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Correction to: Effect of selenium supplementation on antioxidant markers: a systematic review and meta-analysis of randomized controlled trials

Hasani M, Djalalinia S, Khazdooz M, Asayesh H, Zarei M, Gorabi AM, et al.

Hormones (Athens), 2020 Sep;19(3):451.
PMID: 32613535 DOI: 10.1007/s42000-020-00224-8

The original version of this article, published on 10 December 2019 contained a mistake.
Effect of selenium supplementation on antioxidant markers: a systematic review and meta-analysis of randomized controlled trials

Hasani M, Djalalinia S, Khazdooz M, Asayesh H, Zarei M, Gorabi AM, et al.

Hormones (Athens), 2019 Dec 10.
PMID: 31820398 DOI: 10.1007/s42000-019-00143-3

AIM: The aim of this study is the systematic review and meta-analysis of controlled trial studies to assess the antioxidant effects of selenium (Se) supplementation.
METHODS: The systematic review and meta-analysis were performed according to the previously published protocol. The PubMed, Web of Sciences, and Scopus databases were meticulously searched for relevant data, without time or language restriction, up to June 1, 2017. All clinical trials which assessed the effect of Se supplementation on antioxidant markers, including oxidative stress index (OSI), antioxidant potency composite (APC) index, plasma malonaldehyde (MDA), total antioxidant capacity (TAC), antioxidant enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT)), and total antioxidant plasma (TAP), were included. The effect of Se supplementation on antioxidant markers was assessed using standardized mean difference (SMD) and 95% confidence interval (CI). The random-effect meta-analysis method was used to estimate the pooled SMD.
RESULTS: In total, 13 studies which assessed the effect of Se supplementation on antioxidant markers were included. The random-effect meta-analysis method showed that Se supplementation significantly increased GPX (SMD = 0.54; 95% CI = 0.21-0.87) and TAC (SMD = 0.39, 95% CI = 0.13, 0.66) levels and decreased MDA levels (SMD = - 0.54, 95% CI = - 0.78, - 0.30). The effect of Se supplementation on other antioxidant markers was not statistically significant (P > 0.05).
CONCLUSION: The findings showed that Se supplementation might reduce oxidative stress by increasing TAC and GPX levels and decreasing serum MDA, both of which are crucial factors for reduction of oxidative stress.
Effects of Zinc Supplementation on Cardiometabolic Risk Factors: a Systematic Review and Meta-analysis of Randomized Controlled Trials

Khazdouz M, Djalalinia S, Sarrafi Zadeh S, Hasani M, Shidfar F, Ataie-Jafari A, et al.

Biol Trace Elem Res, 2020 Jun;195(2):373-398.
PMID: 31494808 DOI: 10.1007/s12011-019-01870-9

The prevalence of cardiometabolic risk factors has been increasing worldwide. The results of reported studies on the effects of zinc supplementation on cardiometabolic risk factors are unequivocal. This systematic review and meta-analysis of randomized controlled trials was conducted to evaluate the effects of zinc supplementation on cardiometabolic risk factors. A systematic search was conducted through international databases (PubMed/Medline, Institute of Scientific Information, and Scopus) until December 2018 to include all randomized controlled trials (RCT), quasi-RCT, and controlled clinical trials which assessed the effect of zinc supplementation on cardiometabolic risk factors including lipid profile, glycemic indices, blood pressure, and anthropometric indices. Random- or fixed-effects meta-analysis method was used to estimate the standardized mean difference (SMD) and 95% confidence interval (CI). A total of 20 studies were included in the meta-analysis, which included a total of 1141 participants in the intervention group. Meta-analysis showed that zinc supplementation significantly decreased plasma levels of triglyceride (SMD - 0.66, 95% CI - 1.27, - 0.06), very-low-density lipoprotein (SMD - 1.59, 95% CI - 2.86, - 0.31), and total cholesterol (SMD - 0.65, 95% CI - 1.15, - 0.15). Similarly, zinc supplementation significantly decreased fasting blood glucose (SMD - 0.52, 95% CI - 0.96, - 0.07) and HbA1c (SMD - 0.64, 95% CI - 1.27, - 0.02). The effects of zinc supplementation on blood pressure and anthropometric indices were not statistically significant (P > 0.05). Zinc supplements had beneficial effects on glycemic indices and lipid profile. Thus, it appeared that zinc supplementation might be associated with a decrease in cardiometabolic risk factors contributing to a reduction in risk of atherosclerosis.
Fulltext Neck circumference and its association with cardiometabolic risk factors: a systematic review and meta-analysis

Ataie-Jafari A, Namazi N, Djalalinia S, Chaghamirzayi P, Abdar ME, Zadehe SS, et al.

Diabetol Metab Syndr, 2018;10:72.
PMID: 30288175 DOI: 10.1186/s13098-018-0373-y

Background: Recently, neck circumference (NC) has been used to predict the risk of cardiometabolic factors. This study aimed to perform a systematic review and meta-analysis to examine: (i) the sensitivity (SE) and specificity (SP) of NC to predict cardiometabolic risk factors and (ii) the association between NC and the risk of cardiometabolic parameters.
Methods: A systematic search was conducted through PubMed/Medline, Institute of Scientific Information, and Scopus, until 2017 based on the search terms of metabolic syndrome (MetS) and cardio metabolic risk factors. Random-effect model was used to perform a meta-analysis and estimate the pooled SE, SP and correlation coefficient (CC).
Results: A total of 41 full texts were selected for systematic review. The pooled SE of greater NC to predict MetS was 65% (95% CI 58, 72) and 77% (95% CI 55, 99) in adult and children, respectively. Additionally, the pooled SP was 66% (95% CI 60, 72) and 66% (95% CI 48, 84) in adult and children, respectively. According to the results of meta-analysis in adults, NC had a positive and significant correlation with fasting blood sugar (FBS) (CC: 0.16, 95% CI 0.13, 0.20), HOMA-IR (0.38, 95% CI 0.25, 0.50), total cholesterol (TC) (0.07 95% CI 0.02, 0.12), triglyceride (TG) concentrations (0.23, 95% CI 0.19, 0.28) and low density lipoprotein cholesterol (LDL-C) (0.14, 95% CI 0.07, 0.22). Among children, NC was positively associated with FBS (CC: 0.12, 95% CI 0.07, 0.16), TG (CC: 0.21, 95% CI 0.17, 0.25), and TC concentrations (CC: 0.07, 95% CI 0.02, 0.12). However, it was not significant for LDL-C.
Conclusion: NC has a good predictive value to identify some cardiometabolic risk factors. There was a positive association between high NC and most cardiometabolic risk factors. However due to high heterogeneity, findings should be declared with caution.