Deep learning based diagnosis of PTSD using 3D-CNN and resting-state fMRI data.

BACKGROUND: The incidence rate of Posttraumatic stress disorder (PTSD) is currently increasing due to wars, terrorism, and pandemic disease situations. Therefore, accurate detection of PTSD is crucial for the treatment of the patients, for this purpose, the present study aims to classify individuals with PTSD versus healthy control. METHODS: The resting-state functional MRI (rs-fMRI) scans of 19 PTSD and 24 healthy control male subjects have been used to identify the activation pattern in most affected brain regions using group-level independent component analysis (ICA) and t-test. To classify PTSD-affected subjects from healthy control six machine learning techniques including random forest, Naive Bayes, support vector machine, decision tree, K-nearest neighbor, linear discriminant analysis, and deep learning three-dimensional 3D-CNN have been performed on the data and compared. RESULTS: The rs-fMRI scans of the most commonly investigated 11 regions of trauma-exposed and healthy brains are analyzed to observe their level of activation. Amygdala and insula regions are determined as the most activated regions from the regions-of-interest in the brain of PTSD subjects. In addition, machine learning techniques have been applied to the components extracted from ICA but the models provided low classification accuracy. The ICA components are also fed into the 3D-CNN model, which is trained with a 5-fold cross-validation method. The 3D-CNN model demonstrated high accuracies, such as 98.12%, 98.25 %, and 98.00 % on average with training, validation, and testing datasets, respectively. CONCLUSION: The findings indicate that 3D-CNN is a surpassing method than the other six considered techniques and it helps to recognize PTSD patients accurately.

Oblique stagnation point flow of magnetized Maxwell fluid over a stretchable Riga plate with Cattaneo-Christov heat flux and convective conditions.

The current work deals with the oblique stagnation point flow phenomenon of a rate-type Maxwell fluid with the significance of the Cattaneo-Christov double diffusion theory. The Cattaneo-Christov theory is illustrated through the modified form of Fourier's and Fick's laws. The steady magnetized flow mechanism is observed in two dimensions through a stretchable convective Riga plate. In the mass and heat transfer analysis, the consequences of chemical reactions and thermal radiation are also incorporated. With the contribution of relevant dimensionless quantities, the setup of dimensionless equations is acquired which further takes the form of nonlinear equations. The physical significance of the numerous parameters on different features of the flow phenomenon is graphically exhibited. The interesting physical quantities are computed and numerically evaluated relative to the pertinent parameters. This study reveals that the thermal relaxation time parameter lowers the rate of heat transfer, and the thermal Biot number enhances the rate of heat transport. Moreover, the Deborah number minimizes the flow field of both tangential and axial velocities.

The Outcome of COVID-19 Infection on Kidney Transplantation Recipients in Southern Saudi Arabia: Single-Center Experience.

BACKGROUND: To report the incidence, risk factors, and outcome of severe COVID-19 disease in kidney transplant recipients attending a Saudi hospital at a single center in the Kingdom of Saudi Arabia. METHODS: A retrospective chart-based cohort study involving all kidney transplant recipients tested for COVID-19 in the Armed Forces Hospital Southern Region, KSA. RESULTS: Of 532 kidney transplant recipients who reported to the center, from March 2020 to June 2022, 180 were tested for COVID-19. Of these recipients, 31 (17%) tested positive. Among the 31 positive recipients, 11 were treated at home, 15 were admitted to the noncritical isolation ward, and 5 were admitted to the intensive care unit (ICU). Older age (P = .0001), higher body mass index (P = .0001), and history of hypertension (P = .0023) were more frequent in the COVID-19-positive recipients. Admission to the ICU was more frequent in older recipients (P = .0322) with a history of ischemic heart disease (P = .06) and higher creatinine baseline (P = .08) presenting with dyspnea (P = .0174), and acute allograft dysfunction (P = .002). In the ICU group, 4 (80%) patients required hemodialysis, and 4 (80%) died. CONCLUSIONS: Kidney transplant recipients with COVID-19 could have a higher risk for developing acute kidney injury, dialysis, and mortality than the general population. ICU admission and renal replacement therapy were more evident in older recipients with a history of ischemic heart disease, presenting with shortness of breath (P = .017) and a higher serum creatinine baseline. Acute allograft dysfunction was the independent predictor of mortality among patients admitted to the ICU.

Recurrent Urinary Tract Infection in Living Donor Renal Transplant Recipients and the Role of Behavioral Education Program in Management: A Single-Center Experience.

BACKGROUND: Urinary tract infections (UTIs) are the most prevalent type of kidney transplant (KT) recipients. We aimed to investigate the incidence, causes, and clinical impact of early recurrent UTI post-living donor KT and to examine the role of behavioral education program in management. METHODS: This retrospective cohort chart-review study included all KT recipients with recurrent UTI necessitating hospital admission between September 2017 and August 2021. All patients with recurrent UTI were subjected to behavioral education for a month. RESULTS: UTI was found in 14 of 145 patients (9.6%), with recurrent UTI in 11 (7.6%). A total of 93% of UTIs occurred during the first 6 months post-transplant and represented 52% of KT readmissions during the same period. A total of 64.3% of patients were older than 50 years. The mean (SD) length of hospital stay was 5 (2.5) days, with an equal incidence in both sexes. The most common bacterial isolates in early recurrent UTI were Escherichia coli in 80.9%. Both Extended-spectrum beta-lactamases and multidrug-resistant organisms (resistance in ≥3 drugs) were seen in 82.4% of isolates. Furthermore, the most effective antibiotic was meropenem, with 86.7% effectiveness. A total of 65% of UTIs were managed with a single antibacterial course. A total of 64.3% of patients were older than 50 years. In patients who developed UTI, the mean (SD) serum creatinine was 1.31 (0.52) mg/dL, with a mean increase in serum creatinine of 0.19 mg/dL on having the episodes; at 1 year post-transplant, serum creatinine declined to 1.23 (0.43) mg/dL. Four patients (36%) had no recurrence of UTI after behavioral education. CONCLUSIONS: The multidrug-resistant bacterial isolates account for 82.4% of the UTIs. Therefore, antibiotic prescription should follow the antimicrobial stewardship guidelines. Behavioral education significantly reduced the incidence of recurrent UTI.

Does Kidney Transplantation Help Young Patients on Dialysis With Erectile Dysfunction? A Single-center Study.

OBJECTIVE: to investigate the effects of a successful KT on EF in male patients with ESRD. MATERIALS AND METHODS: A single-center cross-sectional prospective study to assess the erectile dysfunction in male patients one month before and one year after KT. We adopted a validated, self-administered translated International Index of Erectile Function (IIEF-15) questionnaire. A sub-analysis was performed by categorizing the cohort into 2 age groups: <50 and ≥50 yr. RESULTS: Between September 2017 and February 2021, 68 ESRD patients underwent kidney transplantation (KT), with a mean age of 48.9 ± 12.9 years. Thirty-one patients were below 50 years (Group I). The median hemodialysis duration was 12 months. Sixty-three patients (92.6%) had ED. The mean total IIEF-15 score before and after was 46.8/75 ±12.7 and 55.5 ±13, respectively (P <.001). Forty-six patients (67.6%) reported improved erectile function, 22 (32.4%) did not demonstrate any change, and no patient reported deterioration. Moreover, after KT, sexual desire, orgasm, and overall patient satisfaction improved significantly. Before KT, 83.8% and 100% of groups I and II patients had ED, which dropped to 22.6% and 86.5%, respectively, after KT. IIEF-15 scores improved in both groups. However, the improvement in ED was observed significantly in young patients with mild ED. CONCLUSION: KT positively impacts sexual function and improves erectile dysfunction, especially among young patients. The duration of dialysis before kidney transplantation had no impact on ED improvement after transplantation. The positive effect of transplantation on ED could encourage ESRD patients to undergo KT.

Post-Laparoendoscopic Single-Site Donor Nephrectomy Ipsilateral Testicular Pain, Does Operative Technique Matter? A Single Center Experience and Review of Literature.

Aim: To assess incidence and characteristics of post-laparoendoscopic single-site donor nephrectomy (LESS DN) testicular pain. Materials and Methods: A prospective comparative study of all male donors post-left LESS DN (group A) vs. postopen nephrectomies (group B) was performed at our center. Patients' demographics, perioperative data, and postoperative consultation reports were reviewed. Testicular pain, swelling, numbness, urinary symptoms, and sexual dysfunction were evaluated. Patients with a history of scrotal pathology or surgical procedure were excluded. Pain and tenderness were scored on a standard 10-point scale. Results: From September 2017 to December 2020, 85 and 35 male patients of groups A and B met the evaluation criteria. Ipsilateral testicular pain developed in 11 patients (15.3%) and 2 patients (9.5%) in groups A and B, respectively. In most instances, the pain was mild to moderate in severity, started after 6 ± 2.1 and 4 ± 1.1 days postoperatively in groups A and B, respectively. Six patients in group A were evaluated with transscrotal ultrasonography that showed no abnormalities. All patients in both groups responded well to medical treatment. Conclusions: Post-LESS DN ipsilateral testicular pain is usually mild and self-limited. Preoperative patient education and discussion of the possibility of development of testicular pain and its management should be an integral component of laparoscopic donor nephrectomy informed consent.

Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging.

Early detection of post-traumatic stress disorder (PTSD) is essential for proper treatment of the patients to recover from this disorder. The aligned purpose of this study was to investigate the performance deviations in regions of interest (ROI) of PTSD than the healthy brain regions, to assess interregional functional connectivity and applications of machine learning techniques to identify PTSD and healthy control using resting-state functional magnetic resonance imaging (rs-fMRI). The rs-fMRI data of 10 ROI was extracted from 14 approved PTSD subjects and 14 healthy controls. The rs-fMRI data of the selected ROI were used in ANOVA to measure performance level and Pearson's correlation to investigate the interregional functional connectivity in PTSD brains. In machine learning approaches, the logistic regression, K-nearest neighbor (KNN), support vector machine (SVM) with linear, radial basis function, and polynomial kernels were used to classify the PTSD and control subjects. The performance level in brain regions of PTSD deviated as compared to the regions in the healthy brain. In addition, significant positive or negative functional connectivity was observed among ROI in PTSD brains. The rs-fMRI data have been distributed in training, validation, and testing group for maturity, implementation of machine learning techniques. The KNN and SVM with radial basis function kernel were outperformed for classification among other methods with high accuracies (96.6%, 94.8%, 98.5%) and (93.7%, 95.2%, 99.2%) to train, validate, and test datasets, respectively. The study's findings may provide a guideline to observe performance and functional connectivity of the brain regions in PTSD and to discriminate PTSD subject using only the suggested algorithms.

Successful Endovascular Repair of Infectious External Iliac Artery Anastomotic Pseudoaneurysm With Graft Preservation Post-Kidney Transplantation: Case Report and Review of Literature.

BACKGROUND: Allograft artery-infected pseudoaneurysm (PA) represents a rare but life-threatening complication of kidney transplantation (KT). A review of the literature, showed that nearly all these cases ended resulted in graft loss. We presented a case of post-KT-infected external iliac artery anastomotic PA successfully managed by endovascular stenting with graft preservation. Additionally, we reviewed the pertinent literature. METHOD: In this article, we described a hypertensive, 47-year-old man who presented 1 month post-cadaveric KT with acute kidney injury and gram-negative bacteremia secondary to a large infectious anastomotic PA of the external iliac artery. RESULTS: Because of favorable anatomy, successful arterial angio-stent fixation of the main renal artery PA, sparing the lower polar artery, was performed after 1 week of antibiotic and fungal coverage. CONCLUSION: Patient was discharged after 2 weeks with functioning graft. Graft function was stable after 3 months.

Machine learning techniques to detect and forecast the daily total COVID-19 infected and deaths cases under different lockdown types.

COVID-19 has impacted the world in many ways, including loss of lives, economic downturn and social isolation. COVID-19 was emerged due to the SARS-CoV-2 that is highly infectious pandemic. Every country tried to control the COVID-19 spread by imposing different types of lockdowns. Therefore, there is an urgent need to forecast the daily confirmed infected cases and deaths in different types of lockdown to select the most appropriate lockdown strategies to control the intensity of this pandemic and reduce the burden in hospitals. Currently are imposed three types of lockdown (partial, herd, complete) in different countries. In this study, three countries from every type of lockdown were studied by applying time-series and machine learning models, named as random forests, K-nearest neighbors, SVM, decision trees (DTs), polynomial regression, Holt winter, ARIMA, and SARIMA to forecast daily confirm infected cases and deaths due to COVID-19. The models' accuracy and effectiveness were evaluated by error based on three performance criteria. Actually, a single forecasting model could not capture all data sets' trends due to the varying nature of data sets and lockdown types. Three top-ranked models were used to predict the confirmed infected cases and deaths, the outperformed models were also adopted for the out-of-sample prediction and obtained very close results to the actual values of cumulative infected cases and deaths due to COVID-19. This study has proposed the auspicious models for forecasting and the best lockdown strategy to mitigate the causalities of COVID-19.

The Impact of Predialysis Patient Education Counseling on Relative Frequencies of Renal Replacement Modalities.

Background and objective The predialysis education program (PDEP) is an integral part of the management of patients with end-stage renal disease (ESRD). Hence, the aim of this study was to assess the distribution of renal replacement therapy (RRT) among patients with ESRD who received PDEP counseling at a single tertiary care center in Khamis Mushait, Kingdom of Saudi Arabia (KSA). Methodology In this study, we included 177 patients with ESRD who received a series of structured PDEP counseling sessions between March 2018 and February 2019 at the Armed Forces Hospital, Southern Region, Khamis Mushait, KSA. All patients were offered available RRT options, which included hemodialysis (HD), continuous ambulatory peritoneal dialysis (CAPD), or renal transplantation. Patients' opted RRT modality was recorded and managed as per the international guidelines and institutional protocols. Results Out of 177 patients, 58.8% (104) were males, with a mean age of 59 ± 13.7 years. The most common comorbid condition as the primary diagnosis was diabetic nephropathy in 49.7% (88), followed by hypertension in 30.5% (54), bilateral small kidney in 15.3% (27), and renal stone in 5.1% (nine) of the patients. Among the available RRTs, 51.4% (91) chose HD, 5.1% (nine) decided on CAPD, four patients (2.3%) opted for renal transplantation, while the remaining 41.2% (73) had yet to choose one, out of which 83.6% (61/73) had stage-IV chronic kidney disease (CKD) while the remaining 16.4% (12/73) had stage-V CKD. Conclusions In conclusion, a series of structured PDEP sessions for the patients progressing to ESRD can facilitate their selection of RRT. In a resource-limited setting, such as ours, where the number of patients who seek treatment for ESRD is rising, PDEP can provide patients with adequate information and knowledge to equip them with the ability regarding the selection of a self-care RRT modality.

Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach.

The present study is aimed at identifying the most prominent determinants of OCD along with their strength to classify the OCD patients from healthy controls. The data for this cross-sectional study were collected from 200 diagnosed OCD patients and 400 healthy controls. The respondents were selected through purposive sampling and interviewed by using the Y-BOCS scale with the addition of a factor, worth of an individual in his family. The validity and reliability of data were assessed through Cronbach's alpha and confirmatory factor analysis. Artificial Neural Network (ANN) modeling was adopted to determine threatening determinants along with their strength to predict OCD in an individual. The results of ANN modeling depicted 98% accurate classification of OCD patients from healthy controls. The most contributing factors in determining the OCD patients according to normalized importance were the contamination and cleaning (100%); symmetric and perfection (72.5%); worth of an individual in the family (71.1%); aggressive, religious, and sexual obsession (50.5%); high-risk assessment (46.0%); and somatic obsessions and checking (24.0%).

Nurses in double trouble: Antecedents of job burnout in nursing profession.

OBJECTIVE: To understand the most prominent factors contributing to job burnout in the nursing profession. METHODS: Mixed method design was used in this study. In the qualitative part of the study, a focus group discussion approach was used to determine the major factors contributing in nurses' job burnout. The quantitative part was conducted by using a questionnaire based on the theme generated in the qualitative part along with other demographic information. The data was collected from 93 nurses with 90.3% response rate. RESULTS: The proposed logistic regression model was able to correctly classify the 96% job burnout cases using factors mutually agreed in the focus group discussion. All the factors are significantly contributing to job burnout. However, the unfavourable work environment contributes more to job burnout as compared to the unfavourable support from family. CONCLUSION: unfavourable support of work environment and unfavourable support from family are the main contributors in the job burnout of nurses. Therefore, an equal improvements in both areas should be made on the priority basis to retain the happy nurses to deliver excellent healthcare services.