95% CI), 1.37(1.15 -1.67)] compared to non-smokers. There was no significant difference in total cholesterol and LDL cholesterol between the two groups. A dose-response relationship was found between the number of cigarettes smoked and HDL-C and TG but no relationship was observed in terms of total cholesterol and LDL-C. CONCLUSIONS: As compared to non-smokers, current smokers and former smokers had abnormal HDL-C and triglyceride and abnormal total cholesterol and triglyceride, respectively. After quitting smoking, heavy smokers showed a more normal HDL-C and total cholesterol levels than the people who tended to smoke a lower number of cigarettes per day.