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Objective. Quality of life (QoL) is a major concern in breast cancer (BC) patients. Despite efforts, no study has comprehensively addressed determinants of QoL in patients with BC. This study aimed to synthesize evidence on QoL correlations using the meta-analytic structural equation modeling (MASEM) approach. Methods. Our search in PubMed, Web of Science, Scopus, and Cochrane databases resulted in 5,238 initial relevant papers, 73 of which were eligible for final analysis with a total of 44,121 patients. We used a two-stage procedure of correlation-based MASEM to examine the relationship between QoL and body mass index (BMI), physical activity (PA), sleep, depression, fatigue, and stress. Results. Final MASEM model suggested that PA (path coefficient = 0.33, 95% CI = −0.0444; 0.6334), fatigue (path coefficient = −0.23, 95% CI = −0.6825; 0.0361), and stress (path coefficient = −0.22, 95% CI = −0.5143; 0.6875) were the most important factors related to QoL in patients with breast cancer. Final model identified variables responsible for 68% of the variation in QoL in BC. Conclusion. QoL is an important outcome in the treatment course of BC. Large-scale and meta-analysis studies could help patients to have a life with improved quality.

Background Considering that ablation of atypical AVNRT may be unsuccessful after ablation at the right posterior septum, in this study, we aimed to present an optimal method for ablation of atypical AVNRT. Also, we evaluated the efficacy of this technique for preventing recurrences. Methods This is a prospective, double-center study. It was conducted on 62 patients with atypical AVNRT referred for radiofrequency ablation. The patients were randomly divided into two groups before ablation: 1-Group A (n = 30): treated with conventional ablation at the anatomic area of the slow pathway; 2-Group B (n = 32): ablation was done 2 mm higher in the septum during fluoroscopy. Results The mean age of patients in groups A and B were 54 ± 11.7 and 55 ± 12.2, respectively (P = 0.43). In group A, ablation was successful in 24 (80%) patients following right-sided slow pathway ablation, and the remaining patients required further treatment with either a left-side approach (N = 4, 13.3%) or ablation of additional regions (N = 2, 6.7%). In group B, ablation was successful in all patients. After a 48-month follow-up, recurrence of symptomatic atypical AVNRT was detected in 4 (13.3%) patients of group A and none of group B patients (p Conclusion In patients with atypical AVNRT, ablation 2 mm above the conventional area is more promising regarding success rate and recurrence of the arrhythmia.

Clinical scoring systems such as the HEART score can predict major adverse cardiovascular events, but they cannot be used to demonstrate the degree and severity of coronary artery disease. We investigated the potential of HEART Score in detecting the existence and severity of coronary artery disease based on SYNTAX score. This multi-centric cross-sectional study investigated patients referred to the cardiac emergency departments of three hospitals between January 2018 and January 2020. Data including age, gender, risk factors, comorbidities, 12-lead ECG, blood pressure and echocardiogram were recorded for all the participants. Serum troponin I level was measured on admission and 6 h later. Coronary angiography was done via the femoral or radial route. HEART and SYNTAX scores were calculated for all patients and their association was assessed. 300 patients (65% female) with mean age of 58.42 ± 12.42 years were included. mean HEART Score was 5.76 ± 1.56 (min = 3, max = 9), and mean SYNTAX score was 14.82 ± 11.42 (min = 0, max = 44.5). Pearson correlation coefficient was 0.493 between HEART Score and SYNTAX score which was statistically significant (P

Introduction: We used machine learning methods to investigate if body composition indices predict hypertension. Methods: Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting and Stacking to classify the investigated cases and find the most relevant features to hypertension. Results: FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. Ensemble methods such as voting and stacking had the best performance for hypertension prediction. Stacking showed an accuracy rate of 79%. Conclusion: By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with an acceptable accuracy.

This paper presents a study on charged black holes in quintic quasi-topological gravity, where we construct numerical solutions and investigate their thermodynamics and conserved quantities. We verify the first law of thermodynamics and compare our findings with that of Einstein gravity. We examine the physical properties of the solutions, considering anti-de Sitter, de Sitter, and flat solutions. Our analysis shows that anti-de Sitter solutions exhibit thermal stability, whereas de Sitter and flat solutions do not. Finally, we discuss the implications of our results and possible future research directions., Comment: 27 pages, 9 Figures

The aim of this study was to investigate the impact of climatic variables (minimum temperature, maximum temperature, average precipitation, and precipitation deviation) on the yields of pistachio, banana, and mango in cold, hot–arid, hot–humid, and temperate–humid climates using the Just–Pope function. The Just–Pope function is a relatively new approach in this context. The most effective variables were identified by stepwise regression and the Feiverson algorithm. Data were collected for the period of 1998–2020 and were tested for stationarity. Finally, the coefficients of the Just–Pope function were estimated for the three crops in the four climates. The results showed that the variables affecting pistachio yield were different in each type of climate. Most variables were effective in warm and dry areas, while cropping area, production trend, and lag were effective in cold regions and in hot and humid areas; the maximum deviation and minimum temperature, production lag, cropping area, and production function were significant in hot and dry regions at the 90% level. The Just–Pope function for pistachio, mango, and banana showed that the impact of temperature and average rainfall was region-specific. Based on the results, a 1% increase in rainfall can increase the banana yield up to 0.032 ton/ha. As Iran experiences extensive climatic fluctuations, horticulturists are faced with difficult conditions. Such practices as the use of cultivars that are resistant to temperature and rainfall variations in the regions in order to alleviate the risk of yield variations in orchards are recommended.

Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) can increase the susceptibility of individuals to contracting mucormycosis through several mechanisms. Nowadays, coronavirus disease (COVID-19)-associated mucormycosis (CAM) is a serious public health concern, particularly in developing countries. This meta-analysis aims to identify the risk factors that affect the mortality rate of patients with CAM.We systematically searched PubMed, Google Scholar, Scopus, Cochrane library, and preprint databases using pertinent keywords and the reference lists of the included relevant articles from inception till October 27, 2021. In order to reduce the effects of small-scale studies, we only selected cross-sectional, case-control, and cohort studies and case series with at least four patients. We identified 26 articles that included 821 patients with CAM. The effect size (ES) of mortality rate was 28% (95% confidence interval (CI) 20%-38%; ICoronavirus disease (COVID-19)-associated mucormycosis (CAM) is a major public health problem, particularly in developing countries. Severe COVID-19 infection, history of mechanical ventilation, early CAM, comorbidities other than diabetes (malignancies, transplant, or renal failure), pulmonary and rhino-orbito-cerebral mucormycosis, and delivering only medical treatment for mucormycosis were the worst prognostic factors in CAM patients. Identifying the mortality-related risk factors in CAM patients may help reduce the mortality rate by implementing optimized treatment approaches.The online version contains supplementary material available at 10.1007/s12281-022-00440-2.

Violence against pregnant women is a significant public health problem, resulting in disability and various physical and mental health disorders. This systematic review and meta-analysis explored the prevalence of physical, verbal, sexual, psychological, emotional, economic, and other types of violence among pregnant women in Iran.Bibliographic databases including PubMed, Embase, Web of Science (WoS), and Scopus, and also Iranian databases including Scientific Information Database (SID), Magiran, and Civilica were searched from 2002 to September 16, 2020. Following a random-effects meta-analysis, we estimated the pooled prevalence of exposure to different types of violence among Iranian pregnant women. Overall, 61 articles that met the inclusion criteria were analyzed in this systematic review.The prevalence of physical violence was 19.0% (95% confidence intervals [CI]: 14.0, 24.0), verbal violence was 42.0% (95% CI: 24.0, 61.0), sexual violence was 26.0% (95% CI: 20.0, 32.0), psychological violence was 37.0% (95% CI: 28.0, 46.0), emotional violence was 51.0% (95% CI: 40.0, 62.0), economic 39.0% (95% CI: 19.0, 60.0), and the prevalence of other types of violence was 54.0% (95% CI: 46.0, 62.0).This study revealed that Iranian pregnant women are often exposed to different types of violence. Therefore, screening for violence in this vulnerable group seems necessary due to the sensitive nature of pregnancy and its importance in maternal ‎health. This alarming rate of violence calls for adopting upstream policies and interventions to reduce violent practices against pregnant women in Iran.

In a changing climate, drought indices as well as drought definitions need to be revisited, because some statistical properties, such as long-term mean, of climate series may change over time. The study aims to develop a Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI) for reliable and robust quantification of drought characteristics in a changing environment. The proposed indicator is based on a non-stationary log-logistic probability distribution, assuming the location parameter of the distribution is a multivariable function of time and climate indices, as covariates. The optimal non-stationary model was obtained using a forward selection method in the framework of Generalized Additive Models in Location, Scale and Shape (GAMLSS) algorithm. The Non-stationary and Stationary forms of SPEI (i.e. NSPEI and SSPEI) were calculated using the monthly precipitation and temperature data of 32 weather stations in Iran for the common period of 1964–2014. The results showed that almost at all the stations studied, the non-stationary log-logistic distributions outperformed the stationary one. Both drought indicators SSPEI and NSPEI significantly differed in terms of spatial and temporal variations of drought characteristics. While SSPEI identified the long-term and continuous drought/wet events, NSPEI revealed the short-term and frequent drought/wet periods at almost all the stations of interest. Finally, it was revealed that NSPEI, compared to SSPEI, was a more reliable and robust indicator of drought duration and drought termination in vegetation cover during the severest drought period (the 2008 drought), and therefore, was suggested as a suitable drought index to quantify drought impact on vegetation cover in Iran.

Linear permanent magnet Vernier machines (LPMVMs) is an attractive solution for stroke and direct-drive applications. Several LPMVM topologies have been presented for different applications that operate based on magnetic flux modulation. LPMVMs have some advantages including high force, and torque density at low speeds. This paper introduces a double-excited linear Vernier machine for wave energy conversion. To model the machine, finite element analysis and nonlinear equivalent network model are used. To improve the accuracy of the model and compact the network, a new meshing method is proposed. For better continuity in the output waveforms of the machine, special positioning is utilized. The end-effect is modeled using two separate networks. Finally, the modeling and simulation results are compared with each other and validated experimentally.

Coronavirus disease 2019 (COVID-19) is a novel virus that primarily involves the respiratory system. Due to the COVID-19 pandemic, an extensive vaccination program is underway worldwide. Herein, we present a 68-year-old woman with paresthesia of both hands associated with gait instability, which started three to four days after receiving the second dose of Oxford/AstraZeneca vaccine against the COVID-19 infection. The acute inflammatory demyelinating polyradiculoneuropathy subtype of the Guillain-Barre syndrome, which is the most common subtype, was diagnosed. Regardless of the beneficial effects of the vaccines, this case report aimed to evaluate their severe complications, such as Guillain-Barre syndrome, to reduce their occurrence in the future.

Background: Obesity has increasingly become a health threat in the Middle East and North Africa (MENA) countries. This study aimed to investigate the scientific publications on obesity in the MENA countries during 2008-2020. Methods: A longitudinal analysis of 13 years (2008-2020) of bibliographic data from obesity-related articles was performed. Web of Science core collection (WoS) was searched for bibliographic data. The bibliometric indicators including overall productivity and collaboration along with the prevalence of obesity and socioeconomic status were used to assess and compare the context of obesity research efforts in the MENA region. Results: The overall obesity-related articles of the MENA countries cumulated to 23680 publications. The MENA region accounted for a 6.5% global publication share in obesity research. Turkey contributed the highest rate of total publications (n=6162) followed by Iran (n=5302) and Israel (n=2847). Iran and Turkey had the lowest rates of international collaborations. The overall obesity research was not significantly associated with socio-demographic index (SDI) measure (r=-0.26, P=0.27). No significant association was found between Gross National Income (GNI) per capita and the overall production of obesity research (r=0.41, P=0.08). Additionally, obesity research was not significantly associated with the prevalence of obesity in the countries (r=0.24, P=0.30). Conclusion: This study observed an increased share of scientific productivity in the field of obesity from the MENA countries. Neither SDI, GNI per capita, nor obesity prevalence was not significantly associated with the overall productivity of the region.

BackgroundMoral injury occurs when negative distressing emotions appear and are suppressed. This could lead to several mental health problems such as depression and post-traumatic stress disorder, and result in long-lasting emotional, behavioral, and social problems. Moral injury, a term more commonly used in war contexts, has come into the spotlight during COVID-19 pandemic. We aimed to evaluate the rate of moral injury and its association with psychological injuries during this healthcare crisis.MethodsWe assessed the rates of depression, anxiety, stress, and their association with moral injury among 333 nurses, medical interns, and residents between December 2020 and January 2021. This study was done using validated versions of Depression Anxiety Stress Scales (DASS- and Moral Injury Symptom Scale-Healthcare Professionals (MISS-HP) scores.ResultsTotally 333 healthcare professionals participated in this study, mostly aged between 26 to 30 years old. Nearly half of the participants had a clinically significant moral injury. The average scores of anxiety and stress were significantly higher in women. The participants who were single showed higher rates of depression and moral injury than married ones. Moreover, anxiety, stress, depression, and moral injury were higher in nurses than other healthcare professionals. The scarcity of personal protective equipment at the workplace and giving care to patients with end-stage COVID-19 diagnosis were among the factors associated with a higher risk of developing mental health problems.ConclusionThe results of this study showed that anxiety, stress, depression, and moral injury were prevalent among healthcare professionals during COVID-19 pandemic. Also, the rates of anxiety, stress, and depression were associated with moral injuries.

Objectives: Cardiovascular diseases are the primary cause of death all around the world, and the complications of heart disease can reduce the patient's quality of life.Adherence to a therapeutic plan can reduce surgical complications and promote the healing process. This study aimed to survey the relationship between adherence to a therapeutic plan and quality of life in discharged patients after a coronary artery bypass graft (CABG). Methods: Descriptive correlational research was carried out to discover relationships among variables. The study was conducted in Hamadan hospital in 2014. Seventyone patients undergoing CABG surgery were selected by convenience sampling method. Before discharge, the patients completed the Mac New Quality of Life Questionnaire and adherence to therapeutic plan questionnaire that included medicine adherence, recommended care, diet and exercise orders, and incentive spirometry. After five weeks, patients again completed the questionnaires, and the data were analyzed. Results: There was a positive and significant relationship between patients' quality of life and adherence to the treatment plan. As the treatment program increased, the patients' quality of life also increased (r= 0.695, p

ObjectivesThis study aims to assess the prevalence of hypertension (HTN), and determine the relationship between HTN and anthropometric indices including fat distribution, body mass index (BMI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) in Shiraz Heart Study.SettingIn this cross-sectional study, subjects were enrolled in 25 clinics in Shiraz. I.R. Iran between 2019 and 2021.ParticipantsA total number of 7225 individuals were selected, aged between 40 and 70 years of whom 52.3% were female. Among the people living in Shiraz, individuals living far from clinics, cases of mental or physical disabilitiy and documented cardiovascular diseases were excluded.Primary and secondary outcome measuresPrimary outcome: The association of body composition, WHR, WHtR and BMI with HTN.Secondary outcome: The sensitivity and specificity of the WHtR for the prediction of HTN.ResultsHTN prevalence was 19.3%. Obesity prevalence was estimated to be 28.5%. WHR and lean body mass showed a significant association with HTN (pConclusionHTN had a meaningful association with all the noted anthropometric indices. WHtR performed well as a predictor of HTN.

To compare the success rate of vaginal misoprostol versus intravenous (IV) oxytocin in termination of pregnancy in the second trimester intrauterine fetal death (IUFD).This was an open-label randomized controlled study for 106 women with second trimester IUFD. Patients were randomly divided into two groups: women given vaginal misoprostol (400 mcg every 6 h up to 48 h) versus those given IV oxytocin (starting with 50 units up to a maximum of 300 units). When the first-line treatment (as mentioned above) failed, treatment methods were replaced with each other. When the second-line treatment failed, the patients underwent dilation and evacuation.The first-line treatment yielded the successful rate of 88.7% versus 73.7% for misoprostol versus oxytocin, respectively (p = 0.047). Among those with first-line treatment failure, the second-line treatment yielded success rate of 85.7% versus 83.3% for misoprostol versus oxytocin (p = 0.891). The mean duration of induction to delivery in women with successful response to first-line treatment was 28.72 and 20.55 h after initially receiving misoprostol versus oxytocin, respectively (p 0.001). While during second-line treatment, this mean interval was not significantly different among those with misoprostol versus oxytocin (p = 0.128). No severe adverse events were observed.Vaginal misoprostol was associated with higher termination rate than oxytocin without adverse events when used as the first-line treatment. Both methods yielded the same success rate when used as the second-line treatment.

This study aimed to investigate the association between regional body fat distribution and the prevalence of Diabetes mellitus (DM) in adult populations using machine learning. We applied machine learning methods to data from a cohort study to analyze the relationship between fat in different body areas and diabetes. All measurement was done by "Tanita Segmental Body Composition Analyzer BC-418 MA Tanita Corp, Japan". The correlation between the used parameters and DM was measured using some machine learning algorithms i.e. SVM, SGD, KNN, MLP, Adaboost and EDINet. A total of 4661 participants were included. The top features that reported higher importance in classification models were age, fat mass, and percentages in legs, arms, and trunk area. Fat-free mass in the legs, arm, and trunk area was reversely associated with diabetes. Our proposed method significantly outperformed the others. It has the best performances in Accuracy, Precision, Recall-0, Recall-1, and F1-score, which were 93.57, 93.67, 96.11, 74.55 and 93.62, respectively. Our machine learning models showed that regional body fat could have specific impacts on diabetes based on the location of the fat accumulation. The most predictor values of diabetes were age, fat mass, and percentages in arms, legs, and trunk area. Further studies on different ages, gender, ethnic groups, and races are recommended.

Human health has been challenged drastically by the emergence of COVID-19. This pandemic has imposed a serious burden on different aspects of life. Apart from the high rates of morbidity and mortality, reporting of newly formed variants with enhanced contagious capacity has made the future vague. Existence of different comorbidities is a prominent factor towards poor prognosis and fatal outcomes. Objectives: The present study aimed to identify the most important comorbidities in the COVID-19 patients who passed away during the first wave in Fars province, Iran. Methods: Trained general physicians obtained data from medical files in the referral hospitals of COVID-19 throughout the province. These included demographic data, past medical history, and existence of comorbidities. The data were analyzed using chi-square test, independent sample t-test, and Mann-Whitney test. P-values less than 0.05 were considered statistically significant. Results: Out of the 3700 confirmed cases, 87 patients died from February to May 2020. Among these patients, 81.1% had comorbidities, with hypertension, diabetes, and cardiovascular disease being the most prevalent ones. The results revealed no significant differences between the individuals with and without comorbidities regarding age, gender, and duration of ICU hospitalization. Oxygen saturation was also poor in both groups. However, the patients with comorbidities had significantly higher blood urea nitrogen and creatinine levels compared to their comorbidity-free peers. Conclusions: Cardiovascular disease and the related risk factors contributed greatly to the deadly fate in COVID-19 patients. Hence, early prophylactic and therapeutic interventions should be considered in COVID-19 patients harboring such comorbidities. This can play a pivotal role in reducing the rate of mortality and the consequent financial and social harms.

Background and purpose. – Identifying multiple sclerosis (MS) lesions is cornerstone in the diagnosis and prognosis of the disease activity. Application of contrast-enhanced magnetic resonance imaging (CE-MRI) is vital but the alternative use of diffusion-weighted imaging (DWI) and biomarkers is most appropriate when the injection of contrast agents is contraindicated. The present study investigated the possible substitution of CE-MRI with DWI and determined a vitamin D3 cutoff point for MS patients with positive MRI.Materials and Methods. – 5 ml of peripheral venous blood was collected from all patients and DWI and post-contrast T1-weighted MRI were performed on 85 patients with acute attacks of MS from April 2018 to November 2019. Contrast-enhanced lesions were considered the gold standard of activity in MRI in evaluating the relation between CE-MRI and DWI.Results. – The accuracy of CE-MRI was higher (63.5%) compared to DWI (27.1%). Majority of patients (54) showed positive results in CE-MRI. The difference between patients with and without positive CE-MRI was statistically significant in terms of vitamin D3 deficiency (P=0.001). The optimal cutoff of vitamin D3 for CE-MRI positive patients was 23.33 ng/ml with 83.33% sensitivity and 61.29% specificity. Conclusions. – Combination of CE-MRI and DWI yields more positive imaging results; DWI sequence alone, without using T1 with contrast in MRI, is not enough to assess brain lesion activity in patients with MS. Furthermore, vitamin D3 levels of

Background: There are still conflicting results on thepostoperative consequences of patients with hip and femoralfractures based on the type of anesthesia. The aim of this studywas to compare mortality and morbidity of general and spinalanesthesia in patients undergoing hip and femoral fractures.Methods: In this analytical cross-sectional study, the informationof 93 patients who had undergone hip and femoral surgery withgeneral and spinal anesthesia was studied during 2011-2019 inthe medical records by census method. Data were analyzed usingSPSS 23 software and descriptive and analytical statistics.Results: The general anesthesia group consisted of 29 patientsand the spinal anesthesia group included 64 patients. The twogroups were the same in terms of demographic information,preoperative hemodynamic variables, and previous medicalhistory. The results of the independent t-test with a significancelevel of 5% did not show a significant difference between thetwo groups in the following variables: mean duration of surgeryand duration of anesthesia, mean arterial pressure and heartrate after surgery, changes in blood pressure, and heart rateduring surgery, bleeding, intravenous fluids and blood productsintake, postoperative hemoglobin, number of days hospitalizedin the Intensive Care Unit and surgical ward. The mean postoperative mean arterial pressure score in the general anesthesiagroup was significantly higher than the spinal group (P=0.004).Complications and mortality after surgery did not differ betweenthe two types of anesthesia.Conclusion: In general, these two methods of anesthesia do notdiffer from each other in terms of postoperative complications andmortality, and physicians can choose the appropriate anesthesiamethod according to the specific conditions of the patients

Assays detecting viral infections play a significant role in limiting the spread of diseases such as SARS-CoV-2. Here we present Rolosense, a virus sensing platform that transduces the motion of synthetic DNA-based motors transporting 5-micron particles on RNA fuel chips. Motors and chips are modified with virus-binding aptamers that lead to stalling of motion. Therefore, motors perform a “mechanical test” of viral target and stall in the presence of whole virions which represents a unique mechanism of transduction distinct from conventional assays. Rolosense can detect SARS-CoV-2 spiked in artificial saliva and exhaled breath condensate with a sensitivity of 103copies/mL and discriminates among other respiratory viruses. The assay is modular and amenable to multiplexing, as we demonstrated one-pot detection of influenza A and SARS-CoV-2. As a proof-of-concept, we show readout can be achieved using a smartphone camera in as little as 15 mins without any sample preparation steps. Taken together, mechanical detection using Rolosense can be broadly applied to any viral target and has the potential to enable rapid, low-cost, point-of-care screening of circulating viruses.

Background Intimate partner violence (IPV) against pregnant women can cause several complications for the mother and her baby, which are life-threatening. Thus, we aimed to find the prevalence of IPV and its associated factors in pregnant women in Shiraz, Iran. Methods This cross-sectional study was conducted among pregnant mothers in Shiraz between July 2020 and January 2021. The questionnaire consisted of four parts: demographic data, socio-economic status (SES), obstetric and medical history, and questions about IPV. Univariate analysis was performed using Chi-square, McNemar, or Fisher’s exact test, and variables with p-value Results The overall prevalence of IPV was 93.1% among 830 pregnant women in Shiraz. Psychological violence was the most prevalent type (92.9%), followed by sexual (11%) and physical (7.7%) violence. High SES (OR = 3.21, (CI:1.61–6.41)) was the only risk factor for overall violence, and the age group, 30–34, was a risk factor for physical violence. Mother-desired pregnancy (OR = 26 (Cl:0.09–0.79)) and father-desired pregnancy (OR = 0.91, (CI:0.22–3.80)) were protective factors against physical and sexual violence, respectively. Furthermore, Psychological violence and sexual violence increased during COVID-19 Pandemic (P.value Conclusion According to the obtained results, the prevalence of IPV during pregnancy in Shiraz was very concerning, especially psychological violence. Improving conflict-solving skills among family members and addressing economic problems could be considered by health policymakers when designing interventional programs and policies to reduce IPV during pregnancy.

This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in extreme precipitation, copula functions were applied to compute the joint return periods of extreme events, and univariate and bivariate distributions were used to determine risk. The results showed that the decrease in consecutive wet days (CWD) was significant in the west and the northwest of Iran, while the consecutive dry days (CDD) index was increasing therein. The precipitation on more than the 90th percentile (P90) very wet days and annual number of days with precipitation less than the 90th percentile threshold (D90) indices followed similar patterns, with no significant trend in most parts of Iran, but at several stations in the north, west, and northwest, their decline was extreme. Furthermore, the increase of D10 (annual number of days with precipitation less than the 90th percentile threshold) and P10 (total precipitation of D10 of a year) was extreme in the wet regions of Iran, including the north, west, and northwest areas, and also part of the center. More than 50 percent of Iran experienced a low risk level, with a return period of extreme events (CWD, CDD) of more than 27.5 years, and the joint return periods of (D10, D90), (P10, P90), and (D10, P10) pairs were less than 100 years in most regions of Iran. Due to the increasing number of dry days in the north, west, and northwest of Iran, the drought risk increased. Based on the changes in extreme precipitation indices in recent years, the findings of this study will be useful for copula-based frequency analysis under a changing environment at regional and global scales.

BackgroundEnd-stage renal disease is a life-threatening condition in which patients require dialysis or kidney transplant. These patients must adhere to the treatment regimen because treatment non-adherence affects their quality of life and health. We conducted this study to predict hemodialysis patients’ treatment adherence based on procrastination and difficulty in emotion regulation.Materials and methodsWe conducted this descriptive correlational study on 218 hemodialysis patients with chronic kidney disease. We used purposive sampling to select participants from six dialysis centers in Kerman, Sirjan, and Rafsanjan. The measuring tools included the end-stage renal disease adherence questionnaire, general procrastination scale, decisional procrastination scale, and difficulty in emotion regulation scale. We used the correlation coefficient, regression analysis, and SPSS18 to analyze data.ResultsOur study indicated that among the dimensions of treatment adherence, medication use had a significant, weak, and inverse relationship with general and decisional procrastination. We also found a significant, weak, and inverse relationship between attendance and general procrastination (p p p > 0.05). Multivariate regression analysis revealed a relationship between age, the cause of kidney failure, and treatment adherence (p = 0.01 and p = 0.02).ConclusionTreatment non-adherence causes problems and complications in hemodialysis Patients, and disrupts their course of treatment. Therefore, it is necessary to identify the factors influencing non-adherence of patients undergoing hemodialysis and improve their treatment adherence, and thus their quality of life.