Publications by authors named "Mahdi Ravankhah"

Purpose: To assess changes in the thickness of macular sublayers in individuals taking hydroxychloroquine (HCQ) without any evident toxicity and to review the relevant literature.

Methods: This prospective case-control study examined 47 adults on HCQ without evident toxicity on spectral-domain optical coherence tomography (SD-OCT) and visual field tests, as well as 25 healthy controls. Macular thickness in different sublayers was measured using SD-OCT.

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Background: Numerous studies have explored the effects of L-arginine, whether administered in the form of a supplement or through infusion during cardioplegia, on cardiac and inflammatory markers in individuals undergoing coronary artery bypass grafting (CABG). However, these studies presented contradictory findings. Consequently, the objective of this study was to investigate the impact of l-arginine on these markers by analyzing available randomized controlled trials (RCTs).

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Objectives: The effects of alpha-lipoic acid (ALA) supplementation on cardiovascular-related factors have been evaluated in a number of randomized clinical trials, with different results. Thus, in this meta-analysis, the effects of ALA on blood levels of inflammatory, lipid, and hematological markers as well as anthropometric indices in patients with chronic kidney disease (CKD) were evaluated.

Methods: Five electronic databases were used to conduct a comprehensive search through October 2023.

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Background: Oxidative stress after ischemic stroke contribute to neuronal cell injury. Unhealthy and unbalanced dietary patterns can increase the risk of several diseases, including stroke and cardiometabolic ones. However, the association between dietary total antioxidant capacity (DTAC) of antioxidant and stroke is controversial.

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Introduction: The application of machine learning (ML) is increasingly growing in biomedical sciences. This study aimed to evaluate factors associated with type 2 diabetes mellitus (T2DM) and compare the performance of ML methods in identifying individuals with the disease in an Iranian setting.

Methods: Using the baseline data from Fasa Adult Cohort Study (FACS) and in a sex-stratified manner, we studied factors associated with T2DM by applying seven different ML methods including Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbours (KNN), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB) and Bagging classifier (BAG).

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