sadegh amiri

The COVID-19 pandemic has had a devastating global impact, with millions of cases and varying severity of illness. Southeastern Iran has been particularly hard hit, with a high number of patients requiring hospitalization. This study aimed to identify risk factors associated with mortality from COVID-19 among hospitalized patients in this region.

A case-control study compared hospitalized COVID-19 patients who succumbed to the disease (confirmed by death certificates and positive PCR tests) with those who recovered, from February 27, 2020, to June 30, 2021. Researchers analyzed data using t-tests and chi-square tests to identify significant factors associated with mortality (p < 0.05). Variables significant at a less stringent level (p < 0.2) were then included in a backward logistic regression model to explore independent predictors of mortality.

This retrospective study examined data from 473 patients, of whom 158 were in the case group and 315 were in the control group. Among the case group, 80.4% were elderly, compared to 41% in the control group. A significantly higher proportion of patients in the case group (12.7%) experienced critical symptoms leading to ICU hospitalization, compared to the control group (7.3%). Multivariable regression analysis identified several factors significantly associated with increased mortality risk. These included ICU hospitalization (OR=5.27, CI: 3.09-8.98), advanced age (OR=4.06, CI: 2.43-6.80), hypertension (OR=4.44, CI: 1.52-12.93), cardiovascular diseases (OR=2.56, CI: 1.1-5.98), and critical symptoms (OR=2.74, CI: 1.92-8.04).  Diabetes, pregnancy, nationality, and gender did not statistically increase mortality risk (p-value ≥ 0.05).

Advanced age, severe symptoms requiring ICU care, hypertension, and cardiovascular diseases are all critical mortality risk factors in hospitalized COVID-19 patients.

In this paper, we propose a  fourth-order compact discretization method   for solving a second-order boundary value problem governed by the nonlinear Fredholm integro-differential equations.  Using an efficient approximate polynomial,  a  compact numerical integration method is first designed. Then by applying the derived numerical integration formulas, the original problem is converted into a nonlinear system of algebraic equations.  It is shown that the proposed method is easy to implement and has the third order of accuracy in the infinity norm. Some  numerical examples are presented to demonstrate its  approximation accuracy and computational efficiency,   as well as to compare the derived results with those  obtained in the literature.

The main purpose of this paper is to propose a high order numerical method based on the finite difference methods for solving nonlinear Itˆo stochastic Volterra integral equations (SVIEs) of the second kind. To develop the method, a fourth-order implicit finite difference method and the explicit Milstein method are implemented for the discretization of non-stochastic and stochastic integral parts, respectively. To solve the original SVIEs, the proposed method has the deterministic fourth-order and strong stochastic first-order accuracy. The convergence analysis of the proposed method is proved. The finite difference method under consideration requires solving a 2×2 system of equations at each step for one-dimensional SVIE. Therefore, the proposed method is very simple to implement and does not require a lot of computational cost. Some numerical examples are prepared to indicate the verity and efficiency of the new method. Moreover, the comparative numerical results show that this method is more accurate than those existing methods given in the literature.

Due to the increase in public interest in the use of traditional and complementary medicine in various diseases, it is necessary in order to adopt a suitable policy that  know the extent of people's use, the type of use and the characteristics of the people. We aimed to determine the frequency and pattern of complementary and alternative medicine use and the reason of use among patients suffering from HIV/AIDS in Fasa city.

This research is a cross-sectional study that was conducted on 96 patients with HIV/AIDS at the behavioral disease counseling center in Fasa city. The sample size was determined by census. Two questionnaires were used to collect data: a researcher-made questionnaire to examine the frequency of complementary and alternative medicine use and other questionnaire was the Quality of Life of the World Health Organization for people with HIV (WHOQOL-HIV). The data analysis for this study involved the use of descriptive statistics, Chi-squared test, independent t-test, and logistic regression model.

Of 96 patients, 78.12% reported using traditional medicine. The most common used type were cupping and medicinal plants. Chamomile and thyme were the most popular herbs used. The most common reason for using chamomile was relaxation, and they often used thyme to increase the general health of the body.

It is necessary to implement appropriate policies and practical responses to increase traditional and complementary medicine use so these services are available safely, timely and with sufficient quality.

This research is based on Stuart Hall's theory of representation. By adopting this method, it intends to express the relationship between understanding the apocalypse and understanding the historical end with the conquest of Iran by Muslim Arabs according to the contents of Dēnkard's text. Thus, there is no meaningful proposition or belief outside the discourse of the Zoroastrian religion for the followers of that religion; And the causes of events are understood and interpreted in the context of the discourse rather than in the light of contemporary reality This discourse narrates the defeat of the Iranians and the conquest of Iranshahr with the hopeful elements of the end of the millennium, and the promised emergence and end of history.

According to statistical data, prostate cancer is the most prevalent tumor in men worldwide and is the second leading cause of cancer deaths among men in the United States. This cancer changes many factors in the blood of patients.

This study was designed to evaluate lysophosphatidic acid (LPA) levels in the serum of patients with prostate cancer.

After collecting blood samples from 20 healthy individuals and 20 patients with prostate cancer, serum was separated from each sample. Then, the enzyme-linked immunosorbent assay (ELISA) method was applied to measure the serum LPA. The obtained data were statistical analyzed by SPSS V. 24 software.

The results of this study showed that the mean BMI of the prostate cancer group was significantly lower than the control group (respectively 22.56 ± 0.53 and 24.49 ± 0.62) (P = 0.023); in addition, the LPA level (nmol/mL) in the serum of the patients was significantly higher than healthy subjects (respectively 2.714 ± 0.054 and 2.467 ± 0.097) (P = 0.037).

The results showed that the serum LPA levels increased in prostate cancer, suggesting that lysophosphatidic acid may be considered as a biomarker in this cancer and will take part in the adjustment of the prostate cancer cells functions as a paracrine/autocrine mediator. This will be involved in the initiation, progression, and metastasis of prostate cancer.