Red Cell Distribution Width as a Prognostic Indicator for Mortality and ICU Admission in Patients with COVID-19.

BACKGROUND: COVID-19 disease caused by the SARS-CoV-2 virus can lead to an acute respiratory illness with a high hospitalization and mortality risk. Therefore, prognostic indicators are essential for early interventions. As a component of complete blood counts, the coefficient of variation (CV) of red blood cell distribution width (RDW) reflects cellular volume variations. It has been shown that RDW is associated with increased mortality risk in a wide range of diseases. This study aimed to determine the relationship between RDW and mortality risk in COVID-19 patients. METHODS: This retrospective study was performed on 592 patients admitted to hospital between February 2020 and December 2020. Patients were divided into low and high RDW groups and the relationship between RDW and mortality, intubation, admission to intensive care unit (ICU), and need for oxygen therapy was investigated. RESULTS: The mortality rate in the low RDW group was 9.4%, while that in the high group was 20% (p < 0.001). Also, ICU admission in the low group was 8%, whereas this was 10% in the high RDW group (p = 0.040). The results of the Kaplan-Meyer curve showed that the survival rate was higher in the low group compared to the high RDW group. Cox results in the crude model showed that higher RDW values were directly related to increased mortality, although this was not significant after adjustment for other covariates. CONCLUSION: The results of our study reveal that high RDW is associated with increased hospitalization and risk of death and that RDW may be a reliable indicator of COVID-19 prognosis.

Prevalence and factors associated with poor sleep quality among nurses in COVID-19 wards.

The COVID-19 pandemic has significantly impacted the working conditions of nurses, leading to a detrimental effect on their sleep quality. This cross-sectional study aimed to investigate the prevalence of poor sleep quality and its associated factors among nurses working in COVID-19 wards in Kermanshah, Iran. A total of 97 nurses were selected through simple random sampling from COVID-19 wards. Data was collected using a demographic information sheet and the Pittsburgh Sleep Quality Index. Descriptive and inferential statistical methods, including chi-square and multiple logistic regression, were used for data analysis. The results showed that 74.2% (n = 72) of the nurses experienced poor sleep quality. Significant associations were found between poor sleep quality and work experience (p = 0.045) as well as the type of work shift (p = 0.001). However, no significant relationships were observed between poor sleep quality and factors such as age, sex, body mass index, overtime hours per month, physical activity, or underlying diseases. The high prevalence of poor sleep quality among nurses working in COVID-19 wards underscores the necessity of implementing targeted interventions to address this issue. In this regard, in addition to periodic shift schedule changes and reductions in working hours, it is necessary to adopt purposeful measures to improve working conditions and enhance the physical and mental health of nurses. These measures may include providing sufficient human resources to reduce the workload and fatigue of nurses, appropriate scheduling of working hours, and the implementation of stress management programs.

Survival rate and its predictors in HIV patients: A 15-year follow-up of 3030 patients.

BACKGROUND: The high prevalence of HIV infection and the deaths caused by it is one of the challenges for the healthcare systems throughout the world. In this study, we analyzed the survival of people living with HIV and co-infections, and related factors. METHODS: This retrospective cohort study was performed on 3030 people living with HIV admitted to Imam Khomeini Behavioral Disease Counseling Center, Tehran, Iran, during 2004-2018. Required data were obtained from the individuals' files. Kaplan Meier diagrams and Log-rank tests were used to assess the relationship between different factors and survival. In addition, Cox regression analysis was performed to determine the effective factors in HIV mortality. Data were analyzed using STATA software, version 14. RESULTS: The mean age of studied population was 43.2 ± 9.5 [years] and 77.3 % were male. Among the subjects, 3.2 % were infected with hepatitis B, 31.5 % with hepatitis C, and 13.9 % with Tuberculosis (TB). One, five, ten, and fifteen-year survival rates were 97.0 %, 93.0 %, 86.0 %, and 54.0 %, respectively. The mean survival time was 154.2 ± 0.9 months. Age more than 35, history of imprisonment, Unsafe sexual behavior, TB, and hepatitis C are independently associated with death in people living with HIV (p < 0.05). CONCLUSION: The survival of people living with HIV in the present study was in the favorable range compared to previous studies. However, co-infection with hepatitis C was associated with reduced survival of the subjects in this study. Therefore, it is suggested to detect and then prevent and control HCV co-infection to increase the survival of subjects.

The most important variables associated with death due to COVID-19 disease, based on three data mining models Decision Tree, AdaBoost, and Support Vector Machine: A cross-sectional study.

Introduction: Death due to covid-19 is one of the biggest health challenges in the world. There are many models that can predict death due to COVID-19. This study aimed to fit and compare Decision Tree (DT), Support Vector Machine (SVM), and AdaBoost models to predict death due to COVID-19. Methods: To describe the variables, mean (SD) and frequency (%) were reported. To determine the relationship between the variables and the death caused by COVID-19, chi-square test was performed with a significance level of 0.05. To compare DT, SVM and AdaBoost models for predicting death due to COVID-19 from sensitivity, specificity, accuracy and the area under the rock curve under R software using psych, caTools, random over-sampling examples, rpart, rpartplot packages was done. Results: Out of the total of 23,054 patients studied, 10,935 cases (46.5%) were women, and 12,569 cases (53.5%) were men. Additionally, the mean age of the patients was 54.9 ± 21.0 years. There is a statistically significant relationship between gender, fever, cough, muscle pain, smell and taste, abdominal pain, nausea and vomiting, diarrhea, anorexia, dizziness, chest pain, intubation, cancer, diabetes, chronic blood disease, Violation of immunity, pregnancy, Dialysis, chronic lung disease with the death of covid-19 patients showed (p < 0.05). The results showed that the sensitivity, specificity, accuracy and the area under the receiver operating characteristic curve were respectively 0.60, 0.68, 0.71, and 0.75 in the DT model, 0.54, 0.62, 0.63, and 0.71 in the SVM model, and 0.59, 0.65, 0.69 and 0.74 in the AdaBoost model. Conclusion: The results showed that DT had a high predictive power compared to other data mining models. Therefore, it is suggested to researchers in different fields to use DT to predict the studied variables. Also, it is suggested to use other approaches such as random forest or XGBoost to improve the accuracy in future studies.

Prevalence and reasons for self-medication for prevention of COVID-19 among the adult population in Kermanshah-Iran.

AIM: To determine the prevalence of self-medication and reasons for self-medication (SM) for the prevention/treatment of COVID-19 among the adult population. DESIGN: Cross-sectional study. METHODS: This study was performed on 147 adults in Kermanshah, Iran. Data were collected by a researcher-made questionnaire and analysed by SPSS-18 software using descriptive and inferential statistics. RESULTS: The prevalence of SM in the participants was 69.4%. Vitamin D and vitamin B complex were the most commonly used drugs. The most common symptoms leading to SM were fatigue and rhinitis. Strengthening the immune system and prevention of COVID-19 (48%) were the main reasons for SM. Factors related to SM included marital status [OR = 8.04, 95% CI = (3.62, 17.83)], education [OR = 0.16, 95%CI = (0.08, 0.35)] and monthly income [OR = 0.09, 95%CI = (0.03, 0.26)]. PATIENT OR PUBLIC CONTRIBUTION: Yes.

Predictors of care burden among caregivers of patients with COVID-19.

AIM: To explore predictors of care burden among the caregivers of patients with COVID-19. DESIGN: The findings of this cross-sectional study were presented in accordance with the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology statement. METHODS: The samples included 172 caregivers in Imam Reza and Farabi Hospitals, located in Kermanshah, Iran, who were enrolled in the study using convenience sampling. A demographic information form and the Caregiver Burden Inventory were administered. The data were collected between 13 May 202 and 20 August 2021. RESULTS: Of the caregivers, 62.8% (n = 108) were male and 71.5% (n = 123) were over 40 years old. Furthermore, 66.3% (n = 114) of caregivers had severe and very severe care burden, with a mean care burden of 78.9 ± 20.4 out of 120. A statistically significant difference was found between care burden and the variables of monthly income, health status, number of patients under care and residence status (p < 0.05). CONCLUSION: The caregivers experienced a high care burden, which can have harmful effects on them. Therefore, it is necessary to provide them with various forms of economic, psychological and social support.

Examining Lifestyle Components in Hospitalized COVID-19 Patients, Iran 2021.

Background: COVID-19 pandemic is a serious health threating element throughout the world. One of the key elements to strengthen the body's immune system is to follow a healthy lifestyle to deal with health threating. The aim of this study was to evaluate the lifestyle components in COVID-19 patients. Methods: This descriptive-analytical study carried on hospitalized COVID-19 patients from October 22, 2020 to January 19, 2021. Demographic characteristics, physical activity, nutritional status, stress and anxiety, and substance abuse were assessed. A simple model and multiple logistic regression model were used. Results: About 32% were hospitalized in the intensive care unit (ICU). Healthy lifestyle was observed only in 28%. About 82% had insufficient physical activity, and 67.3% was reported to be unfavorable in nutritional status. Severe stress and anxiety were observed in 30.4% of people. There were significant relationships between age (AOR = 2.11, p = 0.036), education (AOR = 0.35, p = 0.002) and a healthy lifestyle. A significant correlation was observed between ICU admission and unhealthy lifestyle (AOR = 0.40, p = 0.015). Conclusion: Unhealthy lifestyle behaviors were seen in the most COVID-19 patients. Considering the significance of lifestyle changes could prove effective in reducing the risk of transmissible viral infections.

The relationship of dietary total antioxidant capacity with sarcopenia and cardiometabolic biomarkers in type 2 diabetes patients.

BACKGROUND: The aim of this study was to investigate the relationship of dietary total antioxidant capacity (DTAC) with sarcopenia and metabolic biomarkers in people with type 2 diabetes in the Kurdish race. METHODS: In this cross-sectional study, data of 189 type 2 diabetic patients (35-65 years old) from RaNCD cohort study were evaluated. DTAC, fasting blood sugar, lipid profile, body composition, muscle strength, and sarcopenia were assessed. t and χ2 tests to compare the variables between sarcopenic and non-sarcopenic patients and one-way analysis of variance to compare the variables in DTAC tertiles were used. The relationship between DTAC and different variables was evaluated using multiple logistic regression model. RESULTS: The mean age and body mass index were 49.7 ± 8.7 years and 27.1 ± 3.9 kg/m2 . Body mass index, waist circumference, and hip circumference were significantly different between diabetic patients with and without sarcopenia (p < 0.05). In crude (p = 0.010) and adjusted (p = 0.035) models, there was a significant relationship between DTAC and fasting blood sugar. Also, the relationship between DTAC with waist (p = 0.019) and hip (ß = -4.25, p = 0.026) circumference was significant. Sarcopenia was significantly lower in the third tertile in comparison with the first tertile of DTAC (p = 0.016).  CONCLUSION: Diet with higher DTAC can be associated with lower fasting blood sugar, abdominal obesity and sarcopenia in type 2 diabetic patients. However, further studies are required to confirm these relationships.

Statin Use in COVID-19 Hospitalized Patients and Outcomes: A Retrospective Study.

Background: Coronavirus disease 2019 (COVID-19) might affect everyone, but people with comorbidities such as hypertension and cardiovascular disease (CVD) may often have more severe complications and worse outcomes. Although vaccinations are being performed worldwide, it will take a long time until the entire population of the world is vaccinated. On the other hand, we are witnessing the emergence of new variants of this virus. Therefore, effective therapeutic approaches still need to be considered. Statins are well-known lipid-lowering drugs, but they have also anti-inflammatory and immunomodulatory effects. This study aimed to investigate the effects of statins on the survival of COVID-19 hospitalized patients. Methods: This retrospective study was performed on 583 patients admitted to a highly referenced hospital in Tabas, Iran, between February 2020 and December 2020. One hundred sixty-two patients were treated with statins and 421 patients were not. Demographic information, clinical signs, and the results of laboratory, and comorbidities were extracted from patients' medical records and mortality and survival rates were assessed in these two groups. Results: The results of the Cox crude regression model showed that statins reduced mortality in COVID-19 patients (HR = 0.56, 95% CI: 0.32, 0.97; p = 0.040), although this reduction was not significant in the adjusted model (HRs=0.51, 95%CI: 0.22, 1.17; p = 0.114). Using a composite outcome comprising intubation, ICU admission, and mortality, both crude (HR = 0.43; 95% CI: 0.26, 0.73; p = 0.002) and adjusted (HR = 0.57; 95% CI: 0.33, 0.99; p = 0.048) models suggested a significant protective effect of statin therapy. Conclusion: Due to anti-inflammatory properties of statins, these drugs can be effective as an adjunct therapy in the treatment of COVID-19 patients.