Epidemic size, trend and spatiotemporal mapping of SARS-CoV-2 using geographical information system in Alborz Province, Iran.

BACKGROUND: The first confirmed cases of COVID-19 in Iran were reported in Qom city. Subsequently, the neighboring provinces and gradually all 31 provinces of Iran were involved. This study aimed to investigate the case fatility rate, basic reproductive number in different period of epidemic, projection of daily and cumulative incidence cases and also spatiotemporal mapping of SARS-CoV-2 in Alborz province, Iran. METHODS: A confirmed case of COVID-19 infection was defined as a case with a positive result of viral nucleic acid testing in respiratory specimens. Serial interval (SI) was fitted by gamma distribution and considered the likelihood-based R0 using a branching process with Poisson likelihood. Seven days average of cases, deaths, doubling times and CFRs used to draw smooth charts. kernel density tool in Arc GIS (Esri) software has been employed to compute hot spot area of the study site. RESULTS: The maximum-likelihood value of R0 was 2.88 (95%, CI: 2.57-3.23) in the early 14 days of epidemic. The case fatility rate for Alborz province (Iran) on March 10, was 8.33% (95%, CI:6.3-11), and by April 20, it had an increasing trend and reached 12.9% (95%,CI:11.5-14.4). The doubling time has been increasing from about two days and then reached about 97 days on April 20, 2020, which shows the slowdown in the spread rate of the disease. Also, from March 26 to April 2, 2020 the whole Geographical area of Karj city was almost affected by SARS-CoV-2. CONCLUSIONS: The R0 of COVID-19 in Alborz province was substantially high at the beginning of the epidemic, but with preventive measures and public education and GIS based monitoring of the cases,it has been reduced to 1.19 within two months. This reduction highpoints the attainment of preventive measures in place, however we must be ready for any second epidemic waves during the next months.

The risk factors associated with COVID-19-Related death among patients with end-stage renal disease.

BACKGROUND: The extent to which patients with End-stage renal disease (ESRD) are at a higher risk of COVID-19-related death is still unclear. Therefore, the aim of this study was to identify the ESRD patients at increased risk of COVID-19 -related death and its associated factors. METHODS: This retrospective cohort study was conducted on 74 patients with ESRD and 446 patients without ESRD hospitalized for COVID-19 in Alborz province, Iran, from Feb 20 2020 to Apr 26 2020. Data on demographic factors, medical history, Covid-19- related symptoms, and blood tests were obtained from the medical records of patients with confirmed COVID-19. We fitted univariable and multivariable Cox regression models to assess the association of underlying condition ESRD with the COVID-19 in-hospital mortality. Results were presented as crude and adjusted Hazard Ratios (HRs) and 95% confidence intervals (CIs). In the ESRD subgroup, demographic factors, medical history, symptoms, and blood parameters on the admission of survivors were compared with non-survivors to identify factors that might predict a high risk of mortality. RESULTS: COVID-19 patients with ESRD had in-hospital mortality of 37.8% compared to 11.9% for those without ESRD (P value < 0.001). After adjusting for confounding factors, age, sex, and comorbidities, ESRD patients were more likely to experience in-hospital mortality compared to non-ESRD patients (Adjusted HR (95% CI): 2.59 (1.55-4.32)). The Log-rank test revealed that there was a significant difference between the ESRD and non-ESRD groups in terms of the survival distribution (χ2 (1) = 21.18, P-value < 0.001). In the ESRD subgroup, compared to survivors, non-survivors were older, and more likely to present with lack of consciousness or O2 saturation less than 93%; they also had lower lymphocyte but higher neutrophil counts and AST concentration at the presentation (all p -values < 0.05). CONCLUSIONS: Our findings suggested that the presence of ESRD would be regarded as an important risk factor for mortality in COVID-19 patients, especially in those who are older than age 65 years and presented with a lack of consciousness or O2 saturation less than 93%.

Risk and predictors of in-hospital mortality from COVID-19 in patients with diabetes and cardiovascular disease.

BACKGROUND: Diabetes mellitus (DM) and cardiovascular disease (CVD) are present in a large number of patients with novel Coronavirus disease 2019 (COVID-19). We aimed to determine the risk and predictors of in-hospital mortality from COVID-19 in patients with DM and CVD. METHODS: This retrospective cohort study included hospitalized patients aged ≥ 18 years with confirmed COVID-19 in Alborz province, Iran, from 20 February 2020 to 25 March 2020. Data on demographic, clinical and outcome (in-hospital mortality) data were obtained from electronic medical records. Self-reported comorbidities were classified into the following groups: "DM" (having DM with or without other comorbidities), "only DM" (having DM without other comorbidities), "CVD" (having CVD with or without other comorbidities), "only CVD" (having CVD without other comorbidities), and "having any comorbidity". Multivariate logistic regression models were fitted to quantify the risk and predictors of in-hospital mortality from COVID-19 in patients with these comorbidities. RESULTS: Among 2957 patients with COVID-19, 2656 were discharged as cured, and 301 died. In multivariate model, DM (OR: 1.62 (95% CI 1.14-2.30)) and only DM (1.69 (1.05-2.74)) increased the risk of death from COVID-19; but, both CVD and only CVD showed non-significant associations (p > 0.05). Moreover, "having any comorbidities" increased the risk of in-hospital mortality from COVID-19 (OR: 2.66 (95% CI 2.09-3.40)). Significant predictors of mortality from COVID-19 in patients with DM were lymphocyte count, creatinine and C-reactive protein (CRP) level (all P-values < 0.05). CONCLUSIONS: Our findings suggest that diabetic patients have an increased risk of in-hospital mortality following COVID-19; also, lymphocyte count, creatinine and CRP concentrations could be considered as significant predictors for the death of COVID-19 in these patients.

Factors associated with the poor outcomes in diabetic patients with COVID-19.

PURPOSE: Diabetic's patients are supposed to experience higher rates of COVID-19 related poor outcomes. We aimed to determine factors predicting poor outcomes in hospitalized diabetic patients with COVID-19. METHODS: This retrospective cohort study included all adult diabetic patients with radiological or laboratory confirmed COVID-19 who hospitalized between 20 February 2020 and 27 April 2020 in Alborz province, Iran. Data on demographic, medical history, and laboratory test at presentation were obtained from electronic medical records. Diagnosis of diabetes mellitus was self-reported. Comorbidities including cancer, rheumatism, immunodeficiency, or chronic diseases of respiratory, liver, and blood were classified as "other comorbidities" due to low frequency. The assessed poor outcomes were in-hospital mortality, need to ICU care, and receiving invasive mechanical ventilation. Self-reported. Multivariate logistic regression models were fitted to quantify the predictors of in-hospital mortality from COVID-19 in patients with DM. RESULTS: Of 455 included patients, 98(21.5%) received ICU care, 65(14.3%) required invasive mechanical ventilation, and 79 (17.4%) dead. In the multivariate model, significant predictors of "death of COVID-19" were age 65 years or older (OR (95% CI): 2.0 (1.16-3.44), chronic kidney disease (CKD) (2.05 (1.16-3.62), presence of "other comorbidities" (2.20 (1.04-4.63)), neutrophil count ≥8.0 × 109/L)6.62 (3.73-11.7 ((, Hb level < 12.5 g/dl (2.05 (1.13-3.72) (, and creatinine level ≥ 1.36 mg/dl (3.10 (1.38-6.98)). (All p -values <0.05). Some of these factors were also associated with other assessed poor outcomes, e.g., need to ICU care or invasive mechanical ventilation. CONCLUSION: Diabetic patients with age 65 years or older, comorbidity CKD, "other comorbidities", as well as neutrophil count ≥8.0 × 109/L, Hb level < 12.5 g/dl, and creatinine level ≥ 1.36 mg/dl, were more likely to dead after COVID-19. Presence of hypertension and cardiovascular disease were associated with none of the poor outcomes.

Effect of selenium supplementation on glycemic indices: a meta-analysis of randomized controlled trials.

PURPOSE: The association between selenium supplementation and glycemic indices seems to be a controversial issue. This systematic review and meta-analysis was conducted to evaluate the effect of selenium supplementation on glycemic indices. METHODS: We systematically searched PubMed/MEDLINE, ISI/WOS, and Scopus (from their commencements up to Jan 2016) for relevant studies examining the association between intake of selenium and glycemic indices. The data were extracted from relevant qualified studies and estimated using the random-effect or pooled model and standardized mean difference (SMD) with 95% confidence interval (CI). RESULTS: Twelve articles published between 2004 and 2016 were included. In all the studies, the participants were randomly assigned to an intervention group (n = 757) or a control group(n = 684). All the studies were double blind, placebo controlled trials. Selenium supplementation resulted in a significant decrease in homeostasis model of assessment-estimated ß-cell function (HOMA-B) (SMD: -0.63; 95%CI: -0.89 to -0.38) and a significant increase in quantitative insulin sensitivity check index (QUICKI) (SMD: by 0.74; 95%CI: 0.49 to 0.1) as compared with the controls. There were no statistically significant improvements in glycemic indices, such as fasting plasma glucose (FPG), insulin, homeostasis model of assessment-estimated insulin resistance (HOMA-IR), Hemoglobin A1c (HbA1c) and adiponectin. CONCLUSION: This meta-analysis indicated that selenium supplementation significantly decreased HOMA-B and increased QUICKI score. There was no statistically significant improvement in FPG, insulin, HOMA-IR, HbA1c and adiponectin indices following selenium supplementation.