Investigating the Effect of Modafinil on Marked Brain Regions’ Functional Connectivity While Resting in Young, Healthy Individuals, Using Variance Component Longitudinal Model

Introduction: In recent years, investigating the differences in Functional Connectivity (FC) network in different brain regions in Functional Magnetic Resonance Imagining (fMRI) has appealed to neurological researchers. Examining the functional connectivity differences between two groups can assist in improving neurological disorders cure. The present study explores the differences in functional connectivity between two groups, one using Modafinil and the other placebo, as to consider the impact of this medicine, concerning functional connectivity of regions of interests among young, healthy people. Materials and Methods: Data was downloaded from website "Open fMRI." Downloaded data included 26 young, healthy men with no history of mental disease. They are divided into two groups of 13. The first group received 100 mgr Modafinil, and the second group 100mgr placebo. Three scans were taken from each group during the time. The data were analyzed through a longitudinal model, using a variance component. Results: Exploring the functional connectivity difference between the two groups, using intervention and placebo in the baseline effect did not show a significant statistical difference, but investigating the functional connectivity difference between the two groups in longitudinal trends showed a significant statistical difference in Inter-Hemispheric and Right- Brainstem. Conclusion: According to the present study's findings, Modafinil did not increase functional connectivity in most investigated regions.   &nbsp

Effectiveness of Emotional Intelligence Training on the Quality of Life of Mothers of Children with Leukemia

 AbstractBackground and Objectives: Leukemia is highly prevalent among children, and affects the family in addition to the child's life. The present study aimed to assess the effectiveness of training emotional intelligence on the quality of life of mothers of children with leukemia.Materials and Methods: The present quasi-experimental pretest-posttest uncontrolled study was conducted on 35 mothers of children with leukemia selected by convenient sampling from those attending selected hospitals affiliated to Shahid Beheshti University of Medical Sciences. Data were collected using mothers’ and children’s demographic details and the Persian version of Caregiver Quality of Life Index-Cancer questionnaire. Participants were assessed over 4 two-hour educational sessions using group discussion method (5 to 8 people). Two weeks after the intervention, questionnaires were completed by mothers again.Results: The results obtained using paired t and Wilcoxon tests showed significant reductions in the scores of mothers' quality of life two weeks after intervention in disruptiveness, and mental, physical, and financial concern dimensions (P<0.005) and a significant increase in positive adaptation dimension (P<0.005).Conclusion: The results obtained showed that training emotional intelligence skills can improve the quality of life of mothers of children with leukemia. It is therefore recommended that these skills be taught to mothers in order to improve their quality of life.Keywords: Emotional Intelligence, Quality of Life, Mothers, Children, Leukemia

The Effects of Spiritual Care on Anxiety in Adolescents with Cancer

Introduction: Anxiety is one of the psychological complications of cancer in adolescents and it is due to various factors. Since this complication leaves undesirable effects on physical and mental health and also on the adolescents’ quality of lives, one of the main nursing cares in adolescents with cancer is using various strategies to reduce the anxiety. Experience of living with cancer shows spirituality creates purpose and meaning in life for patients.Objectives: This study aimed to investigate the effects of spiritual care on anxiety in adolescents with cancer.Methods: This is a quasi-experimental study with one- group time-series design. 32 hospitalized adolescents were selected by purposeful sampling method based on the inclusion criteria. The spiritual care program was performed for adolescents in 6 sessions of 45 minutes class during their hospitalization. Data was collected by questionnaires of “personal and clinical characteristics” and “Speilberger State-Trait Anxiety Inventory”. The data were analyzed with the SPSS-19 software using descriptive and inferential statistical tests.Results: According to the results of this study, the difference between the mean score of pretest (55.96±11/34) and posttest (42.84±6/19) was significant. However the difference between mean scores of posttest and follow up (48.40±7/18) was not significant (P < 0.001).Conclusion: Implementation of spiritual care by nurses may affect the mental situation of adolescents with cancer and is a suitable method to reduce anxiety. Therefore it is necessary for nurses to use spiritual interventions during implementation of comprehensive nursing care.  Cite to Article: Torabi F, Sajjadi M, Nourian M, Borumandnia N, Shirinabadi Farahani A. The effects of spiritual care on anxiety in adolescents with cancer. Supportive and Palliative Care in Cancer 2016; in press

The impact of vitamin D changes during pregnancy on the development of maternal adverse events: A random forest analysis

Background: Maternal vitamin D deficiency during pregnancy has been associated with various maternal adverse events (MAE). However, the evidence regarding the effect of vitamin D supplementation on these outcomes is still inconclusive. Methods: This secondary analysis utilized a case–control design. 403 samples with MAE and 403 samples without any outcomes were selected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy study. Random forest (RF) analysis was used to evaluate the effect of maternal vitamin D changes during pregnancy on MAE. Results: The results showed that women who remained deficient (35.2%) or who worsened from sufficient to deficient (30.0%) had more MAE than women who improved (16.4%) or stayed sufficient (11.8%). The RF model had an AUC of 0.74, sensitivity of 72.6%, and specificity of 69%, which indicate a moderate to high performance for predicting MAE. The ranked variables revealed that systolic blood pressure is the most important variable for MAE, followed by diastolic blood pressure and vitamin D changes during pregnancy. Conclusion: This study provides evidence that maternal vitamin D changes during pregnancy have a significant impact on MAE. Our findings suggest that monitoring and treatment of vitamin D deficiency during pregnancy may be a potential preventive strategy for reducing the risk of MAE. The presented RF model had a moderate to high performance for predicting MAE

Lifestyle and occupational risks assessment of bladder cancer using machine learning‐based prediction models

Background: Bladder cancer, one of the most prevalent cancers globally, can be regarded as considerable morbidity and mortality for patients. The bladder is an organ that comes in constant exposure to the environment and other risk factors such as inflammation. Aims: In the current study, we used machine learning (ML) methods and developed risk prediction models for bladder cancer. Methods: This population‐based case–control study is focused on 692 cases of bladder cancer and 692 healthy people. The ML, including Neural Network (NN), Random Forest (RF), Decision Tree (DT), Naive Bayes (NB), Gradient Boosting (GB), and Logistic Regression (LR), were applied, and the model performance was evaluated. Results: The RF (AUC = .86, precision = 79%) had the best performance, and the RT (AUC = .78, precision = 73%) was in the next rank. Based on variable importance analysis in RF, recurrent infection, bladder stone history, neurogenic bladder, smoking and opium use, chronic renal failure, spinal cord paralysis, analgesic, family history of bladder cancer, diabetic mellitus, low dietary intake of fruit and vegetable, high dietary intake of ham, sausage, can and pickles were respectively the most important factors, which effect on the probability of bladder cancer. Conclusion: Machine learning approaches can predict the probability of bladder cancer according to medical history, occupational risk factors, and dietary and demographical characteristics

Machine learning-based classifiers to predict metastasis in colorectal cancer patients

BackgroundThe increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning (ML) approaches in terms of demographic and clinical factors.MethodsThis study focuses on 1,127 CRC patients who underwent appropriate treatments at Taleghani Hospital, a tertiary care facility. The patients were divided into training and test datasets in an 80:20 ratio. Various ML methods, including Naive Bayes (NB), random rorest (RF), support vector machine (SVM), neural network (NN), decision tree (DT), and logistic regression (LR), were used for predicting metastasis in CRC patients. Model performance was evaluated using 5-fold cross-validation, reporting sensitivity, specificity, the area under the curve (AUC), and other indexes.ResultsAmong the 1,127 patients, 183 (16%) had experienced metastasis. In the predictionof metastasis, both the NN and RF algorithms had the highest AUC, while SVM ranked third in both the original and balanced datasets. The NN and RF algorithms achieved the highest AUC (100%), sensitivity (100% and 100%, respectively), and accuracy (99.2% and 99.3%, respectively) on the balanced dataset, followed by the SVM with an AUC of 98.8%, a sensitivity of 97.5%, and an accuracy of 97%. Moreover, lower false negative rate (FNR), false positive rate (FPR), and higher negative predictive value (NPV) can be confirmed by these two methods. The results also showed that all methods exhibited good performance in the test datasets, and the balanced dataset improved the performance of most ML methods. The most important variables for predicting metastasis were the tumor stage, the number of involved lymph nodes, and the treatment type. In a separate analysis of patients with tumor stages I–III, it was identified that tumor grade, tumor size, and tumor stage are the most important features.ConclusionThis study indicated that NN and RF were the best among ML-based approaches for predicting metastasis in CRC patients. Both the tumor stage and the number of involved lymph nodes were considered the most important features

Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study

Background: Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients. Materials and methods: A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran’s three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve. Results: The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650–0.734), as well as 0.627 (0.670, 0.686) in the test data. Conclusion: We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC

Worldwide trend analysis of primary and secondary infertility rates over past decades: A cross-sectional study

Background: Infertility is a global health issue and is reported differently worldwide. Objective: To assess the longitudinal trends of primary and secondary infertility prevalence rate (PSIPR) per 100,000 across all countries during past decades. Materials and Methods: The PSIPR was extracted from the Global Burden of Disease database for 195 countries during 1993-2017. The longitudinal trends of PSIPR were explored across the seven epidemiological regions designated by the Global Burden of Disease. Results: Globally, the PSIPR was lower among men than women. Over time, the prevalence of primary infertility in men and women had a decreasing trend of -9.3 and -11.6 in high-income countries. Other regions have seen an increase, the highest being in South Asian women, and men of the Middle East and North Africa, with rates of change of 40.9 and 19.0, respectively. Over time, the secondary infertility prevalence in women of Central Asia, Central Europe and Eastern Europe, as well as of high-income countries, has been declining (rates of change of -16.9 and -11.7, respectively). Other regions have been on the rise, with the highest increase among women of the Middle East, North Africa, and South Asia (trend of 119.9 and 83.4, respectively), and in South Asian men (trend of 48.4). Conclusion: The overall trend of infertility prevalence shows a downward trajectory in high-income and developed countries and an upward trend in others. These findings might be explained by missed cases of infertility due to a low tendency for reproduction and the presence of more infertility treatment facilities in these regions. Key words: Infertility, Global burden of disease, Longitudinal studies.&nbsp

The impact of covid-19 pandemic on pregnancy outcome

Abstract Background The acute respiratory disease caused by the coronavirus (COVID-19) has spread rapidly worldwide yet has not been eliminated. The infection is especially deadly in vulnerable populations. The current studies indicate that pregnant women are at greater risk of getting seriously ill. Even though fetuses protect against disease, the additional finding showed that the COVID-19 pandemic could increase fetal and maternal morbidities. In a situation where COVID-19 and new strains of the virus are still not controlled, scientists predicted that the world might experience another pandemic. Consequently, more research about the effects of COVID-19 infection on pregnancy outcomes is needed. This study aimed to compare the pregnancy outcomes of Iranian pregnant women in the first year of the pandemic with the previous year. Methods This prospective cross-sectional study was performed to compare the pregnancy outcome during the COVID-19 pandemic among Iranian pregnant women who gave birth during the pandemic and one year before the pandemic (2019–2020 and 2020–2021). The sample size was 2,371,332 births registered at hospitals and birth centers platforms. The studied variables include stillbirth, congenital anomaly, birth weight, preeclampsia, gestational diabetes, cesarean section, ICU admission, mean of the gestational age at birth, preterm births, NICU admission, neonatal mortality and the percentage of deliveries with at least one complication such as blood transfusion and postpartum ICU admission. Analyzing data was done by using SPSS version 25 software. Results We found statistical differences between pregnancy and birth outcomes during the COVID-19 pandemic compared to one year before. The risk of preeclampsia, gestational diabetes, cesarean section, preterm birth and NICU admission were clinically significant. Also, there was a significant decrease in mean gestational age. Conclusion The COVID-19 pandemic has affected the pregnancy outcome by increasing morbidities and complications during pregnancy, birth, and postpartum. In addition, extensive quarantine outbreaks disrupted the healthcare system and hindered access to prenatal services. It is necessary to develop preventive and therapeutic care protocols for similar pandemic conditions