This trial aims to evaluate the effectiveness of adding melatonin to the treatment protocol of hospitalized coronavirus disease 2019 (COVID‐19) patients. This was an open‐label, randomized controlled clinical trial in hospitalized COVID‐19 patients. Patients were randomized into a treatment arm receiving melatonin plus standard care or a control arm receiving standard care alone. The trial's primary endpoint was sleep quality examined by the Leeds Sleep Evaluation Questionnaire (LSEQ). The trial's secondary endpoints were symptoms alleviation by Day 7, intensive care unit admission, 10‐day mortality, white blood cell count, lymphocyte count, C‐reactive protein status, and peripheral capillary oxygen saturation. Ninety‐six patients were recruited and allocated to either the melatonin arm (n = 48) or control arm (n = 48). Baseline characteristics were similar across treatment arms. There was no significant difference in symptoms on Day 7. The mean of the LSEQ scores was significantly higher in the melatonin group (p < 0.001). There was no significant difference in laboratory data, except for blood oxygen saturation, which has improved significantly in the melatonin group compared with the control group (95.81% vs. 93.65% respectively, p = 0.003). This clinical trial study showed that the combination of oral melatonin tablets and standard treatment could substantially improve sleep quality and blood oxygen saturation in hospitalized COVID‐19 patients.

Objectives: Breast cancer is known as one of the deadliest forms of cancer, and it is increasing globally. There are a variety of proven and controversial risk factors for this malignancy. Herein, we aimed to undertake a systematic review and meta-analysis focus on the epidemiology of breast cancer risk factors in Iran. Methods: We performed a systematic search via PubMed, Scopus, Web of Science, and Persian databases for identifying studies published on breast cancer risk factors up to March 2019. Meta-analyses were done for risk factors reported in more than one study. We calculated odds ratios (ORs) with corresponding 95% confidence intervals (CIs) using a fixed/random-effects models. Results: Thirty-nine studies entered into the meta-analysis. Pooling of ORs showed a significant harmful effect for risk factors including family history (OR: 1.80, 95%CI 1.47–2.12), hormonal replacement therapy (HRT) (OR: 5.48, 95%CI 0.84–1.74), passive smokers (OR: 1.68, 95%CI 1.34–2.03), full-term pregnancy at age 30 (OR: 3.41, 95%CI 1.19–5.63), abortion (OR: 1.84, 95%CI 1.35–2.33), sweets consumption (OR: 1.71, 95%CI 1.32–2.11) and genotype Arg/Arg (crude OR: 1.59, 95%CI 1.07–2.10), whereas a significant protective effect for late menarche (OR: 0.58, 95%CI 0.32–0.83), nulliparity (OR: 0.68, 95%CI 0.39–0.96), 13–24 months of breastfeeding (OR: 0.68, 95%CI 0.46–0.90), daily exercise (OR: 0.59, 95%CI 0.44–0.73) and vegetable consumption (crude OR: 0.28, 95%CI 0.10–0.46). Conclusions: This study suggests that factors such as family history, HRT, passive smokers, late full-term pregnancy, abortion, sweets consumption and genotype Arg/Arg might increase risk of breast cancer development, whereas late menarche, nulliparity, 13–24 months breastfeeding, daily exercise and vegetable consumption had an inverse association with breast cancer development.

Since numerous studies have stated that there may be a relationship between Helicobacter pylori infection and nonalcoholic fatty liver disease, and because of the high prevalence of both conditions worldwide, this study investigated the risk of non-alcoholic fatty liver disease in patients infected with H. pylori. Following a systematic review of PubMed, Scopus, Web of Science and Embase, and a search in Google Scholar using MeSH terms such as H. pylori and non-alcoholic fatty liver disease, the relevant papers up to November 2020 were reviewed. All cohort, case-control, and cross-sectional studies that examined the risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori entered this study. A meta-analysis was conducted in STATA 11. This systematic review examined 22 papers with 117 117 participants (33 711 patients infected with H. pylori and 83 406 participants as control) and 20 studies were subjected to meta-analysis The results indicated a 22% to 27% increase in the risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori (crude odds ratio: 1.27, 95% CI: 1.17-1.33; and adjusted odds ratio: 1.22, 95% CI: 1.09-1.35). According to the subgroup analysis, the study region, sample size, and the method of diagnosing H. pylori were the factors contributing to the high heterogeneity. The meta-analysis revealed the increased risk of developing non-alcoholic fatty liver disease in patients infected with H. pylori. This indicates that H. pylori is a serious risk factor in patients susceptible to NAFLD.

Background: Coronavirus Disease 2019 (COVID-19) has become a major global issue with rising the number of infected individuals and mortality in recent months. Among all therapeutic approaches, arguments have raised about hydroxychloroquine (HCQ) efficacy in the treatment of COVID-19. We carried out a systematic review and meta-analysis overcome the controversies regarding the effectiveness of hydroxychloroquine in the treatment of COVID-19. Methods: A systematic search was performed in PubMed, Scopus, Embase, Cochrane Library, Web of Science, Google Scholar and medRxiv pre-print database using all available MeSH terms for COVID-19 and hydroxychloroquine up to July 19, 2020. Studies focused on the effectiveness of HCQ with/without azithromycin (AZM) in confirmed COVID-19 patients were entered into the study. Two researchers have independently evaluated quality assessment of the studies and abstracted data for data extraction. Extracted data were analyzed using CMA v . 2.2.064. Heterogeneity was assessed using the I -squared ( I ² ) test, and fixed/random-effects model was used when appropriate for pooling of studies. Results: Out of 26 studies entered into our systematic review, 21 studies including 14 comparative studies with control group and seven observational studies containing 103,486 participants have entered into the meta-analysis. The results of the meta-analysis on comparative studies indicated no significant clinical effectiveness (negative in RT-PCR evaluation) for HCQ regimen in the treatment of COVID-19 in comparison to control group (RR: 1.03, 95% CI, 0.79-1.34). The same result was observed for the combination of HCQ+azithromycin (RR: 1.26, 95% CI, 0.91-1.74). No significant differences were found for both HCQ (RR: 0.92, 95% CI, 0.72-1.16) and HCQ+AZM (RR: 1.72, 95% CI, 0.86-3.42) mortality rate; however, mortality was affected by age differences according to meta-regression analysis (P<0.000001). No substantial difference was observed for disease exacerbation (RR: 1.23, 95% CI, 0.65-2.30) between HCQ group and controls. Also, radiological findings significantly improved in the HCQ group (OR: 0.32, 95% CI, 0.11-0.98). Odds of known HCQ adverse effects (diarrhea, vomiting, blurred vision, rash, headache, etc.) occurred in the HCQ regimen group was approximately 3.5 times of control group (OR: 3.40, 95% CI, 1.65-6.98), but no substantial differences were found regarding intubation odds between HCQ group and control group (OR: 2.11, 95% CI, 0.31-14.03). Meta-analysis indicated no significant prophylactic effects for HCQ (OR: 0.40, 95% CI, 0.04-3.65) Conclusion: This systematic review and meta-analysis showed no clinical benefits regarding HCQ treatment with/without azithromycin for COVID-19 patients. Although mortality rate was not significantly different between cases and controls, frequency of adverse effects was substantially higher in HCQ regimen group. However, due to that most of the studies were non-randomized and results were not homogenous, selection bias was unavoidable and further large randomized clinical trials following comprehensive meta-analysis should be taken into account in order to achieve more reliable findings. Also, it is worth mentioning that if this work does not allow to quantify a “value” of the HCQ, it allows at least to know what is not the HCQ and that it would be prudent not to continue investing in this direction.