Background: Cardiovascular disease in particular acute coronary syndrome (ACS) is remained one of the most cause of morbidity and mortality, annually. Considering inflammatory pathway of atherosclerosis, colchicine as an anti-inflammatory drug is introduced to be effective in pathogenesis, prognosis and mortality rate of these patients. So in order to find out the effects of this drug we conducted this trial to know whether it reduces major adverse cardiac events (MACE) in ACS patients or not. Methods: In a prospective randomized double-blinded placebo-controlled trial, we enrolled ACS patients (40–70 years) with recent ST-segment elevation myocardial infarction (STEMI) or NSTE-ACS diagnosed by coronary angiography and managed with either medical therapy or percutaneous coronary intervention. Patients were assigned to two groups either receiving colchicine 0.5 mg daily or placebo for 6 months. Both groups simultaneously received standard medical therapy as accessible guidelines. MACE occurrence consists of decompensated heart failure, ACS, stroke and survival rate compared between two groups. Results: A total of 249 patients were recruited between October 2019-March 2020 with mean age of 56.89 ± 7.54, 69.5% males; 120 assigned to the colchicine group and 129 assigned to the placebo group. Over the 6 months’ period, 36 MACE occurred that were 8 events in the colchicine group compared with 28 events in the placebo group experiencing the event (P = 0.001). All of four deaths in the colchicine group and two in the placebo group were due to cardiovascular events. Evaluating adverse effects, gastrointestinal symptom was the most with the rate of 15 (12.5%) in the colchicine group and 3 (2.5%) in the controls. (P = 0.002). Conclusion: The addition of colchicine to standard medical therapy in ACS patients significantly reduces MACE occurrence and improves survival rate over the time.

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35–70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

Clinical scoring systems such as the HEART score can predict major adverse cardiovascular events, but they cannot be used to demonstrate the degree and severity of coronary artery disease. We investigated the potential of HEART Score in detecting the existence and severity of coronary artery disease based on SYNTAX score. This multi-centric cross-sectional study investigated patients referred to the cardiac emergency departments of three hospitals between January 2018 and January 2020. Data including age, gender, risk factors, comorbidities, 12-lead ECG, blood pressure and echocardiogram were recorded for all the participants. Serum troponin I level was measured on admission and 6 h later. Coronary angiography was done via the femoral or radial route. HEART and SYNTAX scores were calculated for all patients and their association was assessed. 300 patients (65% female) with mean age of 58.42 ± 12.42 years were included. mean HEART Score was 5.76 ± 1.56 (min = 3, max = 9), and mean SYNTAX score was 14.82 ± 11.42 (min = 0, max = 44.5). Pearson correlation coefficient was 0.493 between HEART Score and SYNTAX score which was statistically significant (P < 0.001). We found that HEART Score of more than 6 is 52% sensitive and 74.7% specific to detect extensive coronary artery involvement (SNTAX score ≥ 23). The present study showed that the HEART score has a moderate and positive correlation with the SYNTAX score and HEART score with a cut-off value of 6 is a predictor for SYNTAX score of ≥ 23.

Background: Electrocardiogram (ECG) remains an important medical diagnostic and screening tool. This study aimed to compare the effectiveness of online classes instead of traditional face-to-face or blended methods in medical students’ ECG learning.Methods: Two hundred and fifteen medical students (including 105 (48.8%) males and 110 (51.2%) females) were studied from February 2021 to February 2022. Regardless of their grade, participants were divided into three groups: online, face-to-face, and blended. Then all participants sat for an ECG interpretation exam, and their results were compared.Results: Twenty-six (12.1%) participants were residents, and 189 (87.9%) were interns. Thirty-five (16.3%), 85 (39.5%), and 95 (44.2%) participants were taught ECG through face-to-face, online, and blended methods, respectively. Regarding participants’ preferences on teaching methods, 118 (54.9%) preferred face-to-face learning, and the remaining 97 (45.1%) chose online learning (p < 0.001). The blended method seemed more promising in almost half of the exam questions regarding teaching method effectiveness. The mean total exam score was also significantly higher in participants who were taught blended than in the others (7.20 ± 1.89, p = 0.017). Face-to-face (5.97 ± 2.33) and online teaching methods (6.07 ± 2.07) had similar efficacy according to the mean total score (p = 0.819).Conclusion: While most students preferred face-to-face learning to online learning, a blended method seemed more promising regarding students’ skill enhancement to interpret ECG.

Background: Polypharmacy in patients with cardiovascular diseases (CVDs) has been linked to several adverse outcomes. This study aimed to investigate the pattern of medication use and prevalence of polypharmacy among CVDs patients in Iran. Method: We used the baseline data of the Pars cohort study (PCS). The participants were asked to bring their medication bags; then, the medications were classified using the Anatomical Therapeutic Chemical classification. Polypharmacy was defined as using five or more medications concurrently. Poisson regression modeling was applied. The adjusted prevalence ratios (PR) and its 95% confidence interval (CI) were estimated. Results: Totally, 9262 participants were enrolled in the PCS, of whom 961 had CVDs. The prevalence of polypharmacy in participants with and without CVDs was 38.9% and 7.1%, respectively. The highest prevalence of polypharmacy (51.5%) was among obese patients. Abnormal waist-hip ratio (PR: 2.79; 95% CI 1.57–4.94), high socioeconomic status (PR: 1.65; 95% CI 1.07–2.54), tobacco-smoking (PR: 1.35; 95% CI 1.00–1.81), patients with more than three co-morbidities (PR: 1.41; 95% CI 1.30–1.53), high physical activity (PR: 0.66; 95% CI 0.45–0.95), use of opiate ever (PR: 0.46; 95% CI 0.26–0.82), and healthy overweight subjects (PR: 0.22; 95% CI 0.12–0.39) were associated with polypharmacy. Cardiovascular drugs (76.1%), drugs acting on blood and blood-forming organs (50.4%), and alimentary tract and metabolism drugs (33.9%) were the most frequently used drugs. Agents acting on the renin-angiotensin system were the mostly used cardiovascular system drugs among men and those above 60 years old, while beta-blocking agents were mostly prevalent among cardiovascular system drugs in women with CVDs. Conclusion: Given the high prevalence of polypharmacy among CVDs patients, and subsequent complications, programs to educate both physicians and patients to prevent this issue is crucial.

Backgound: One of the known risk factors for hypertensive crisis (HTN‐C) is non‐steroidal anti‐inflammatory drugs (NSAIDs) which their adverse effects can lead to end‐organ damage such as gastrointestinal and cardiovascular issues.Aims: Data on the correlation between NSAIDs and HTN‐C are limited. In this study, we determined the prevalence of NSAID use among patients with HTN‐C.Materials & Methods: This cross‐sectional study was conducted among patients primarily diagnosed with HTN‐C referred to Alzahra hospital, Shiraz, Iran from April 2015 to April 2020. Demographic data, as well as information regarding the past medical and drug history and laboratory findings, were gathered retrospectively. The history of NSAID use was also asked specifically. The collected data were analyzed by SPSS and the P‐value less than .05 was considered significant.Results: A total of 257 patients with a mean age of 59.73 were enrolled in the study. Among them 62.6% were female and 137 patients (53.33%) used NSAIDs. Of all the patients 197 (76.7%), 71 (27.6%), and 46 (17.9%) suffered from concomitant hypertension (HTN), diabetes mellitus (DM), and ischemic heart disease (IHD) respectively. A significant relation was found between having each of the comorbidities and NSAIDs use among HTN‐C patients (P‐value <.0001). NSAIDs use was also significantly higher in older age (P‐value <.0001) and female gender (P‐value <.02). A high rate of NSAID use was seen among HTN‐C patients with a positive significant correlation to concomitant diseases, older age, and female gender.Conclusion: The Results of our study indicate that NSAIDs are frequently used among those with HTN‐C and considering the adverse effects of these medication our results further highlight the importance of monitoring and limiting NSAID use.