Search

Abstract Chronic kidney disease (CKD) is a non-communicable disease that includes a range of different physiological disorders causing abnormal renal function and progressive decline in the glomerular filtration rate (GFR). This study aimed to investigate the associations of several Environmental factors with CKD in the Iranian population. This is the second phase of a hospital-based case-control study, which was conducted on 700 participants (350 CKD cases and 350 controls, age and gender frequency matched). Multiple logistic regression was applied to measure the associations between the selected factors and CKD. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. All p-values were two-sided and the results were considered statistically significant at p

Background: Stroke is recognized as the second leading cause of death and the primary cause of disability in developing and underdeveloped countries. This study investigated the time trend of calls for suspected stroke received by the Emergency Medical Services (EMS) from 2013 to 2019 in Shiraz, Iran.Methods: This was a descriptive - ecological study using time series data. The necessary data were extracted from the Shiraz Emergency Medical Center from 2013 to 2019. Excel 2013 and SPSS (version 24.0) were used for data analysis. The results were then presented in figures and tables.Results: From 2013 to 2019, the EMS call center in Shiraz City received 844,004 calls, of which 6,620 were suspected stroke cases. The number of suspected stroke cases demonstrated a steady trend within a certain range from 2013 to 2016. However, there was a significant increase between 2016 and 2017, after which the number of stroke cases reached relative stability. In the short-term seasonal trend, we found that the number of suspected stroke cases reported to EMS was higher in cold seasons compared to warm seasons.Conclusion: The results showed that the long-term trend of reported suspected stroke cases to EMS is currently stable, following a previous increase in Iran.

Background: Brucellosis, a zoonotic disease, poses a significant health and economic challenge in many parts of the world, including Mediterranean and Middle Eastern countries. This study aimed to investigate the risk factors and recurrence of brucellosis, focusing on demographic variables such as age, gender, occupation, place of residence, and the spatiotemporal pattern of the population.Methods: The study design was cross-sectional.The authors enrolled all Brucella cases registered in the infectious disease surveillance system of Fars province from 2014 to 2018 in the study. They performed a multivariate analysis of the disease risk factors using a Poisson regression model and a multivariate analysis of the risk factors associated with brucellosis recurrence using a logistic regression model.Results: The incidence of brucellosis in Fars province exhibited a decreasing trend. The findings revealed that the sex ratio of patients who consumed unpasteurized dairy products, the mean age of patients per month, and the proportion of people living in rural areas relative to the total number of patients with brucellosis were significantly associated with the risk of brucellosis. Moreover, the probability of disease recurrence was higher in colder seasons compared to spring.Conclusion: A higher ratio of lightweight livestock to heavyweight livestock was identified as a risk factor for brucellosis, indicating the more significant role of lightweight livestock in the incidence of brucellosis in Fars province. Therefore, controlling the disease in lightweight livestock is of paramount importance, and the vaccination of these livestock should be more strictly monitored and implemented.

Purpose: Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs. Methods: This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages. Results: Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively. Conclusion: The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers.

Introduction Identifying patterns of human immunodeficiency viruses (HIV) transmission and factors affecting it can help to prevent and control the disease. The present study aimed to identify the latent classes of HIV risk factors in Iran. Material and methods This cross-sectional study was conducted among 32,168 HIV patients. We fitted latent class analysis by considering 11 indicators. Models with 2 to 5 classes were fitted, and the best-fitted model was chosen based on Acaik information critical (AIC), Bayesian information criterion (BIC), entropy, and interpretability of the results. Additionally, multinomial logistic regression model was applied to assess relationships between the covariates and latent class membership. Results We identified 3 latent classes, including low-risk (41.35%), high-risk (50.28%), and moderate-risk (8.37%) classes. The moderate-risk class was most likely prison history (69.09%) and addiction (67.37%). The high-risk class included addiction (99.68%), injection drugs users (IDUs) (99.06%), prison history (86.27%), and sharing needles (79.64%). Older age and being single increased the odds of membership in high-risk class (OR: 1.021, 95% CI: 1.017-1.024%; OR: 1.34, 95% CI: 1.20-1.50%), respectively, while older age increased the odds of membership in classes of moderate-risk (OR: 1.028, 95% CI: 1.023-1.033%) compared with low-risk group (p

Abstract Early initiation of Antiretroviral Treatment (ART) in HIV patients is essential for effectively suppressing the viral load and prognosis. This study utilized National HIV/AIDS Surveillance Data in Iran to identify factors associated factors with the duration to initiate ART. This hybrid cross-sectional historical cohort study was conducted on Iran’s National HIV/AIDS Surveillance Data from 2001 to 2019. Sociodemographic characteristics, route of transmission, HIV diagnosis date, and ART initiation date were collected. Multivariable linear and quantile regression models were employed to analyze the duration to initiate ART by considering predictor variables. This study included 17,062 patients (mean age 34.14 ± 10.77 years, 69.49% males). Multivariate quantile regression coefficients varied across different distributions of the dependent variable (i.e., duration to initiate ART) for several independent variables. Generally, male gender, injecting drug use (IDU), and having an HIV-positive spouse were significantly associated with an increased duration to initiate ART (p

Abstract Background and Aims Declines in estradiol levels after menopause have been reported to be associated with several health outcomes. This study aimed to determine the effect of age at natural menopause (ANM) on some of the most common chronic diseases. Methods This historical cohort study was performed on 2636 postmenopausal women aged 40–70 years participating in phase one of the PERSIAN cohort study in Kharameh, Iran, during 2015–2017. The effect of early (53 years) on chronic diseases such as hypertension, diabetes, ischemic heart diseases, stroke, thyroid diseases, and depression was assessed using classic logistic regression for diseases with an incidence rate of more than 10% and Firth's logistic regression for diseases with an incidence of less than this amount. Results The mean age of women was 53.48 ± 8.59. Respectively, early and intermediate menopause was associated with ischemic heart disease (odds ratio [OR = 1.61, 95% confidence interval [CI]: 1.08–2.42; p = 0.020), (OR = 1.57, 95% CI: 1.13–2.21; p = 0.008) and thyroid diseases (OR = 3.10, 95% CI: 1.64–6.24; p

Abstract Background Breast cancer (BC) is the most common cancer in the world, and is associated with significant economic costs for patients and communities. Therefore, the information on the costs of the disease and the identification of its underlying factors will provide insights into designing effective interventions and reducing the costs. Thus, the present study aimed to identify the factors affecting the economic burden of breast cancer from all medical centers providing diagnostic and treatment services in southern Iran. Methods A list of factors affecting the economic burden of breast cancer was obtained based on the effective factors searched in the databases, including PubMed, ProQuest, Scopus, ISI Web of Science, SID, and Magiran, and the opinions of BC cancer specialists. Then, the data on 460 breast cancer patients was collected from March 2020 to March 2022. The relationship between the factors affecting Breast Cancer costs was analyzed using SPSS 13.0 software by the use of multiple regression analysis. Results The results of the multiple regression analysis showed that stages (P-value

Abstract Background Breast cancer is one of the main causes of death from cancer around the world, imposing a significant economic burden on the families and healthcare system. The present study aimed at determining the economic burden of breast cancer in the patients referred to the medical centers in Fars province in southern Iran in 2021. Methods This cross-sectional study is a partial economic evaluation and a cost-of-illness study with a bottom-up and prevalence-based approach, conducted in Fars province in southern Iran in 2021 from the societal perspective. A total of 230 patients were randomly included in the study, and a researcher-made data collection form was used to collect the required data. The data on direct medical costs were collected using the information on patients’ medical and financial records. On the other hand, the data on direct non-medical and indirect costs were obtained using self-reports by the patients or their companions. The Excel 2016 software was used to analyze the collected data. Results The results showed that the annual cost of each breast cancer patient in the studied sample was 11,979.09 USD in 2021. Direct medical costs accounted for the largest share of costs (70.69%, among which the cost of radiotherapy was the highest one. The economic burden of the disease in the country was estimated at 193,090,952 USD. Conclusions In general, due to the high prevalence of breast cancer and the chronicity of this disease, its medical costs can impose a heavy economic burden on society, the health system, the insurance system, and patients. Thus, in order to reduce the costs, the following suggestions can be offered: the use of advanced radiotherapy techniques, increasing the insurance coverage of required services, establishing low-cost accommodation centers near medical centers for the patients and their companions, providing specialized medical services for the patients in towns, using the Internet and virtual space to follow up the treatment of the patients, and carrying out free screening programs and tests for faster diagnosis of the infected patients and susceptible or exposed people.

Background: The effectiveness of COVID-19 vaccination determines the resource allocation for saving lives in this pandemic. Certainly, the efficacy of all vaccines has been studied in laboratory situations. However, the present study aims to estimate the effectiveness of vaccination in real conditions of Iranian populations by controlling the effect of demographic factors and the history of chronic diseases.Methods: This historical cohort study used information on 1988 hospitalized COVID-19 patients with less than 93% blood oxygen levels. Cox regression, Survival Tree, and Forests were applied to estimate the effect of immunity from vaccination on survival, while the effect of demographic characteristics and history of chronic diseases was controlled.Results: The analysis showed that 10% of the patients were immunized, while the Sinopharm vaccine and the rest by Sputnik induced 86% of the immunity. Although there was no difference in the effectiveness of the vaccines, it was found that the immunity from each vaccine increased survival. Patient age was identified as the most influential factor in survival. Other contributing factors include the history of opium/smoking, cancer, the history of chronic lung disease, kidney disease, high blood pressure, and cardiovascular problems.Conclusion: Although age is the most influential factor in patient survival, immunity can control the risk of COVID-19. Therefore, it is recommended to prioritize the old and patients with any of the above underlying problems for vaccination and timely treatment.

Background: It is estimated that in 2025, the cost of diabetes will account for 40% of total health spending. In Iran, 4.5 to 5 million people are afflicted with diabetes, and its prevalence has doubled during the past three decades. The aim of this study was to determine the function and preparedness of diabetes surveillance system in Iran.Methods: In this cross-sectional study, all managers, health policymakers and experts of diabetes(N:125) entered the study and completed a questionnaire on the existence and implementation of the surveillance system domains (from data collection to evaluation) and the relationship between domains of this system and their function. The descriptive statistical method, path analysis, was employed using Amos.Results: A ccording t o m anager’s v iewpoint, t he r ange o f existence and implementation of all domains of surveillance system were 12% to 68.7% in average. They believed that 10-69% of domains of surveillance system were working properly. Most of respondents (59-87%) declared that investing in diabetes at different levels of prevention was less than expected. Satisfaction with both diabetes surveillance system function and diabetic patients was low and they don’t have a good and bright future for diabetes and its various aspects. By modeling analytical structural equations, some components of surveillance system were moderately worked together.Conclusion: we conclude that we must first formulate and prepare a standard surveillance system as well as train the relevant personnel and make clear changes in the existing care system. With the current surveillance system, we have a long way to go to prevent and control diabetes to an acceptable the average level of performance of the care system is lower than expected

BackgroundNatural menopause is defined as the permanent cessation of menstruation that occurs after 12 consecutive months of amenorrhea without any obvious pathological or physiological cause. The age of this phenomenon has been reported to be associated with several health outcomes.ObjectivesThis study aimed to estimate the Age at Natural Menopause (ANM) and to identify reproductive and demographic factors affecting ANM.MethodsThis cross-sectional, population-based study was conducted on 2517 post-menopausal women aged 40-70 years participating in the first phase of the PERSIAN cohort study of Kharameh, Iran, during 2014-2017. To more accurately detect the determinants of ANM, we applied multiple linear regression beside some machine learning algorithms including conditional tree, conditional forest, and random forest. Then, the fitness of these methods was compared using Mean Squared Error (MSE) and Pearson correlation coefficient.ResultsThe mean±SD of ANM was 48.95±6.13. Both applied forests provided more accurate results and identified more predictors. However, according to the final comparison, the conditional forest was the most accurate method which recognized that more pregnancies, longer breastfeeding, Fars ethnicity, and urbanization have the greatest impact on later ANM.ConclusionsThis study found a wide range of reproductive and demographic factors affecting ANM. Considering our findings in decision-making can reduce the complications related to this phenomenon and, consequently, improve the quality of life of post-menopausal women.

Abstract Background Cardiovascular diseases are the main cause of mortality in the world. This study aimed to estimate the incidence and identify the risk factors of these diseases. Methods This prospective cohort study was performed on 9442 individuals aged 40–70 years in Kharameh, a city in the South of Iran, in 2015–2022. The subjects were followed up for 4 years. The demographic information, behavioral habits, biological parameters, and history of some diseases were examined. The density incidence of cardiovascular disease was calculated. The log-rank test was calculated to assess the cardiovascular incidence difference between men and women. Simple and multiple Cox regression with Firth's bias reduction method were used to identify the predictors of cardiovascular disease. Results The mean ± SD age of the participants was 51.4 ± 8.04 years, and the density incidence was estimated at 1.9 cases per 100,000 person-day. The log-rank test showed that men had a higher risk of cardiovascular disease than women. The Fisher's exact test showed a statistically significant difference between the incidence of cardiovascular diseases in different age groups, education levels, diabetes, and hypertension in men and women. The results of multiple Cox regression revealed that with increasing age, the risk of developing CVDs increased. In addition, the risk of cardiovascular disease is higher in people with kidney disease (HRadj = 3.4, 95% CI 1.3 to 8.7), men (HRadj = 2.3, 95% CI 1.7 to 3.2), individuals with hypertension (HRadj = 1.6, 95% CI 1.3 to 2.1), diabetics (HRadj = 2.3, 95%c CI 1.8 to 2.9), and alcohol consumption (HRadj = 1.5, 95% CI 1.09 to 2.2). Conclusions In the present study, diabetes, hypertension, age, male gender, and alcohol consumption were identified as the risk factors for cardiovascular diseases; three variables of diabetes, hypertension and alcohol consumption were among the modifiable risk factors, so if they were removed, the incidence of cardiovascular disease could greatly reduce. Therefore, it is necessary to develop strategies for appropriate interventions to remove these risk factors.

Background: Reinfection with Coronavirus Diseases 2019 (COVID-19) has raised remarkable public health concerns globally. Therefore, the present retrospective cohort study intended to investigate COVID-19 reinfection in registered patients of Fars province in Iran from February 2020 to April 2021.Methods: The patients’ data, including the COVID-19 infection, symptoms, comorbidities, and demographics, were collected using the Health Information Systems (HISs). The patients were divided into three groups in terms of the duration between the initial infection and reinfection, including 28-44, 45-89, and more than 90 days. Following the univariate analysis, logistic regression was used to investigate the factors effective on COVID-19 reinfection. Results: A total of 213768 patients had a positive Polymerase Chain Reaction (PCR) test. The reinfection rate was 0.97% (2079 patients). Of these re-infected individuals, 14.9%, 18.5%, and 66.6% had their second positive test 28-45, 45-89, and ≥90 days later, respectively. The mean duration between the initial infection and reinfection was 130.56 days (29-370 days). The chance of reinfection was significantly higher in the youths (Odds Ratio (OR)=2.055; P

Abstract The goal of this study was to develop a predictive machine learning model to predict the risk of prolonged mechanical ventilation (PMV) in patients admitted to the intensive care unit (ICU), with a focus on laboratory and Arterial Blood Gas (ABG) data. This retrospective cohort study included ICU patients admitted to Rajaei Hospital in Shiraz between 2016 and March 20, 2022. All adult patients requiring mechanical ventilation and seeking ICU admission had their data analyzed. Six models were created in this study using five machine learning models (PMV more than 3, 5, 7, 10, 14, and 23 days). Patients’ demographic characteristics, Apache II, laboratory information, ABG, and comorbidity were predictors. This study used Logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), random forest (RF), and C.5 decision tree (C.5 DT) to predict PMV. The study enrolled 1138 eligible patients, excluding brain-dead patients and those without mechanical ventilation or a tracheostomy. The model PMV > 14 days showed the best performance (Accuracy: 83.63–98.54). The essential ABG variables in our two optimal models (artificial neural network and decision tree) in the PMV > 14 models include FiO2, paCO2, and paO2. This study provides evidence that machine learning methods outperform traditional methods and offer a perspective for achieving a consensus definition of PMV. It also introduces ABG and laboratory information as the two most important variables for predicting PMV. Therefore, there is significant value in deploying such models in clinical practice and making them accessible to clinicians to support their decision-making.

Abstract Background and Aims Hypertension and abnormal liver enzymes are common health issues that frequently coexist, and recent research has suggested a possible association between them, warranting further investigation. Therefore, the aim of this study is to explore the relationship between liver enzymes and hypertension. Methods This prospective cohort study utilized data from the Kharameh cohort study, which is a branch of the Prospective Epidemiological Studies in Iran (PERSIAN) database. The study included 7710 participants aged between 40 and 70 years. Hypertension was defined in accordance with the European guidelines for hypertension management, and the association between liver enzymes and hypertension was modeled and predicted using Firth logistic regression. Results This study investigated the association between liver enzymes and hypertension risk in a cohort of 7710 individuals aged 40–70 years. The results showed that higher levels of alanine aminotransferase (ALT), gamma glutamyl transferase (GGT), and alkaline phosphatase (ALP) were associated with an increased risk of hypertension, and this relationship remained significant even after adjusting for potential confounding factors. Additionally, separate analyses within age subgroups revealed a significant association between ALP concentration and high blood pressure in certain age ranges. Conclusion The study demonstrated a significant association between high levels of ALT, GGT, and ALP and an increased risk of hypertension, regardless of other risk factors. These results suggest that monitoring liver enzymes, specifically ALT, GGT, and ALP, could serve as a useful tool to predict hypertension risk and identify individuals who could benefit from early intervention. Overall, these findings underscore the importance of monitoring liver function in preventing and managing hypertension.

Abstract Background Osteoporosis, as the most common metabolic disease and the leading cause of death among older people, affects more than 200 million women throughout the world. This study aimed to evaluate the effect of a health communication campaign on knowledge, attitude, and practice of older women towards prevention and control of osteoporosis. Methods In this multi-stage mixed methods study, 30 days’ health communication campaign for prevention of osteoporosis was conducted on 60- 75-year-old women, in rural areas of Fasa, Iran. Subjects were divided into two groups, control (n = 103) and intervention (n = 98). Data were collected using a researcher-made questionnaire and analyzed by SPSS 25.0. The significance level was set at

Abstract Providing fresh blood to keep people in need of blood alive, has always been a main issues of health systems. Right policy-making in this area requires accurate forecasting of blood demand. The current study aimed at predicting demand for different blood groups in Shiraz using Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and a hybrid approaches. In the current time series analysis, monthly data of the Shiraz hospitals and medical centers demand for 8 blood groups during 2012–2019 were gathered from Shiraz branch of Iranian Blood Transfusion Organization. ARIMA, ANN and a hybrid model of them was used for prediction. To validate and comprise ARIMA and ANN models, Mean Square Error (MSE) and Mean Absolute Error (MAE) criteria were used. Finally, ARIMA, ANN and hybrid model estimates were compared to actual data for the last 12 months. R3.6.3 were used for statistical analysis. Based on the MSE and MAE of models, ARIMA had the best prediction for demand of all blood groups except O+ and O−. Moreover, for most blood groups, ARIMA had closer prediction to actual data. The demand for four blood groups (mostly negative groups) was increasing and the demand for other four blood groups (mostly positive ones) was decreasing. All three approaches including ARIMA, ANN and the hybrid of them predicted an almost downward trend for the total blood demand. Differences in the performance of various models could be due to the reasons such as different forecast horizons, daily/month/annual data, different sample sizes, types of demand variables and the transformation applied on them, and finally different blood demand behaviors in communities. Advances in surgical techniques, fetal screening, reduction of accidents leading to heavy bleeding, and the modified pattern of blood request for surgeries appeared to have been effective in reducing the demand trend in the current study. However, a longer time period would certainly provide more accurate estimates.

Abstract Background and Aim Prehypertension and hypertension are important risk factors for cardiovascular diseases. This study was carried out to evaluate the effect of prehypertension and hypertension on the development of cardiovascular diseases. Methods This prospective cohort study was performed on 9442 people aged 40−70 in Kharameh, southern Iran. Individuals were divided into three groups: normal blood pressure (N = 5009), prehypertension (N = 2166), and hypertension (N = 2267). In this study, demographic data, disease histories, behavioral habits, and biological parameters were studied. At first, the incidence density was calculated. Then Firth's Cox regression models were used to investigate the association between prehypertension and hypertension with the incidence of cardiovascular diseases. Results The incidence density in the three groups of individuals with normal blood pressure, prehypertension, and hypertension was 1.33, 2.02, and 3.29 cases per 100,000 person‐days, respectively. The results of multiple Firth's Cox regression by controlling all factors showed that the risk of occurrence of cardiovascular disease in people with prehypertension was 1.33 times (hazard ratio [HR] = 1.32, 95% confidence interval [CI]: 1.01−1.73, p = 0.03) and those with hypertension were 1.85 times higher (HR = 1.77, 95% CI: 1.38−2.29, p

ObjectiveDelayed diagnosis of HIV can lead to an inappropriate response to antiretroviral therapy (ART), rapid progression of the disease, and death. It can also carry harmful effects on public health due to the increment of transmission. This study aimed to estimate the duration of delayed diagnosis (DDD) in HIV patients in Iran.MethodsThis hybrid cross-sectional cohort study was conducted on the national HIV surveillance system database (HSSD). Linear mixed effect models with random intercept, random slope, and both were used to estimate the parameters required for the CD4 depletion model to determine the best-fitted model for DDD, stratified by the route of transmission, gender, and age group.ResultsThe DDD was estimated in 11,373 patients including 4,762 (41.87%) injection drug users (IDUs), 512 (4.5%) men who had sexual contact with men (MSM), 3,762 (33.08%) patients with heterosexual contacts, and 2,337 (20.55%) patients who were infected through other routes of HIV transmission. The total mean DDD was 8.41 ± 5.97 years. The mean DDD was 7.24 ± 0.08 and 9.43 ± 6.83 years in male and female IDUs, respectively. In the heterosexual contact group, DDD was obtained as 8.60 ± 6.43 years in male patients and 9.49 ± 7.17 years in female patients. It was also estimated as 9.37 ± 7.30 years in the MSM group. Furthermore, patients infected through other transmission routes were found with a DDD of 7.90 ± 6.74 years for male patients and a DDD of 7.87 ± 5.87 years for female patients.ConclusionA simple CD4 depletion model analysis is represented, which incorporates a pre-estimation step to determine the best-fitted linear mixed model for calculating the parameters required for the CD4 depletion model. Considering such a noticeably high HIV diagnostic delay, especially in older adults, MSM, and heterosexual contact groups, regular periodic screening is required to reduce the DDD.

Introduction: Altered immune responses, in particular neutrophil changes, are perceived to play a key role in immune responses to trauma. This study aimed to evaluate the association of neutrophil changes with patients’ survival in severe multiple trauma cases. Methods: The current retrospective cohort study was conducted using data from patients admitted in the intensive care unit (ICU) of a trauma center in Shiraz, Iran, between 2016 and 2021. Patients were divided into three groups (i.e., normal, neutropenia, and neutrophilia) based on neutrophil count at the time of ICU admission, and the association of neutrophil count with in-hospital mortality was analyzed. Results: 2176 patients with the mean age of 37.90 ± 18.57 years were evaluated (84.04% male). The median trauma severity based on injury severity score (ISS) in this series was 9 (4 -17). Patients were divided in to three groups of neutrophilia (n = 1805), normal (n = 357), and neutropenia (n = 14) There were not any significant differences between groups regarding age distribution (p = 0.634), gender (p = 0.544), and trauma severity (p = 0.197). The median survival times for the normal, neutropenia, and neutrophilia groups were 49 (IQR: 33 -47) days, 51 (IQR: 8- 51) days, and 38 (IQR: 26 - 52) days, respectively (p = 0.346). The log-rank test showed a statistically significant difference between the three groups adjustment for ISS (p ≤ 0.001). For each unit increase in ISS, the hazard ratio increased by 2%. In ISS 9-17, the hazard ratio increased by 11% compared to ISS17, the hazard ratio increased by 76% compared to ISS

Abstract Backgrounds SARS-CoV-2 is almost the most problematic virus of this century. It has caused extensive damage to various economic, social, and health aspects worldwide. Nowadays, coronavirus disease 2019 (COVID-19) is the most dangerous threat to human survival. Therefore, this study aimed to investigate factors associated with the survival of Iranian patients with SARS-CoV-2. Methods This retrospective hospital-based cohort study was conducted on 870 COVID-19 patients with blood oxygen levels of less than 93%. Cox regression and mixture cure model were used and compared to analyze the patients’ survival. It is worth noting that no similar study has been previously conducted using mixture cure regression to model the survival of Iranian patients with COVID-19. Result The cure rate and median survival time were respectively 81.5% and 20 days. Cox regression identified that respiratory distress, history of heart disease and hypertension, and older age were shown to increase the hazard. The Incidence and Latency parts of the mixture cure model respectively revealed that respiratory distress, history of hypertension, diabetes and cardiovascular diseases (CVDs), cough, fever, and older age reduced the cure odds; also, respiratory distress, history of hypertension, and CVDs, and older age increased the hazard. Conclusion The findings of our study revealed that priority should be given to older patients with a history of diabetes, hypertension, and CVDs in receiving intensive care and immunization. Also, the lower cure odds for patients with respiratory distress, fever, and cough favor early hospitalization before the appearance of severe symptoms.

Abstract Background Determining the risk of Cardiovascular Disease (CVD) is a necessity for timely preventive interventions in high-risk groups. However, laboratory testing may be impractical in countries with limited resources. This study aimed at comparison and assessment of the agreement between laboratory-based and non-laboratory-based WHO risk charts models. Methods This study was performed using the baseline data of 8138 participants in the pars cohort study who had no history of CVD and stroke. The updated 2019 WHO model was used to determine the 10-year fatal and non-fatal CVD risks. In general, there are two types of new WHO risk prediction models for CVD. The scores were determined based on age, sex, smoking status, diabetes, Systolic Blood Pressure (SBP), and total cholesterol for the laboratory-based model and age, sex, smoking status, SBP, and Body Mass Index (BMI) for the non-laboratory-based model. The agreement of these two models was determined via kappa statistics for the classified risk (low:

Abstract Background Chronic kidney disease (CKD) is a non-communicable disease that includes a range of different physiological disorders that are associated with abnormal renal function and progressive decline in glomerular filtration rate (GFR). This study aimed to investigate the associations of several behavioral and health-related factors with CKD in Iranian patients. Methods A hospital-based case-control study was conducted on 700 participants (350 cases and 350 controls). Logistic regression was applied to measure the association between the selected factors and CKD. Results The mean age of cases and controls were 59.6 ± 12.4 and 58.9 ± 12.2 respectively (p = 0.827). The results of multiple logistic regression suggested that many factors including low birth weight (OR yes/no = 4.07, 95%CI: 1.76–9.37, P = 0.001), history of diabetes (OR yes/no = 3.57, 95%CI: 2.36–5.40, P = 0.001), history of kidney diseases (OR yes/no = 3.35, 95%CI: 2.21–5.00, P = 0.001) and history of chemotherapy (OR yes/no = 2.18, 95%CI: 1.12–4.23, P = 0.02) are associated with the risk of CKD. Conclusions The present study covered a large number of potential risk/ preventive factors altogether. The results highlighted the importance of collaborative monitoring of kidney function among patients with the above conditions.

Introduction: Therapeutic Abortion (TA) has been defined as termination of pregnancy before the 20th week of gestation in order to save the mother’s life and prevent birth defects.The present study aimed to investigate the incidence of TA and its related maternal-fetal risk factors. Methods: This historical cohort study reviewed 11000 birth records. Among these reviewed records, 83 cases of TA were identified. Then, for each case, three controls of live infants born in the same hospital on the same day were selected and matched for gestational age. We used a researcher-made questionnaire for data collection. Results: The cumulative incidence of TA was computed 7.54 per 1000 live births. The results of multiple Cox regression model revealed that four risk factors including male gender; parental consanguinity; maternal diseases including gestational hypertension, gestational diabetes mellitus, hypothyroidism, infertility, the use of In Vitro Fertilization (IVF) and urinary tract infection; and maternal medication consumption increased the risk of TA (all hazard ratios > 1: p

Abstract Background Markov system dynamic (MSD) model has rarely been used in medical studies. The aim of this study was to evaluate the performance of MSD model in prediction of metabolic syndrome (MetS) natural history. Methods Data gathered by Tehran Lipid & Glucose Study (TLGS) over a 16-year period from a cohort of 12,882 people was used to conduct the analyses. First, transition probabilities (TPs) between 12 components of MetS by Markov as well as control and failure rates of relevant interventions were calculated. Then, the risk of developing each component by 2036 was predicted once by a Markov model and then by a MSD model. Finally, the two models were validated and compared to assess their performance and advantages by using mean differences, mean SE of matrices, fit of the graphs, and Kolmogorov-Smirnov two-sample test as well as R2 index as model fitting index. Results Both Markov and MSD models were shown to be adequate for prediction of MetS trends. But the MSD model predictions were closer to the real trends when comparing the output graphs. The MSD model was also, comparatively speaking, more successful in the assessment of mean differences (less overestimation) and SE of the general matrix. Moreover, the Kolmogorov-Smirnov two-sample showed that the MSD model produced equal distributions of real and predicted samples (p = 0.808 for MSD model and p = 0.023 for Markov model). Finally, R2 for the MSD model was higher than Markov model (73% for the Markov model and 85% for the MSD model). Conclusion The MSD model showed a more realistic natural history than the Markov model which highlights the importance of paying attention to this method in therapeutic and preventive procedures.

Background: An effective strategy for primary prevention of Cardiovascular Disease (CVD) is accurate diagnosis and the subsequent evidence-based treatment for high-risk people. This study aimed to estimate the 10-year risk of CVD and its related factors. Methods: The baseline data of 8138 participants of the Pars cohort study (PCS) in southern Iran were used. Risk scores were calculated using the updated 2019 WHO CVD risk prediction charts. The scores were determined based on age, gender, current smoking status, systolic blood pressure (SBP), diabetes status, and total serum cholesterol. Demographic and socioeconomic variables, physical activity, and anthropometric indices were measured and analyzed. Multivariable logistic regression was applied to estimate the adjusted odds ratio (aOR) and 95% confidence intervals (CI). Results: The mean (SD) age of the participants was 51.65 (9.06) years, and 53.44% were female. The 10-year CVD risk for 23.89% of participants was ≥10%. The prevalence of hypertension, diabetes, hypercholesterolemia, and smoking was 12.79%, 8.38%, 12.80%, and 14.41%, respectively. Having abdominal obesity, having low or moderate physical activity, being illiterate or having diplomas or lower degrees, and being in the third quartile of the wealth score group were associated with a higher 10-year risk of CVD. Conclusion: About one-fourth of the participants had moderate risk and higher. Due to the relatively high prevalence of CVD risk factors in the middle-aged population, the modifiable risk factors are recommended to be adjusted. Additionally, individual- and community-based educational policies are essential to create a healthy lifestyle.

Abstract The Framingham 10-year cardiovascular disease risk is measured by laboratory-based and non-laboratory-based models. This study aimed to determine the agreement between these two models in a large population in Southern Iran. In this study, the baseline data of 8138 individuals participated in the Pars cohort study were used. The participants had no history of cardiovascular disease or stroke. For the laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, systolic blood pressure (SBP) and treatment status, total cholesterol, and High-Density Lipoprotein. For the non-laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, SBP and treatment status, and Body Mass Index. The agreement between these two models was determined by Bland Altman plots for agreement between the scores and kappa statistic for agreement across the risk groups. Bland Altman plots showed that the limits of agreement were reasonable for females

Background: Insulin-dependent diabetes mellitus (IDDM) or type 1 diabetes mellitus (T1DM) is known as a chronic autoimmune disease with an increasing prevalence and incidence. This study was conducted to determine the incidence rate and prevalence of insulin-dependent diabetes in Iran in 2016 and 2017. Methods: In this cross-sectional study, the prevalence of IDDM in insured subjects under the age of 19 was measured through the prescribed insulin in two consecutive years. In this study, we assumed that IDDM patients are those who receive at least one prescription containing any insulin over 2 years in insurance databases. This study was carried out on 98% of patients under age 19, and the prevalence and incidence of IDDM were calculated. Finally, the result of this method was compared with Integrated Health System (IHS) databases. Results: In general, 1,135,105 insured persons under 19 years of age were enrolled in this study, and the prevalence rates of IDDM in subjects under 19 were 117.6 (111.5-124.2) and 136.8 (130.1-143.8) per 100,000 in 2016 and 2017, respectively. The incidence rate of this disease was 27.4 (24.6-30.8) per 100,000. The highest incidence and prevalence were significantly observed in the age group of 14-19 years. The prevalence of IDDM was not significantly different between boys and girls. Conclusion: The results of this study showed that the method of prescription follow up was appropriate, acceptable, convenient, and accurate. Our findings showed that the incidence and prevalence of IDDM in this method were in line with other worldwide reliable and accurate reports, even in the developed countries. The results of the present study showed that the prevalence and incidence rate of IDDM in Iran (Fars province) is at an intermediate level.

Background: One of the main health problems in the world is hepatitis B virus (HBV) infection. Vaccination and other factors can affect HBV infection. As various effective factors have been reported in different regions and studies, this study aimed to investigate the association between HBV infection and routine vaccination and other effective factors 25 years since the launch of the national vaccination program in Iran.Methods: This cross-sectional study, conducted in 2017 in Shiraz (Iran), investigated factors such as demographic variables such as gender, education, and occupation, vaccination status, and the potential risk factors for HBV infection. Hepatitis B surface antigen (HBsAg) and anti-hepatitis B core antibody (HBc Ab) tests were performed to determine HBV infection status. The data were analyzed using R software (version 3.5.2), using multivariate logistic regressions and machine learning methods. The level of significance was considered below 0.05.Results: A total of 2720 individuals were enrolled in the study (194 cases with HBV infection). Based on the logistic regression analyses, factors such as a family history of the disease (OR=2.53, p

Abstract Background The assessment of the natural history of metabolic syndrome (MetS) has an important role in clarifying the pathways of this disorder. Objective This study purposed to provide a rational statistical view of MetS progression pathway. Methods We performed a systematic review in accordance with the PRISMA Statement until September 2019 in the Medline/PubMed, Scopus, Embase, Web of Science and Google Scholar databases. From the 68 found studies, 12 studies were eligible for review finally. Results The selected studies were divided in 2 groups with Markovian and non-Markovian approach. With the Markov approach, the most important trigger for the MetS chain was dyslipidemia with overweight/obesity in the under-50 and with hypertension in the over-50 age group, where overweight/obesity was more important in women and hypertension in men. In non-Markov approach, the most common trigger was hypertension. Transition probability (TP) from no component to MetS were higher in all Markovian studies in men than in women. In the Markovians the combination of dyslipidemia with overweight/obesity and in non-Markovians, hyperglycemia with overweight/obesity were the most common combinations. Finally, the most important components, which predict the MetS, were 2-component states and hyperglycemia in Markovian approach and overweight/obesity in non-Markovians. Conclusions Among the components of the MetS, dyslipidemia and hypertension seems to be the main developer components in natural history of the MetS. Also, in this chain, the most likely combination over time that determines the future status of people seems to be the combination of dyslipidemia with obesity or hyperglycemia. However, more research is needed.

Background: This study aimed to assess the marginal adaptation and internal fit of cobalt-chromium copings fabricated by the selective laser melting (SLM) and conventional techniques using a profilometer. Materials and Methods: In this in vitro study sample size was calculated to be a total of 10 in two groups (n = 5). A brass model was used that had a circular cross-section with a round shoulder margin with 0.5 mm thickness and axial walls with 10 mm length and 6° taper. The copings fabricated with both techniques (SLM and casting method) were placed on the model, and vertical marginal gap was measured using a profilometer. The internal fit of copings was assessed by weighing the light-body addition silicone applied inside them, which simulated the cement. Data were analyzed through parametric (Independent t-test) and nonparametric (Mann–Whitney U-test, Bootstrap, Spearman, and Pearson Correlation) analysis. All analyses were performed at a significant level (α = 0.05) using SPSS. Results: The mean marginal gap in the casting group (132.93 ± ) was significantly higher than that in the SLM group (67.14 ± 15.67 μm) (P < 0.05). The mean weight of light-body silicone was 9.60 ± in the SLM and 8.70 ± 1.21 mg in the casting group. No significant difference was noted between the two groups regarding the internal fit (P > 0.05). Conclusion: The copings fabricated by the SLM technique showed a smaller vertical marginal gap compared to the casting group. However, the two groups were not significantly different in terms of internal fit.

Background: We aimed to estimate the exploratory factor analysis (EFA) of metabolic syndrome components based on variables including gender, BMI, and age groups in a population-based study with large sample size. Methods: This study was conducted on 10663 individuals 40-70 yr old in Phase 1 of the Persian Kharameh cohort study conducted in 2014-2017. EFA of the metabolic syndrome components, including waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), high-density lipoprotein (HDL) and fasting blood sugar (FBS), was performed on all participants by gender, BMI (Body Mass Index), and age groups. Results: EFA results in the whole population based on eigenvalues ​​greater than one showed two factors explaining 56.06% of the total variance. Considering factor loadings higher than 0.3, the first factor included: DBP, SBP, and WC, named as hypertension factor. The second factor also included TG, negative-loaded HDL, FBS, and WC, named as lipid factor. Almost similar patterns were extracted based on subgroups. Conclusion: MetS is a multi-factorial syndrome. Both blood pressure and lipid had a central role in this study and obesity was an important factor in both ones. Hypertension, having the highest factor loading, can generally be a valuable screening parameter for cardiovascular and metabolic risk assessment.

Objective: Type 2 diabetes is the most prevalent chronic disease in the world. Timely and appropriate control can significantly reduce the burdens and costs of this disease. Although insulin injection is the most efficient method to control type 2 diabetes, patients avoid this method for unknown reasons. The main aim of the present study is to determine the factors influential in non-adherence to insulin using tools and models that have not been applied in this field so far. Methods: The tendency to insulin injection in 457 patients with type 2 diabetes was investigated in this cross-sectional study using the classic logistic regression and new learning algorithms, including conditional tree, conditional forest, and random forest. Different fits were compared so that the best model can be determined to identify the factors in non-adherence to insulin. Results: Although random forest had the highest accuracy among the fitted models, all the methods had a relative consensus that having life insurance, academic education, and insulin injection experience in immediate family members increase the tendency to accept insulin therapy. Our results also showed that younger patients and those who were committed to a specific diet better approved insulin therapy. Conclusions: The reasons for non-adherence to insulin can be summarized in economic and psychological aspects. Therefore, the health system policies are recommended to address economic issues and also raise public awareness about this treatment method.

Background: Many patients with type 2 diabetes are uncontrolled on maximum oral treatment. The early introduction of insulin can lower diabetes-related complications. This study aimed to evaluate type 2 diabetes patients’ demographic characteristics, clinical factors, and attitude toward insulin therapy initiation. Methods: In the present cross-sectional study, 457 patients were selected from 12 diabetes clinics in the southern Iranian city of Shiraz in 2017. Adult patients (>30 y) with type 2 diabetes indicated to use insulin for the first time (insulin-naive) were asked to complete a researcher-designed questionnaire. The data were analyzed using SPSS 19. The relationships between insulin and the tendency to use insulin, demographic characteristics, and clinical data were evaluated using the χ2 or t test and logistic regression. The significance level was considered at 0.05. Results: The mean age of the participants was 55.16±8.76 years and 67.4% were female. Despite physician recommendations, 60.2% of the patients were disinclined to use insulin. Those unwilling to initiate insulin therapy had more misconceptions. In the multivariate analysis, the chances of insulin noncompliance were increased by 4.63-fold among the patients without supplementary insurance (P

Drinking water sources may be polluted by various pollutants depending on geological conditions and agricultural, industrial, and other human activities. Ensuring the safety of drinking water is, therefore, of a great importance. The purpose of this study was to assess the quality of drinking groundwater in Bardaskan villages and to determine the water quality index.Water samples were taken from 30 villages and eighteen parameters including calcium hardness (CaH), total hardness (TH), turbidity, pH, temperature, total dissolved solids (TDS), electrical conductivity (EC), alkalinity (ALK), magnesium (Mg2+), calcium (Ca2+), potassium (K+), sodium (Na+), sulphate (SO42−), bicarbonate (HCO3−), fluoride (F−), nitrate (NO3−), nitrite (NO2−) and chloride (Cl−) were analyzed for the purpose for this study. The water quality index of groundwater has been estimated by using the ANFIS. The spatial locations are shown using GPS. The results of this study showed that water hardness, electrical conductivity, sodium and sulfate in 66, 13, 45 and 12.5% of the studied villages were higher than the Iranian drinking water standards, respectively. Based on the Drinking Water Quality Index (DWQI), water quality in 3.3, 60, 23.3 and 13.3% of villages was excellent, good, poor and very poor, respectively. • Groundwater is one of the sources of drinking water in arid and semi-arid regions such as Bardaskan villages, which monitor the quality of these resources in planning for improving the quality of water resources. • The DWQI can clearly provide information associated with the status of water quality resources in Bardaskan villages. • The results of this study clearly indicated that with appropriate selection of input variables, ANFIS as a soft computing approach can estimate water quality indices properly and reliably. • Some parameters were in the undesirable level is some villages. Therefore, the government should try to improve the chemical and physical quality of drinking water in these areas with the necessary strategies. Protocol name: Estimation a water quality index in Bardaskan city, Keywords: Drinking water, WQI, Bardaskan villages, Iran

Qualitative fit testing is mandatory for tight-fitting respirators to ensure that the wearer fitted properly before entering a contaminated workplace. The purpose of this study was to evaluate the homemade solutions as substitution of commercial products for qualitative fit testing of particulate respirators. Two homemade solutions of Bitrex™ and saccharin were made according to the Occupational Safety and Health Administration (OSHA) regulation 29 CFR 1910.134. Threshold Screening Tests (TSTs) of commercial solutions, as well as homemade ones, were conducted on 62 participants in a random order. A placebo was also tested to assure the participants could distinguish its flavorless from other taste of solutions. There were no statistically significant differences between the commercial and homemade solutions representing that participants detected the bitter taste of the Bitrex™ and sweet taste of the saccharin solutions (96.8% vs. 91.9% and 93.5% vs. 83.9%, respectively). Homemade solutions that were stable and haven’t been contained microbial contaminations, could be substituted for commercial products in qualitative fit testing of filtering face-piece respirators (FFRs). Overall, this protocol presents a practical and cost-benefit technique to assess the fit testing of FFRs. Protocol name: Efficacy of homemade fit solutions as qualitative challenge agents for fit testing of filtering face-piece respirators (FFRs), Keywords: Qualitative fit test, Challenge agents, Commercial and homemade solutions, Filtering face piece respirators

Background: The outbreak of COVID-19 is rapidly spreading around the world and became a pandemic disease. For help to better planning of interventions, this study was conducted to forecast the number of daily new infected cases with COVID-19 for next thirty days in Iran. Methods: The information of observed Iranian new cases from 19th Feb to 30th Mar 2020 was used to predict the number of patients until 29th Apr. Artificial Neural Networks (ANN) and Auto-Regressive Integrated Moving Average (ARIMA) models were applied for prediction. The data was prepared from daily reports of Iran Ministry of Health and open datasets provided by the JOHN Hopkins. To compare models, dataset was separated into train and test sets. Mean Squared Error (MSE) and Mean Absolute Error (MAE) was the comparison criteria. Results: Both algorithms forecasted an exponential increase in number of newly infected patients. If the spreading pattern continues the same as before, the number of daily new cases would be 7872 and 9558 by 29th Apr, respectively by ANN and ARIMA. While Model comparison confirmed that ARIMA prediction was more accurate than ANN. Conclusion: COVID-19 is contagious disease, and has infected many people in Iran. Our results are an alarm for health policy planners and decision-makers, to make timely decisions, control the disease and provide the equipment needed.

Background & Objective: Today, Likert scale data is used in many studies in medical, educational, and psychometric fields to understand the attitudes of individuals. This study was conducted with the aim of correctly understanding how to design a Likert scale and to analyse the issues and challenges in determining the reliability and analysis of Likert scale data. Instruments & Methods: In the current review study, search engines such as PubMed, Google Scholar, and Science Direct were searched between May and August 2017. Based on the searched terms, 532 articles were primarily obtained; according to the inclusion and exclusion criteria of the study, eventually 60 articles were examined. Results: Using the 5-point scale is more common than other multi-choice options. Considering the option as intervals encourage people to answer the questions. While using Likert scale data, there are always decision-making challenges, especially when discussing the type of test to be used for parametric or non-parametric tests. If there is a presumption of the normalization of the distance data, independent t-test is used for the two separate groups. Conclusion: In most of the Likert scale studies that have been carried out so far, there is some confusion or disagreement with how to design, construct, and analyse its data. Ultimately, although there is no detailed and comprehensive agreement on the design and analysis of Likert data, this study, with a general summary in this regard, has greatly curtailed the confusion.