bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Depression Severity and Sexual Satisfaction Between Fertile and Infertile Women in Iran: A Population Based Case-Control Study
Authors: Bakhtiar Katayoun , Ardalan Arash , Ebrahimzadeh Farzad , Bastami Fatemeh , Almasian Mohammad 
Published: May 2020

Abstract
Background: Depression and sexual dissatisfaction are among the most common psychological factors caused by infertility. Infertility is an important topic in Iranian culture and many studies have already targeted them. The aim of this study was to compare the severity of both depression and sexual dissatisfaction between fertile and infertile groups of women in Iran.Methods: A number of 180 infertile and 540 fertile women participated in this case-control study. The cases were selected through a combination of multistage stratified and cluster sampling method. For each infertile woman, three fertile women were randomly selected. Data gathering instrument consisted of demographic variables, Depression Inventory Scale, Second Edition, and the Linda Berg Sexual Satisfaction Questionnaire. The multivariate marginal model and SPSS 21 software were used for data analyses with a significance level of 0.05.Results: After adjusting for the effect of confounding variables, the marginal model showed the odds of depression increased by approximately 21.305 times among cases compared to control subjects (OR = 21.305, 95% CI for OR:14.75-32.021, P < 0.001). This model also found that by moderating the effect of confounding variables, infertility increased the odds of low sexual satisfaction by approximately 15.560 times (OR = 15.560, 95% CI for OR = 5.089–47.571, p < 0.001). Chi-square test (Monte Carlo Simulation) showed a significant relationship between infertility treatment and severity of depression in infertile group of women (P = 0.001). Severe cases of depression were mostly seen among women who received IVF treatment.Conclusion: The overall severity of depression and sexual dissatisfaction were higher in infertile group than that of fertile one. Also, most cases of severe depression were seen in IVF clinics, which may boost their depression. The results of this study may help reveal the psychological and social aspects of infertility in, Iran.
Associations Between High Triglycerides and Arterial Stiffness in a Population-Based Sample: Results from the Kardiovize 2030 Study
Authors: Pavlovska Iuliia , Kunzova Sarka , Jakubik Juraj , Hruskova Jana , Skladana Maria , Rivas-Serna Irma Magaly , Medina-Inojosa Jose R. , Lopez-Jimenez Francisco , Vysoky Robert , Geda Yonas E. , Stokin Gorazd B. , González-Rivas Juan P. 
Published: May 2020

Abstract
Background The term arterial stiffness (ArSt) describes the reduced capability of an artery to expand and contract in response to pressure changes and is recognized as an independent predictor of cardiovascular diseases (CVD). The evidence relating ArSt and triglycerides (TG) shows contradictory results. The aim of this paper is to assess the association between high TG and ArSt, using the cardio-ankle vascular index (CAVI).Methods Subjects aged between 25 and 64 years from a random population-based sample were evaluated between 2013–2016. Data from questionnaires, blood pressure, anthropometric measures and blood samples were collected to identify the metabolic syndrome (MetS). CAVI was measured using VaSera VS-1500N devise (Fukuda Denshi Co., Ltd., Japan). Subjects with history of CVD or chronic renal disease were excluded.Results 1934 participants, 44.7% males, were included. Median age was 48 (Interquartile Range [IQR] 19) years, TG levels were 1.05 (0.793) mmol/L, and CAVI 7.24 (1.43) points. Prevalence of high CAVI was 10.0% (14.5% in males and 6.4% in females; p < 0.001). Correlation between TG and CAVI was 0.136 (p < 0.001). High CAVI values were more prevalent among participants with MetS, high blood pressure, dysglycemia, abdominal obesity, and high total cholesterol. Using binary regression analysis, high TG were associated with high CAVI, even after adjustment for other MetS components, age, gender, smoking status and cholesterol (OR = 1.630, 95% CI = 1.061–2.505, p = 0.026).Conclusion TG levels were correlated with ArSt, measured as CAVI. High TG was associated with high CAVI independent of multiple cardiometabolic risk factors.
Environmental and Psychological Differences in Moderate-to-Vigorous Physical Activity Among Young Adults at Cardiometabolic Risks: A Case-Control Study
Authors: Li Ching , Yen Hsin-Yen 
Published: May 2020

Abstract
Background: Young adults’ physical activity is a foundation of creating future healthy lifestyles. The purpose of this study was to explore differences in physical activity, sedentary behavior, walkability, and health beliefs between young adults with and without cardiometabolic risk factors and the influence of moderate-to-vigorous physical activity.Methods: A cross-sectional study was conducted using a structured questionnaire.Results: Totally, 1149 valid responses were received for a response rate of 86.32%. A significant effect of cardiometabolic risk factors on the physical activity and sedentary time among groups was found. Young adults at high risk had a lower probability of moderate-to-vigorous physical activity than did healthy adults. Individuals who perceived that there were more recreational facilities, higher benefits of exercise, and lower barriers to exercise were more likely to participate in moderate-to-vigorous physical activity.Conclusions: Engaging in physical activity from environment and psychological perspectives is necessary for young adults’ cardiometabolic health promotion.
The Role of Insula in Physical Activity Moderate the Association Between Problematic Mobile Phone Use and Emotional Symptoms in Late Adolescents
Authors: Zou Liwei , Wu Xiaoyan , Tao Shuman , Yang Yajuan , Zhang Qingjun , Hong Xuedong , Xu Honglv , Xie Yang , Li Tingting , Zheng Suisheng , Tao Fangbiao 
Published: May 2020

Abstract
Background: Problematic mobile phone use (PMPU) and psychopathological symptoms are great public health concerns in adolescents. Previous studies have shown the associations between PMPU and emotional symptoms, but few studies to explore physical activity (PA) and the neural structures correlated with PA which moderate the relationship between PMPU and emotional symptoms. The aim of current study is to examine the moderating effect of PA and neural basis of such moderating effect on the relation between PMPU and emotional symptoms.Methods: A total of 251 college students underwent magnetic resonance imaging scanning. PMPU, PA and emotional symptom were assessed by self-rating questionnaire for adolescent problematic mobile phone use (SQAPMPU), international physical activity questionnaire (IPAQ-C), and depression anxiety stress scale-21 (DASS-21), respectively. A multiple regression model was performed to detect brain structure-gray matter volume associated with PA by voxel-based morphometry method. Moderating analysis was conducted using PROCESS macro in the SPSS software.Results: PA has significantly moderate effect on the association between PMPU with depressive (β = 0.301, p < 0.05), anxiety (β = 0.328, p < 0.05) and stress (β = 0.343, p < 0.05) symptoms. PA was correlated to the GMV of the right fusiform gyrus, the left precuneus, the left insula, and the left triangular part of inferior frontal gyrus. The relation between PMPU and depressive symptom was moderated by greater GMV of left insula.Conclusions: The findings indicate that high levels of PA can reducing the association between PMPU and emotional symptoms, and further find the GMV of left insula which correlated with PA may play a key role on the relationship between PMPU and depressive symptom. The intervention programs of emotional symptoms and insula-based deep brain stimulation is discussed as future study.
Effects of Climatological Parameters on the Outbreak Spread of COVID-19 in Highly Affected Regions of Spain
Authors: Shahzad Khurram , Shahzad Umer , Iqbal Najaf , Shahzad Farrukh , Fareed Zeeshan 
Published: May 2020

Abstract
The Coronavirus (COVID-19) pandemic is infecting the human population, killing people, and destroying livelihoods. This research sought to explore the associations of daily average temperature (AT) and air quality (PM 2.5) with the daily new cases of COVID-19 in the top four regions of Spain (Castilla y Leon, Castilla-La Mancha, Catalonia, and Madrid). We apply Pearson correlation, Spearman correlation, Kendall’s rank correlation, and panel regressions to quantify the overall co-movement between temperature, air quality, and daily cases of COVID-19 from February to 17th April 2020. Overall empirical results show that temperature and air quality exert pressure to increase new COVID-19 infections. Our findings are contrary to the earlier studies, which show a significant impact of temperature in reducing the COVID-19 spread. The conclusions of this work can serve as an input to mitigate the rapid spread of COVID-19 in Spain and reform policies accordingly.
Pulmonary embolism and screening for concomitant proximal deep vein thrombosis in noncritically ill hospitalized patients with coronavirus disease 2019.
Authors: Dubois-Silva Álvaro , Barbagelata-López Cristina , Mena Álvaro , Piñeiro-Parga Patricia , Llinares-García Diego , Freire-Castro Santiago 
Published: May 2020

Abstract
Background The clinical characteristics of noncritically ill patients with coronavirus disease 2019 (COVID-19) who develop pulmonary embolism (PE) and the prevalence of concomitant proximal deep-vein thrombosis (DVT) of the lower limbs have not been evaluated consistently.Methods We identified nonintensive care unit (non-ICU) patients admitted with COVID-19 who were diagnosed with PE at a single center in northwest Spain. Point-of-care compression ultrasonography (CUS) of the lower limbs was performed to screen for concomitant proximal DVT. Clinical data were analyzed retrospectively.Results From April 2 to April 17, 2020, 8 patients with COVID-19 and PE were identified. PE was diagnosed a median of 19 (interquartile range [IQR], 17–23) days after onset of COVID-19 symptoms and a median of 13 (IQR, 8–15) days after admission. All patients received thromboprophylaxis with enoxaparin or biosimilar at a median dose of 40 mg. All tested patients had high levels of D-dimer (≥2000 ng/mL), serum ferritin (≥300 mg/dL) and IL-6 (≥5 pg/mL) at PE diagnosis. Six (75%) and 7 (87.5%) patients had high C-reactive-protein (≥1 mg/dL) and lactate dehydrogenase (≥250 U/L) levels, respectively. All PE events were segmental or subsegmental, with lobar involvement in only one. None of these patients had concomitant proximal DVT of the lower limbs on CUS.Conclusions Non-ICU hospitalized patients with COVID-19 diagnosed with PE had mainly segmental or subsegmental events without concomitant proximal DVT of the lower limbs. Our findings suggest a predominance of small-vessel thrombosis secondary to inflammatory and immune responses in these patients.
Microbiota diversity following antibiotic treatment of Clostridium difficile infection
Authors: Binyamin Dana , Nitzan Orna , Azrad Maya , Hamo Zohar , Koren Omry , Peretz Avi 
Published: May 2020

Abstract
Background: Clostridium difficile (C. difficile) is a major nosocomial pathogen that infects the human gut and can cause C. difficile infection (CDI), a diarrheal disease. A dominant risk factor is antibiotic treatment, which disrupts the normal gut microbiota. The aim of the study was to examine the correlation between antibiotic treatment received prior to CDI onset and patient gut microbiota during the infection.Methods: Stool samples were collected from patients with CDI, presenting at the Baruch Padeh Medical Center Poriya, Israel. Demographic and clinical information, including previous antibiotic treatments, was collected from patient charts, and CDI severity score was calculated. Bacteria were isolated from stool samples, and gut microbiome was analyzed by sequencing the 16S rRNA gene, using the Illumina MiSeq platform and QIIME2.Results: In total, 84 patients with CDI were enrolled in the study; all had received antibiotics prior to disease onset. Due to comorbidities, 46 patients (55%) received more than one class of antibiotics. The most common class of antibiotics used was cephalosporins (n=44 cases). The intestinal microbiota of the patients was not uniform. Differences in intestinal microbiome were influenced by the different numbers of antibiotics families that the patients received (p = 0.022)Conclusions: The number of different antibiotics amount has a major impact on the gut microbiome of CDI patients, particularly on its bacterial richness.
Clinical and CT Features of the COVID-19 Infection: Comparison among different four age groups
Authors: Li Wei , Fang Yijie , Liao Jianwei , Yu Wenjun , Yao Lin , Cui Huaqian , Zeng Xiang , Li Shaolin 
Published: May 2020

Abstract
Purpose: To compare and analyze the clinical and CT features of coronavirus disease 2019 (COVID-19) among different four age groups.Methods: 97 patients with chest CT examination and positive reverse transcriptase polymerase chain reaction test (RT-PCR) from January 17, 2019 to February 21, 2020 were reviewed. The first clinical symptoms of each patient were collected and their first chest CT images were observed by dividing them into 4 groups according to age: junior, young, middle-age, and senior.Results: Comorbidities are more common in the senior group. Cluster onset is more common in junior group and senior group. Older patients have shown higher incidence with the highest clinical classification of severe or critical in these 4 groups. Senior patients have a higher incidence of large/multiple ground-glass opacity (GGO). Junior patients are mostly negative for chest CT or involve only one lobe of the lung. While in elderly patients, older patients have a higher incidence of involvement of 4 or 5 lung lobes. The frequency of lobe involvement also has significant differences in 4 different age groups. Conclusion: The clinical and imaging features of patients in different age groups are significantly different. Understanding of these features correctly and making the correct diagnosis promptly is of great significance for the scanning, diagnosis and prevention of COVID-19.
Chest CT changes in COVID-19 patients with hypertension comorbidities
Authors: Li Wei , Yu Wenjun , Liao Jianwei , Fang Yijie , Yao Lin , Cui Huaqian , Zeng Xiang , Li Shaolin 
Published: May 2020

Abstract
AIMTo summarize the chest CT and clinical features of COVID-19 pneumonia patients with hypertension comorbidities.METHODSThe initial chest CT imaging and clinical data of 15 confirmed COVID-19 patients with hypertension comorbidities treated in our hospital were analyzed retrospectively from January 1, 2019 to February 14, 2020. The chest CT images and clinical data were reviewed and their relationship of the disease was analyzed.RESULTSTotally 15 COVID-19 patients diagnosed with hypertension comorbidities were included. In terms of clinical characteristics, 14/15 (93.3%) of patients had characteristics of clustering onset, and the positive rates of the first RT-PCR test and the initial CT were 80% and 93% respectively. The most frequent CT abnormality observed was ground glass opacity (GGO) (13/15, 86.7%), including patchy/ punctate GGO and large/multiple GGO. Most of the lesions were multiple, and 60% of them involved 4-5 lobes. Most patients present with bilateral CT onset (12,80.0%), and most present with subpleural distribution (10,66.7%). The average CT score is 13.7, and 40% of the patients exceeded 20 points.CONCLUSIONThe common chest CT findings in COVID-19 patients with hypertension comorbidities are GGO, most of which at present with bilateral CT onset and subpleural distribution. CT is indispensable in the diagnosis and evaluation of this global health emergency.
Abnormal immunity of non-survivors with COVID-19: predictors for mortality
Authors: yang Zhao , hanxiang Nie , ke Hu , xiaojun Wu , yunting Zhang , mengmei Wang , tao Wang , zhishui Zheng , xiaochen Li , shaolin Zeng 
Published: May 2020

Abstract
Background The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread all over the world. The specific information about immunity of non-survivors with COVID-19 is scarce. We aimed to describe the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors.Methods In this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between Jan, 13 and Mar 4, 2020 from Renmin Hospital of Wuhan University. 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. Demographic and clinical characteristics, laboratory findings and chest computed tomograph results at admission, and treatment were collected. The immunity-related risk factors associated with in-hospital death were detected.Results Non-survivors were older than survivors. More than half of non-survivors was male. Nearly half of the patients had chronic medical illness. The common signs and symptoms at admission of non-survivors were fever. Non-survivors had higher white blood cell (WBC) count, more elevated neutrophil count, lower lymphocytes and platelete count, raised concentration of procalcitonin and C-reactive protein (CRP) than survivors. The levels of CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ T cells, and CD16+56+T cells were significantly decreased in non-survivors when compared with survivors. The concentrations of immunoglobulins (Ig) G, IgA and IgE were increased, whereas the levels of complement proteins (C)3 and C4 were decreased in non-survivors when compared with survivors. Non-survivors presented lower levels of oximetry saturation at rest and lactate. Old age, comorbidity of malignant tumour, neutrophilia, lymphocytopenia, low CD4+ T cells, decreased C3, and low oximetry saturation were the risk factors of death in patients with confirmed COVID-19. The frequency of CD4+ T cells positively correlated with the numbers of lymphocytes and the level of oximetry saturation, whereas CD4+ T cells were negatively correlated with age and the numbers of neutrophils.Conclusion Abnormal cellular immunity and humoral immunity were considerable in non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4+ T cells, and decreased C3 were the immunity-related risk factors predicting mortality of patients with COVID-19.
A New Deep Learning Pipeline to Detect Covid-19 on Chest X-Ray Images using Local Binary Pattern, Dual Tree Complex Wavelet Transform and Convolutional Neural Networks
Authors: Yaşar Huseyin , Ceylan Murat 
Published: May 2020

Abstract
At the end of 2019, a new type of virus, belonging to the coronaviridae family has emerged and it is considered that the virus in question is of zootonic origin. The virus that emerged in China first affected this country and then spread worldwide. Pneumonia develops due to Covid-19 virus in patients having severe disease symptoms. Many literature studies have been carried out in the process where the effects of the disease-induced pneumonia in lungs have been demonstrated with the help of chest X-ray imaging. In this study, which aims at early diagnosis of Covid-19 disease by using X-Ray images, the deep-learning approach, which is a state-of-the-art artificial intelligence method, was used and automatic classification of images was performed using Convolutional Neural Networks (CNN). In the first training-test data set used in the study, there were a total of 230 abnormal and 80 normal X-Ray images, while in the second training-test data set there were 476 X-Ray images, of which 150 abnormal and 326 normal. Thus, classification results have been provided for two data sets, containing predominantly abnormal images and predominantly normal images respectively. In the study, a 23-layer CNN architecture was developed. Within the scope of the study, results were obtained by using chest X-Ray images directly in training-test procedures and the sub-band images obtained by applying Dual Tree Complex Wavelet Transform (DT-CWT) to the above-mentioned images. The same experiments were repeated using images obtained by applying Local Binary Pattern (LBP) to the chest X-Ray images. Within the scope of the study, a new result generation algorithm having been put forward additionally, it was ensured that the experimental results were combined and the success of the study was improved. In the experiments carried out in the study, the trainings were carried out using the k-fold cross validation method. Here the k value was chosen 23. Considering the highest results of the tests performed in the study, values of sensitivity, specificity, accuracy and AUC for the first training-test data set were calculated to be 1, 1, 0,9913 and 0,9996; while for the second data set of training-test, they were 1, 0,9969, 0,9958 and 0,9996 respectively. Considering the average highest results of the experiments performed within the scope of the study, the values of sensitivity, specificity, accuracy and AUC for the first training-test data set were 0,9933, 0,9725, 0,9843 and 0,9988; while for the second training-test data set, they were 0,9813, 0,9908, 0,9857 and 0,9983 respectively.
A New Radiomic Study on Lung CT Images of Patients with Covid-19 using LBP and Deep Learning (Convolutional Neural Networks (CNN))
Authors: Yaşar Hüseyin , Ceylan Murat 
Published: May 2020

Abstract
The Covid-19 virus outbreak that emerged in China at the end of 2019 caused a huge and devastating effect worldwide. In patients with severe symptoms of the disease, pneumonia develops due to Covid-19 virus. This causes intense involvement and damage in lungs. Although the emergence of the disease occurred a short time ago, many literature studies have been carried out in which these effects of the disease on the lungs were revealed by the help of lung CT imaging. In this study, the amount of 25 lung CT images in total (15 of Covid-19 patients and 10 of normal) was multiplied (250 images in total) using three data augmentation methods which relate to contrast change, brightness change and noise addition, and these images were subjected to automatic classification. Within the scope of the study, experiments were made for each case which include the use of the CT images of lungs (gray-level and RGB) directly, the images obtained by applying Local Binary Pattern (LBP) to these images (gray-level and RGB) and the images obtained by combining these images (gray-level and RGB). In the study, a 23-layer Convolutional Neural Networks (CNN) architecture was developed and used in classification processes. Leave-one-group-out cross validation method was used to test the proposed system. In this context, the result of the study indicated that the best AUC and EER values were obtained for the combination of original (RGB) and LBP applied (RGB) images, and these figures are 0,9811 and 0,0445 respectively. It was observed that, applying LBP to images, the use of CNN input causes an increase in sensitivity values while it causes a decrease in values of specificity. The highest sensitivity was obtained for the case of using LBP-applied (RGB) images and has a value of 0,9947. Within the scope of the study, the highest values of specificity and accuracy were obtained by the help of CT of lungs (gray-level) with 0,9120 and 95,32%, respectively. The results of the study indicate that analyzing images of lung CT using deep learning methods in diagnosing Covid-19 disease will speed up the diagnosis and significantly reduce the burden on healthcare workers.