Outcomes of transrectal ultrasound guided prostate biopsies amenable lesions on MRI prostate

Introduction & Objectives: With the introduction of new modalities for prostate biopsies, detection rates of prostate cancer have been increased on one hand but on the other hand there are still some institutions where transperineal prostate (TP) biopsies cannot be offered due to limitations such as lack of expertise, absence of facilities, financial limitations, immense pressure on health system and especially during Covid pandemic. The aim of our study is to look at the prostate cancer detection rates of mpMRI (multi-parametric) prostate lesions amenable to transrectal ultrasound prostate biopsies (TRUS) and whether or not it can be offered in institutions with limited options. Material(s) and Method(s): Retrospectively we looked at the results of 95 patients with mean age of 67.8 years, mean prostate volume 46.5 cc, median PSA 7.2 ng/mL. TRUS biopsies amenable lesions on MRI prostate comprised of all peripheral or posterior zone lesions with: PIRADS II with rising PSA (1 patient);PIRADS >3 with PSAD of > 0.12 (14 patients), PIRADS IV (42 patients) and PIRADS V (33 patients). In addition to these there were 5 patients where PIRADS category was not clear. All patients underwent prostate biopsies (from both lobes) as per departmental protocol. Result(s): We found 0%, 42.9%, 68.4% and 90.3% in PIRADS II, PIRADS >III with PSAD >0.12, PIRADS IV and PIRADS V, respectively. In those where no PIRADS category was given 2 (40%) patients had the positive histology for prostate cancer. Overall prostate cancer detection rate was 65.2%. A direct proportional link was found between PIRADS category and prostate cancer detection. Only 2 patients with negative prostate biopsies agreed to have TP prostate biopsies repeated, that showed Gleason score 6 in PIRADS IV lesion and benign histology in other patient with PIRADS V lesion. It is also found that 15-50% of lesions in contralateral lobe have not been picked up by the MRI scan that came positive for prostate cancer (see table).(Table Presented) Most common to least common, the following histology was note: Gleason score (GS) > 8 (36 patients, 58%), GS 4+3 (10 patients, 16.1%), GS 3+4 (12 patients, 19.3%), GS 6 (4 patients, 6.4%) and high grade PIN (1 patient, 1.6%). Conclusion(s): It can be concluded that TRUS prostate biopsies can be utilized in a productive way by achieving highly satisfactory results in patients who has MRI prior to biopsies. A careful selection and a proper reading of MRI are warranted to achieve the good outcomes. TRSU biopsies are helpful in those departments with limitations in carrying out TP prostate biopsiesCopyright © 2022 European Association of Urology. Published by Elsevier B.V.

Severity and Mortality of Covid-19 in Patients with Diabetes Mellitus

Background: Covid-19 infection appeared as rapidly spreading cases of acute respiratory disease in Wuhan city of China that became pandemic. It was brought to the notice of WHO on December 31, 2019. Diabetes mellitus is one of the biggest health problems and fast growing emergencies of the 21st century. Diabetic patients with who got infected with Covid-19 have more chance of in hospital treatment need, intensive care unit care requirement, intubation and death. Objective(s): The objective of this study was to know the severity and mortality of covid-19 in patients with diabetes mellitus. Study Design: This was a descriptive case series study. Study Setting: It was done in the Covid-19 isolation and ICU unit of Ayub Teaching Hospital Abbottabad from May 2020 to October 2021. Method(s): Using non-probability consecutive sampling, 189 diabetic patients were enrolled. Sample included all covid-19 patients having diabetes that received indoor treatment during this period. All patients from both genders with age > 18 years were included. Patients with malignancy or on immunosuppressants for more than 1 month were excluded. Patients who were maintaining oxygen saturation at room air/facemask/nasal prongs were labelled as having non-severe disease while patient who needed CPAP or assisted ventilation were labelled as having severe covid-19 disease. All patients who died during admission were documented as covid-19 related mortality. Patients were labelled as diabetic who were known diabetic and taking diabetes treatment. Data was collected on a structured pro forma. Statistical program SPSS version 16.0 was used for the analysis of data. Result(s): In this study, mean age was 61.29 +/- 11.73 years. There were 40.2% male and 59.8% female patients. 86.2% patients were not-vaccinated, 3.7% patients were partially vaccinated and 10.1% patients were fully vaccinated. Hypertension was most common comorbidity (42.3%) and only CKD was significantly associated with increased mortality. 43.92%patients had non-severe illness while 56.08% patients had severe illness. The overall mortality of illness was 48.15% while it was 84.9% in patients with severe illness. Practical implication: These published publications provide a variety of various estimations and impact amounts due to the numerous different study designs and demographics. A comprehensive and methodical study is required because of the unpredictability of the situation. So that we conducted this study to assess the severity and mortality of covid-19 in patients with diabetes mellitus Conclusion(s): Our study concluded that severity and mortality of covid-19 was high in diabetic patients with high fasting & random sugar levels, pack smoking years and low oxygen saturation. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

Effect of COVID-19 Lockdown on Sleep Quality and Insomnia in Collegiate Students

The COVID-19 Pandemic necessitates strict lockdowns worldwide to prevent its spread, which has hurt people's lives, including students, on a physical, economic, and emotional level. This study examines the impact of the COVID-19 lockdown on the quality of sleep and the prevalence of insomnia among college students in Chennai. Using a random sampling approach, collegiate students (n=450) are invited to complete Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI). Frequencies, unpaired T-test, and the chi-square test were the statistical techniques employed to assess the data. The findings imply that 48% of students experienced poor sleep quality, and 37% reported Subthreshold insomnia during the COVID-19 lockdown. Even though no gender difference was observed regarding the overall sleep quality and insomnia scores, there is a significant association observed between gender with sleep quality;however, those failed to show a significant association with insomnia. Thus, the study concluded that the lockdown has affected sleep quality and led to insomnia among college students. Copyright This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY). Published by Oriental Scientific Publishing Company © 2022.

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Achieving high performance for GPU codes requires developers to have significant knowledge in parallel programming and GPU architectures, and in-depth understanding of the application. This combination makes it challenging to find performance optimizations for GPU-based applications, especially in scientific computing. This paper shows that significant speedups can be achieved on two quite different scientific workloads using the tool, GEVO, to improve performance over human-optimized GPU code. GEVO uses evolutionary computation to find code edits that improve the runtime of a multiple sequence alignment kernel and a SARS-CoV-2 simulation by 28.9% and 29% respectively. Further, when GEVO begins with an early, unoptimized version of the sequence alignment program, it finds an impressive 30 times speedup-a performance improvement similar to that of the hand-tuned version. This work presents an in-depth analysis of the discovered optimizations, revealing that the primary sources of improvement vary across applications;that most of the optimizations generalize across GPU architectures;and that several of the most important optimizations involve significant code interdependencies. The results showcase the potential of automated program optimization tools to help reduce the optimization burden for scientific computing developers and enhance performance portability for domain-specific accelerators. © 2022 IEEE.

Covid-19 Detection by using Deep learning-based Custom Convolution Neural Network (CNN)

The early diagnosis and treatment of COVID-19 has been a challenge all over the world. It is challenging to manufacture many testing kits and even then, their accuracy rate is very low. Studies carried out recently show that chest x-ray images are of great help in the diagnosis of COVID-19. In this study, we have developed a COVID-19 detection model that by observing the chest x-ray images of the patient, detects that either the patient is affected by COVID-19 or not. The model is developed using a custom Convolutional Neural Network (CNN) that differentiates between COVID-19 and healthy x-ray images so that the patient can be diagnosed and quarantined on time to prevent the spread of the pandemic. We used two different datasets which are publicly available for the training and validation of this model. Upon completion, the proposed model yields an accuracy of almost 98%. Upon further training, our model will be able to be used as a COVID-19 detection tool in hospitals worldwide and will play a vital role in early detection and timely containment of the pandemic.

State-of-the-Art Light to Digital Converter Circuits Applicable in Non-Invasive Health Monitoring Devices to Combat COVID-19 and Other Respiratory Illnesses: A Review.

In the past few years, a tremendous advancement in the outcome of biomedical circuits and systems has been reported. Unfortunately, at the time of the sudden outbreak of COVID-19, the electronic engineering researchers felt dearth on their side to combat the pandemic, as no such immediate cutting-edge solutions were ready to recognize the virus with some standard and smart electronic devices. Likely, in this paper, a detailed comparative and comprehensive study on circuit architectures of the biomedical devices is presented. Mostly, this study relates the industry standard circuit schemes applicable in non-invasive health monitoring to combat respiratory illnesses. The trending circuit architectural schemes casted-off to tapeout non-invasive health-care devices available in the past literature are meticulously and broadly discussed in this study. Further, the comprehensive comparison of the state of art of the device performance in terms of supply voltage, chip area, sensitivity, dynamic range, etc. is also shown in this paper. The inclusive design processes of the health monitoring devices from Lab to Industry is thoroughly discussed for the readers. The authors think, that this critical review summarising all the trending and most cited health-care devices in a single paper will alternately help the industrialists to adapt and modify the circuit architectures of the health monitoring devices more precisely and straightforwardly. Finally, the demand for health monitoring devices particularly responsible to detect respiratory illnesses, measuring blood pressure and heart-rate is growing widely in the market after the the incident of COVID-19 and other respiratory diseases.

Monitoring, Tracking and Diagnosing Dengue Fever using Smartphone, GPS and Machine Learning

Diagnosing infectious disease using smartphone and ML has emerged as popular research area. Many tropical nations including Pakistan are suffering from a viral disease i.e. Dengue. It can be recognized by its symptoms. Due to exhausted pressure of patients i.e. Covid-19 in hospitals and early monitoring, tracking and diagnosing of dengue epidemic is a real challenge to the authorities. Moreover, currently there does not exit any application to diagnose DF and SDF. Hence, we proposed a model, developed an android application, conducted pilot testing and apply ML. Whereas, WHO recommended symptoms of dengue are adopted. A pilot study is conducted on 80 participants. It revealed that the smartphone technology along with GPS on particular symptoms is helpful for early detection. Furthermore, the incorporation of GPS technology is useful for the surveillance during an epidemic or pandemic. Moreover, we also collected data of the last six-year dengue infection from hospitals for applying ML classification techniques using WEKA on clinical features of the patients. The results are compared in terms of Precision, Recall, F-measures and Accuracy to evaluate the performance of SMO, J48, Naïve Bayes, Random Forest and ZeroR classifiers. The performance of the Random Forest classifier has been achieved 98.8% using 10-folds cross-validation and 66% percentage split techniques. © 2021 IEEE.

Severity of Disease and Outcomes in Vaccinated and Non Vaccinated Covid patients in District Muzaffarabad AJK

Aim: Covid infection after first and second dose of vaccination was assessed in comparison to unvaccinated SARS-CoV-2 infection patients. Methodology: Patients were divided into two groups: Those who had not got any immunizations and those who had received vaccines that were prescribed. Individuals who have taken second dose of either the mRNA vaccine or the viral vector vaccine and have a positive COVID-19 within 14 days of receiving their second dose are deemed fully immunised. Results: Among 180 patients, the males were 75% and 25% was females. In our study, 16.7% (30/180) patients still suffered from COVID-19 despite of the fact that they were vaccinated, but the ratio of immune patients was greater i.e. 83.3% (150/180).The severity of the symptoms in vaccinated patients was much lesser and in some cases almost nil. 144/180 (80%) patients did not suffer from any severe symptoms after vaccination. 33/180 (18.3%) patients showed moderate symptoms while 3/180 (1.7%) showed severe symptoms. In the analysis of severity of symptoms of non vaccinated patients, 70% (126/180) showed severe symptoms, 25% (45/180) showed moderate and 5% (9/180) patients showed low symptoms. Conclusion: People without vaccination have more severe symptoms whereas COVID patients with vaccination had a reduced mortality rate and milder symptoms.

Uptake, satisfaction, and quality of family planning services in Pakistan: before and during Covid-19 outbreak: Stocktaking with clients of a private sector organisation

OBJECTIVE: To report the uptake, satisfaction, and quality of family planning services in the clients of a private sector organisation during Covid-19 in Pakistan and compare it with the situation before Covid-19 pandemic. METHODS: This paper is based on the client exit interview data collected before and then after the outbreak of Covid-19, using a structured questionnaire. Clients were chosen at the exit of the social franchise (SF) clinics, situated in rural and peri-urban areas, and beneficiaries of the outreach services delivery channel in the remote rural area. Descriptive analysis was carried out in SPSS, and frequencies and percentages were computed. RESULTS: All respondents were married women of reproductive age (MWRA) with an average age of 30 years, with either no or very low literacy levels. During the pandemic, overall utilization of the intrauterine contraceptive devices (IUCDs) declined, while the condom remained popular. Client satisfaction remained high in both service delivery channels during a pandemic. However, some results varied vis-à-vis the residence of the client. CONCLUSIONS: All respondents were married women of reproductive age (MWRA) with an average age of 30 years, with either no or very low literacy levels. During the pandemic, overall utilization of the intrauterine contraceptive devices (IUCDs) declined, while the condom remained popular. Client satisfaction remained high in both service delivery channels during a pandemic. However, some results varied vis-à-vis the residence of the client.

Accuracy of computed tomography for detection of COVID-19 among suspected patients

Objective: To determine the accuracy of CT chest in diagnosis of COVID-19 taking RT-PCR-testing as gold standard. Materials and Methods: A total of 150 patients of suspicion of COVID-19 who were referred for CT Chest in Radiology Department of Nishtar Medical University Multan from June-2020 to May-2021 were included. In all patients, two RT-PCR test results were obtained with 7 days of admission in hospital. Presence of any of these positive was labelled as COVID-19 infection. CT chest was performed in all patients within 2 days of admission in hospital using 128 slices CT scan machine. The diagnosis of COVID-19 infection was made according to the recommendations by Radiological Society of North America (RSNA) protocol. Results: Mean age was 51.3±14.7 years. 78 (52%) patients were male and 72 (48%) patients were female. RT-PCR test was positive in 89 (59.3%) patients. While the CT chest findings were suggestive of COVID-19 infection in 130 (86.7%) patients. The sensitivity of CT chest was 95.5%, specificity 26.2%, PPV wad 65.4% and NPV was 80.0%. Conclusion: CT chest has a very good sensitivity for detection of COVID-19, it can be used as a rapid diagnostic tool especially in areas of pandemic. However, the specificity of CT chest is low, that can limit its use in low COVID-19 affected areas.

Assessment of COVID-19 management at saidu group of teaching hospital swat: analytical cross-sectional study

Background: This research aimed to assess the current care management processes for COVID-19 and determine patient outcomes.

A big data approach to black Friday sales

Retail companies recognize the need to analyze and predict their sales and customer behavior against their products and product categories. Our study aims to help retail companies create personalized deals and promotions for their customers, even during the COVID-19 pandemic, through a big data framework that allows them to handle massive sales volumes with more efficient models. In this paper, we used Black Friday sales data taken from a dataset on the Kaggle website, which contains nearly 550,000 observations analyzed with 10 features: Qualitative and quantitative. The class label is purchases and sales (in U.S. dollars). Because the predictor label is continuous, regression models are suited in this case. Using the Apache Spark big data framework, which uses the MLlib machine learning library, we trained two machine learning models: Linear regression and random forest. These machine learning algorithms were used to predict future pricing and sales. We first implemented a linear regression model and a random forest model without using the Spark framework and achieved accuracies of 68% and 74%, respectively. Then, we trained these models on the Spark machine learning big data framework where we achieved an accuracy of 72% for the linear regression model and 81% for the random forest model. © 2021, Tech Science Press. All rights reserved.

Implementing ‘cleanliness is half of faith’ in re-designing tourists, experiences and salvaging the hotel industry in Malaysia during COVID-19 pandemic

Purpose: In the prevailing COVID-19 pandemic, organizations now are expected to serve customers who are highly conscious of safety and sanitation. Among others, the hospitality industry is significantly and negatively influenced by this pandemic. Given the unique characteristics of services, using advanced technology is not enough to create a memorable experience without physical interaction between service providers and customers. Thus, this study aims to define the “new normal” for service customers and to explore the “new service design” for the hotel industry. Design/methodology/approach: As most of the Southeast Asian countries heavily rely on the tourism industry, this study focuses on one of the emerging tourism destinations in this region, Malaysia. The data is collected through in-depth interviews with 17 potential national and international tourists. Findings: The results suggest that considering the “new normal” for customers, there is an immediate need for the hotel industry to revamp their service design by mainly practicing disinfection and sanitation activities, re-designing overall infrastructure and introducing promotional offers. Originality/value: This study is novel in its kind as it provides useful guidelines for both practitioners and academicians/researchers. Under this crucial time, very few research is conducted specifically focusing on the hotel industry and tourists’ behaviors amidst the COVID-19 pandemic. The study will provide in-depth knowledge about tourists’ expectations from the hotel services, especially in their own voices. © 2020, Emerald Publishing Limited.

Exergaming: An Effective Way to Maintain Physical and Mental Health at Home during COVID-19 Pandemic

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