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BACKGROUND: The characteristics of electrocardiogram (ECG) abnormalities related to cardiac channelopathies potentially linked to sudden cardiac death (SCD) are not widely recognized in Iran. We examined the prevalence of such ECG patterns and their related factors among adult residents of Tehran, Iran. METHODS: The clinical characteristics and 12-lead ECGs of Tehran Cohort Study participants were examined. Long QT intervals, short QT intervals, Brugada syndrome (BrS) patterns, and early repolarization (ER) were evaluated using computer-based assessment software validated by cardiologists. Logistic regression models were employed to identify the factors associated with the prevalence of different ECG patterns. RESULTS: Out of 7678 available ECGs, 7350 were included in this analysis. Long QT interval, ER pattern, BrS patterns, and short QT interval were found in 3.08%, 1.43%, 0.31%, and 0.03% of participants, respectively. The prevalence of long QT interval increased with age, opium consumption, and presence of hypertension. Younger age, lower body mass index (BMI), alcohol use and male sex were independently linked to an elevated prevalence of ER pattern. Most individuals with BrS patterns were men (95%) and had lower BMI, high- and low-density lipoprotein, and total cholesterol compared to those without the BrS pattern. At a mean follow-up of 30.2 ± 5.5 months, all-cause mortality in the group exhibiting abnormal ECG patterns (6.3%) was approximately twice as high as that in the group without such patterns (2.96%). CONCLUSION: Abnormal ECG patterns corresponding to channelopathies were relatively rare among adult residents of the Tehran population, and their prevalence was influenced by various factors. CLINICAL TRIAL NUMBER: Not applicable.

BackgroundAccurate and timely diagnosis and effective prognosis of the disease is important to provide the best possible care for patients with COVID-19 and reduce the burden on the health care system. Machine learning methods can play a vital role in the diagnosis of COVID-19 by processing chest x-ray images. ObjectiveThe aim of this study is to summarize information on the use of intelligent models for the diagnosis and prognosis of COVID-19 to help with early and timely diagnosis, minimize prolonged diagnosis, and improve overall health care. MethodsA systematic search of databases, including PubMed, Web of Science, IEEE, ProQuest, Scopus, bioRxiv, and medRxiv, was performed for COVID-19–related studies published up to May 24, 2020. This study was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. All original research articles describing the application of image processing for the prediction and diagnosis of COVID-19 were considered in the analysis. Two reviewers independently assessed the published papers to determine eligibility for inclusion in the analysis. Risk of bias was evaluated using the Prediction Model Risk of Bias Assessment Tool. ResultsOf the 629 articles retrieved, 44 articles were included. We identified 4 prognosis models for calculating prediction of disease severity and estimation of confinement time for individual patients, and 40 diagnostic models for detecting COVID-19 from normal or other pneumonias. Most included studies used deep learning methods based on convolutional neural networks, which have been widely used as a classification algorithm. The most frequently reported predictors of prognosis in patients with COVID-19 included age, computed tomography data, gender, comorbidities, symptoms, and laboratory findings. Deep convolutional neural networks obtained better results compared with non–neural network–based methods. Moreover, all of the models were found to be at high risk of bias due to the lack of information about the study population, intended groups, and inappropriate reporting. ConclusionsMachine learning models used for the diagnosis and prognosis of COVID-19 showed excellent discriminative performance. However, these models were at high risk of bias, because of various reasons such as inadequate information about study participants, randomization process, and the lack of external validation, which may have resulted in the optimistic reporting of these models. Hence, our findings do not recommend any of the current models to be used in practice for the diagnosis and prognosis of COVID-19.

BACKGROUND: The prevalence and burden of substance and opium use have increased worldwide over the past decades. In light of rapid population changes in Tehran, we aimed to evaluate the prevalence of opium and other substance use among adult residents in Tehran, Iran. METHOD: From March 2016 to March 2019, we utilized data from 8 296 participants in the Tehran Cohort Study recruitment phase (TeCS). We calculated the age-sex-weighted prevalence of substance use and the geographic distribution of substance use in Tehran. We also used logistic regression analysis to determine possible determinants of opium use. RESULT: We analyzed data from 8 259 eligible participants with complete substance use data and the average age of participants was 53.7 ± 12.75 years. The prevalence of substance use was 5.6% (95% confidence interval [CI]: 4.6- 7.1%). Substance use was more common in males than females (Prevalence: 10.5% [95% CI: 8.6- 12.6%] vs. 0.5% [95% CI: 0.2- 1.2%], respectively). The age-sex weighted prevalence of substance use was 5.4% (95% CI: 4.6-7.1%). Moreover, opium was the most frequently used substance by 95.8% of substance users. Additionally, we found that male gender (Odds ratio [OR]: 12.1, P

BACKGROUND: Dyslipidemia is among the leading risk factors for cardiovascular diseases (CVDs), with an increasing global burden, especially in developing countries. We investigated the prevalence of dyslipidemia and abnormal lipid profiles in Tehran. METHODS: We used data from 8072 individuals aged≥35 from the Tehran Cohort Study (TeCS) recruitment phase. Fasting serum total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), and triglyceride were measured. Dyslipidemia was defined according to the National Cholesterol Education Program Adult Treatment Panel III criteria, and high LDL/HDL was defined as a ratio>2.5. The age-sex standardized prevalence rates were calculated based on the 2016 national census. Furthermore, the geographical distribution of dyslipidemia and lipid abnormalities was investigated across Tehrans zip code districts. RESULTS: The age-sex standardized prevalence was 82.7% (95% CI: 80.1%, 85.0%) for dyslipidemia, 36.9% (95% CI: 33.8%, 40.1%) for hypertriglyceridemia, 22.5% (95% CI: 19.9%, 25.4%) for hypercholesterolemia, 29.0% (95% CI: 26.1%, 32.1%) for high LDL-C, 55.9% (95% CI: 52.6%, 59.2%) for low HDL-C, and 54.1% (95% CI: 50.9%, 57.3%) for high LDL/HDL ratio in the Tehran adult population. The prevalence of dyslipidemia, low HDL-C, and high LDL/HDL ratio was higher in the northern regions, hypercholesterolemia was higher in the southern half, and high LDL-C was more prevalent in the middle-northern and southern areas of Tehran. CONCLUSION: We found a high prevalence of dyslipidemia, mainly high LDL/HDL in the Tehran adult population. This dyslipidemia profiling provides important information for public health policy to improve preventive interventions and reduce dyslipidemiarelated morbidity and mortality in the future.

The present study aimed to explore the malocclusion trends, sagittal skeletal discrepancies, and the index of orthognathic functional treatment need (IOFTN) scores in a sample of Iranian and Turkish orthognathic patients.

Hypertension (HTN) management continues to be a concern due to challenges with behavioral risk factors. Patient education to modify unhealthy behaviors appears to be effective in managing HTN. Therefore, this meta-analysis aimed to determine whether individualized face-to-face education and counseling have a beneficial effect on systolic and diastolic blood pressure (SBP and DBP) in hypertensive patients. Studies were extracted from PubMed, Scopus, Cochrane Library, and Web of Science databases. Nine studies, comprising 2627 participants, were included. Random effects models were used to pool estimates of mean differences (MDs) with 95% confidence intervals (CIs) in SBP and DBP between the intervention and usual care groups. SBP and DBP were significantly reduced at the 6-month (MD = -4.38 mmHg, 95% CI: -6.95 to -1.81; MD = -2.09 mmHg, 95% CI: -3.69 to -0.50, respectively) and 12-month time points (MD = -2.48 mmHg, 95% CI: -3.96 to -1.01; MD = -1.71 mmHg, 95% CI: -2.88 to -0.55, respectively) with intervention. At the 24-month time point, there was a significant change in SBP (MD = -2.13 mmHg, 95% CI: -3.94 to -0.32) with intervention compared with the usual care group. This study showed that individualized face-to-face education and counseling add significant benefits to usual care for lowering blood pressure in hypertensive patients.

Tobacco use is a major health concern worldwide, especially in low/middle-income countries. We aimed to assess the prevalence of cigarette smoking, waterpipe, and pipe use in Tehran, Iran. We used data from 8272 participants of the Tehran Cohort Study recruitment phase. Tobacco use was defined as a positive answer to using cigarettes, waterpipes, or pipes. Participants who did not report tobacco use during the interview but had a previous smoking history were categorized as former users. Age- and sex-weighted prevalence rates were calculated based on the national census data, and characteristics of current and former tobacco users were analyzed. Age- and sex-weighted prevalence of current tobacco users, cigarette smokers, waterpipe, and pipe users in Tehran was 19.8%, 14.9%, 6.1%, and 0.5%, respectively. Current tobacco use was higher in younger individuals (35-45 years: 23.4% vs. ≥ 75 years: 10.4%, P  12 years: 19.3% vs. illiterate: 9.7%, P

BackgroundThe prevalence of type 2 diabetes mellitus has increased in the past decades. We investigated the prevalence of diabetes and its awareness, treatment, and control among adult residents of Tehran.MethodsWe used the recruitment phase data of the Tehran Cohort study, enrolling a random sample of adult residents of Tehran aged ≥35 years. Diabetes was defined as self-report, current use of glucose-lowering medications, and/or fasting plasma glucose (FPG) ≥126mg/dl. Impaired fasting glucose (IFG) was defined as an FPG of 100-125mg/dl. Awareness was defined as diabetes self-report, treatment as receiving glucose-lowering medications, and glycemic control as FPG