The sociodemographic and psychosocial correlates of COVID-19 vaccine concerns among urban college students

COVID-19 vaccine concerns remain high among Americans. Although recent studies have investigated the sociodemographic disparities in vaccine concerns, less attention has been given to reasons for vaccine skepticism and psychosocial factors that may explain it. The current study examined specific types of vaccine concerns among a diverse sample of college students (N = 1985) living in New York City. Participants who identified as Black, younger, with later immigrant generational status, and those with more conservative political leanings reported more vaccine concerns. Concerns regarding vaccine side effects were the most frequently reported source of concern. Reason for getting vaccinated, personal experiences with COVID, and COVID stress was also associated with vaccine concerns. Study results emphasize the importance of sociodemographic factors and COVID knowledge and stress in examining and addressing vaccine concerns.

Mawidi: Smart Appointments Booking System for Social Distancing

In traditional systems of banks, the booking process requires the client to be in the same place, the client withdraws a numbered paper from an electronic device and then sits in the waiting area until his/her number appears on the screen. However, these systems may cause many problems such as wasting clients' time, overcrowding in the waiting area, slow workflow, etc. In this paper, a smart appointment booking system is developed to solve the problems of traditional booking systems of banks and achieve social distancing. The proposed system applies Quick Response (QR) code, Global Positioning System (GPS), and Bluetooth Low Energy (BLE) technologies to improve workflow and achieve social distancing in banks. The proposed system is developed on two sides. On the client-side, a mobile application is developed, a QR is generated for the user, which contains booking information, and GPS is used to determine the location of the client as it is only possible to book if he/she is within 100 meters from the bank. Due to the restrictions imposed caused by the spread of COVID-19, BLE technology works to ensure social distancing between clients. On the employee side, a website is created to enable the employee to deal with the client. The proposed system is expected to reduce problems related to traditional systems, gain client satisfaction, facilitate workflow for employees, and contribute to reduce the spread of COVID-19. © 2023 NSP Natural Sciences Publishing Cor.

Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging (preprint)

The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic.

Isolation of Methicillin-Resistant Staphylococcus aureus from Wound Samples during the COVID-19 Pandemic: A Retrospective Study

Introduction: On March 11th, 2020, the World Health Organisation (WHO) declared the outbreak of the novel coronavirus disease caused by the Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) virus as a pandemic. This recently discovered b-coronavirus spread instantaneously across mainland China due to human-to -human transmission and crossed international borders aided by intercontinental travel. In most nations, the logarithmic growth of the cases very quickly overwhelmed the healthcare system which led to the overcrowding of the hospitals and led to a sudden surge in Hospital-Acquired Infections (HAIs). Implementation of contact precautions was implemented to control cross-infection. Aim: To determine the effect of Coronavirus Disease-2019 (COVID-19) on the prevalence of HAIs with special emphasis on Staphylococcus aureus (S. aureus). Materials and Methods: This three-year retrospective study (September 2018-August 2021) was undertaken at an apex tertiary care institute in Northern India. Wound swabs were collected and processed in the laboratory for the presence of aerobic bacterial isolates. S. aureus was identified using conventional methods and antimicrobial sensitivity was performed by the Kirby-Bauer disc diffusion method. Data was entered in Microsoft Excel and later analysed in International Business Machines (IBM) Statistical Package for the Social Sciences (SPSS) version 22.0. Results: A steady increase in the isolation of Methicillin-Resistant Staphylococcus aureus (MRSA) was noted during the study period (60.5% in 2018 to 78.1% in 2021). A statistically significant increase was noted in the detection of MRSA after the onset of the COVID-19 pandemic (p=0.018) despite the reduced number of surgeries conducted in the institution and rigorous execution of contact precautions. Conclusion: There was an increase in the rate of MRSA isolation during the study period. The increase was significantly affected by the onset of COVID-19. To contain the spread of MRSA, novel methods including preoperative screening of patients undergoing elective surgeries and periodic screening of hospital staff need to be implemented along with standard infection control precautions at all times.

Preparing for online peer support for I Punjabi men's mental health

In the context of the COVID-19 pandemic, some Punjabi men have supported their mental health through digital peer support interventions. However, there is little research which reflects upon the impact of peer support education for people who identify as culturally, linguistically, or geographically Punjabi. This review aims to map, discuss and appraise the scholarly literature concerning Punjabi communities and peer support education. Open-source articles published in English were sought through Google Scholar due to broadest accessibility. Screened articles were analysed for common themes, summarised, and critically appraised alongside a case study reflection. The findings show that there is a distinct lack of literature which could help to develop and evaluate digital peer support education for Punjabi populations and that future research is warranted. Despite this, some existing research can provide scholarly foundations for such work. Further practice and evaluation is required to understand the potential possibilities and pitfalls for peer support education in Punjabi and racialized communities more broadly. Future research should take a specific focus on the potential for impact in peer support for Punjabi communities to explore the unique needs of the population. Without such research we risk being unable to develop precise and specific peer support interventions which may exacerbate existing inequities within mental health more widely © This paper is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

Examining college students' food security coping strategies and experiences during the COVID-19 pandemic

College students' food situations may have been disrupted by the COVID-19 pandemic, which could have affected their health and well-being. However, little is known about how the pandemic impacted students' food experiences and how students coped with food-related disruptions, particularly from the student's own perspective. This study reviews data from 571 undergraduates who attended public colleges during Fall 2021 and Spring 2022 and wrote a narrative about the pandemic's impact on their food experiences. Most students indicated they experienced a wide range of food difficulties and adapted new food practices. Despite these challenges, students emphasized proactive coping strategies and positive pandemic outcomes rather than difficulties and negative outcomes. These findings have implications for students' long-term health and well-being. © 2023 John Wiley & Sons Ltd.

COVID-19 Identification From Lung CT Scans in a Low-Resource Setting Using a Regularized 3D Convolutional Neural Network

Right at the end of 2019, the world saw an outbreak of a new type of SARS (severe acute respiratory syndrome) disease, SARS-Cov-2, or COVID-19. Even in 2022, around 1 million people worldwide are getting infected with the virus every day. To date, more than 6 million people have died as a result of the virus. To tackle the pandemic, the first step is to successfully detect the virus among the mass population. The most popular method is the RT-PCR test, which, unfortunately, is not always conclusive. The physicians thus suggest lung CT tests for the patients for clinical relevance. But the problem with lung CT scans for the detection of coronavirus is that the COVID-19 infected scan is very similar to community-affected pneumonia (CAP) infected scan, and the results in many cases get wrongly interpreted. In addition, the virus is always mutating into different strains, and the severity and infection pattern slightly change with each mutation. Because of this rapid mutation, a large and balanced dataset of lung CT scans is not always available. In this work, we systematically evaluate the accuracy of a deep 3D convolutional neural network (CNN) on a small-scale and highly imbalanced dataset of lung CT scans (the SPGC COVID 2021 dataset). Our experiments show that it can outperform previous state-of-the-art 3D CNN models with proper regularization, an appropriate number of dense layers, and a weighted loss function. Our research, therefore, suggests an effective solution for identifying COVID-19 in lung CT scans using deep learning for small and highly imbalanced datasets. © 2022 IEEE.

Pharmacoinvasive Therapy in Treating Acute STEMI Patients in COVID-19 Era-Thrombolysis by Tenecteplase (TNK) / Streptokinase (STK) Followed by Rescue PCI of the Culprit Vessel

Background: Treating acute STEMI patients by primary PCI has dramatically fallen globally in covid era as there is chances of potential threat of spreading Covid among the non-Covid patient. Thereby, thrombolysis of acute STEMI patient either by Streptokinase (STK) or Tenecteplase (TNK) in grey zone till Covid RT PCR report to come, was the mode of treatment of acute myocardial infarction patient in our hospital. Post thrombolysis, Covid positive cases were managed conservatively in a Covid dedicated unit. Covid negative cases were treated by rescue PCI of the culprit lesion. Exact data on benefit of thrombolysis either by TNK or STK of STEMI patients in Covid era, is not well addressed in our patient population. Thereby, we have carried out this prospective observational study to see the outcomes of thrombolysis and subsequent intervention. Method(s): STEMI Patient who represented to our ER with chest pain and ECG and hs-TROP-I evidenced acute ST segment elevated myocardial infarction (STEMI), were enrolled in the study. Total 139 patients enrolled (Male:120, Female :19);average age for Male: 54yrs., female was: 56yrs. All patients were admitted in the grey zone of CCU where thrombolysis done either by TNK or STK. Positive for COVID-19, were patients excluded from intervention and managed conservatively in Covid-19 dedicated ward. Covid Negative patients were kept transferred to CCU green zone. Result(s): COVID-19 test was carried out on all studied patients. Among them, Covid-19 positive were 7.9% (11) patients and managed conservatively in dedicated Covid ward, Covid-19 negative were 92.1% (128). Primary PCI was performed in 5.03% (7). Rest was managed by Pharmacoinvasive therapy either by TNK or STK. Thrombolysis by Tenecteplase in 64% (89), Streptokinase in 17.9% (25) patient, 12.9% (18) patient did not receive any thrombolysis due to late presentation and primary PCI done in 5.4% (7). On average 2.1 days after Fibrinolysis, elective PCI carried out. Data analysis from 48 patients;chest pain duration (3.71 +/-2.8 hr., Chest pain to contact time 3.3+/-2.8hr., Chest pain to needle time 7.2 +/-12.7hr., thrombolysis to balloon time 117.5+/-314.8hr., as many of the patient develop LVF post thrombolysis. More than 50% stenosis resolution observed in 41.6% (20) patients, chest pain resolution with one hour of thrombolysis observed in 43.8% (21) patients and development of LVF in 20.8% (10) patients. Door to needle time was 30 min. At presentation of STEMI;Ant Wall MI 46.8% (65), Inferior Wall MI 52.5% (73) and high Lateral 0.7% (1). Average Serum hs Trop-I was 16656 for male and 12109 for female. LVEF were 41% for male and 48% for female. HbA1C were in Male 8.34%: Female 8.05%, SBP for Male 120mmHg: Female 128 mmHg. Total, 88 stents were deployed in 83 territories. CABG recommended for 5.03% (7) patients, PCI in 58.3% (81), remaining were kept on medical management. Stented territory was LAD 45.7% (37) and RCA 39.5% (32) and LCX 14.8% (12). Common stent used;Everolimus 61.4% (54), Sirolimus 25% (22), Progenitor cell with sirolimus 2.3%(2) and Zotarolimus 11.4% (10) Conclusion(s): In the era of COVID-19, in this prospective cohort study, on acute STEMI patient management, we found that Pharmaco therapy by Tenecteplase and Streptokinase, reduced patient symptom and ST resolution partially. Therefore, coronary angiogram and subsequent Rescue PCI by Drug Eluting Stents (DES) are key goals of complete revascularization.Copyright © 2023

Effets pervers de la COVID-19 sur les soins dans deux hopitaux de reference en Tunisie.

Contexte: Des multiples effets collateraux de la lutte contre la pandemie de COVID-19, sur les systemes de sante ont ete recemment reveles. L'objectif de cette etude est d'evaluer l'impact de la COVID-19 sur la performance des soins dans les hopitaux de 3e ligne, a Sousse (Tunisie). Methodes: Il s'agit d'une etude quasi-experimentale de type avant/apres, durant les trois mois de mars, avril et mai, en 2019 (avant) et en 2020 (apres) dans deux services traceurs de la pratique medicale de reference a Sousse (Tunisie): Chirurgie generale (CHU Sahloul) et Oncologie (CHU Hached). Les urgences abdominales et le cancer du sein ont ete les problemes de sante inclus dans l'audit clinique. L'impact de la COVID-19 a ete evalue a travers les indicateurs d'acces aux soins, de la gravite des maladies et de la flexibilite de l'offre des soins. Resultats: Au total, 196 patients en 2019 et 153 patients en 2020 ont ete inclus. En chirurgie generale, 68,9 % (n=71) des patients ont consulte apres un jour de l'apparition des symptomes en 2020, versus 52,3 % (n=68) en 2019 (p<0,05), avec plus de peritonites : 47,6 % (n=49) versus 30 % (n=39), p<10-2. Au service d'oncologie, le delai median entre le diagnostic et le traitement etait de 3 [2,75-6] mois en 2019 contre 4 [2.5-6] (p=0,61), sans changement des schemas therapeutiques et sans contextualisation. Discussion/Conclusion: La lutte contre la COVID-19 a ete accompagnee de difficultes a l'acces aux soins avec un retard de consultation entrainant des formes cliniquement compliquees. En plus, la faible flexibilite du systeme de soins a adapter l'offre avec les contraintes de la pandemie, a impacte negativement la performance globale de conservation des acquis et de riposte contre les pandemies. D'ou l'urgence de renforcement de la resilience des structures de sante face aux epidemies emergentes. Declaration de liens d'interets: Les auteurs declarent ne pas avoir de liens d'interets.Copyright © 2022

Acceptance of the Learning Management System in the Time of COVID-19 Pandemic: An Application and Extension of the Unified Theory of Acceptance and Use of Technology Model

After the spread of the coronavirus around the world, the Egyptian government imposed blended learning on higher education institutions. Consequently, colleges and universities in Egypt are entering a new era where learning is not confined to the classroom alone but also through learning management systems (LMSs). Thus, this study adopts the Unified Theory of Acceptance and Use of Technology (UTAUT) to study how students accept and use the LMSs. An online survey was conducted through a structured questionnaire to collect quantitative data for analysis. Obtained data from 803 respondents were analyzed using structural equation modelling Partially least squares regression was used for the model and hypothesis testing. The results show that trust is vital in determining the acceptance and use of LMSs. The study results may provide insights into a better approach to promoting LMS acceptance.

Single Minute Exchange Die (SMED): A sustainable and well-timed approach for Bangladeshi garments industry

Bangladesh is the second largest Ready-Made Garments (RMG) exporting country after China. The cost of cotton and other raw materials, labor cost, and subsidiary cost increased much in post COVID-19 with the comparison of pre-Covid-19 times, but from the prospect of buyer's price is not increasing that much. In this context, our study focused on the RMG's very first time extensive Quick Changeover (QCO) process to minimize cost reduction as well as wastage and time using Single Minute Exchange Die (SMED). Initially, concentrated on the learning period to make acknowledge the changing phase of one style to another. At the same time, tried to figure out the overall weekly performance before and after implementing QCO on the floors, efficiency, before and after implementing QCO hit rate and time consumption, and wastages. According to the case study, floor one had the best average weekly performance, action achieved percentage, and efficiency performance of 57%, 48%, and 46%, respectively, among the five, analyzed floors. From the investigated five floors, the third one had the lowest weekly performance, percentage of actions completed, and efficiency, at 52%, 40%, and 34%, respectively. In the case of hit styles, floor two and floor five both achieved 83% after QCO apply in the floors. During the QCO, the highest production loss on floor one was the alarming sign which was 21,940 pieces and on floor three loss production was the lowest 2605 pieces after QCO implementation. © 2022 The Authors

A Developing Crisis in Hunger: Food Insecurity within 3 Public Colleges before and during the COVID-19 Pandemic

During the COVID-19 pandemic, food insecurity increased across the United States, with college students being particularly vulnerable. This study surveyed 1989 undergraduates attending three public colleges before and during the first year of the pandemic. At all times, students' food insecurity was related to worse academic performance, greater housing insecurity, poorer psychological and physical health, and less access to healthcare. Compared to pre-pandemic students, during-pandemic students reported greater use of and fewer barriers to food programs, spending more on and and receiving more government aid for food, experiencing more academic difficulties due to food insecurity, having greater housing insecurity, and enduring less access to healthcare. © 2022 Taylor & Francis Group, LLC.

Null-values imputation using different modification random forest algorithm

Today, the world lives in the era of information and data. Therefore, it has become vital to collect and keep them in a database to perform a set of processes and obtain essential details. The null value problem will appear through these processes, which significantly influences the behaviour of processes such as analysis and prediction and gives inaccurate outcomes. In this concern, the authors decide to utilise the random forest technique by modifying it to calculate the null values from datasets got from the University of California Irvine (UCL) machine learning repository. The database of this scenario consists of connectionist bench, phishing websites, breast cancer, ionosphere, and COVID-19. The modified random forest algorithm is based on three matters and three number of null values. The samples chosen are founded on the proposed less redundancy bootstrap. Each tree has distinctive features depending on hybrid features selection. The final effect is considered based on ranked voting for classification. This scenario found that the modified random forest algorithm executed more suitable accuracy results than the traditional algorithm as it relied on four parameters and got sufficient accuracy in imputing the null value, which is grown by 9.5%, 6.5%, and 5.25% of one, two and three null values in the same row of datasets, respectively.

A Psychometric Analysis of Somatic and Cognitive Factors of Anxiety in Healthcare Workers during COVID-19 Pandemic Based on State-Trait Inventory for Cognitive and Somatic Anxiety Scale: An Observational Study

Background: The Pandemic of COVID-19 has put healthcare workers under significant psychological pressure. This aimed to analyze the cognitive and somatic components of anxiety among healthcare workers using the State-Trait Inventory for Cognitive and Somatic Assessment Scale (STICSA) before and during the pandemic. In this observational study, 300 healthcare workers were analyzed using the STICSA questionnaire. Various demographic data like age, gender, marital status, educational background, sleep duration was collected. The somatic and cognitive dysfunction score were compared using an independent sample T-test between gender, duration of sleep, etc. Somatic and cognitive dysfunction severity was compared with demographic and pandemic-related parameters using the Chi square test. Result(s): Among 300 participants, the majority (83%, n=249) were below 29 years of age, 159(53%) were females. In respect to duration of sleep during the pandemic, the total score was 40.85 +/- 13.3 in participants sleeping less than 7 hours and 35.83 +/- 11.7 among participants sleeping more than7 hrs. This difference in total score and duration of sleep between the groups was statistically significant (P value 0.001). The mean total score of somatic and cognitive dysfunction before the pandemic was 34.88 +/- 11.527, and it was 38.03 +/- 12.655 during the pandemic. The difference in scores before the pandemic and during the pandemic was statistically significant (P value <0.001). Conclusion(s): This study gives enough evidence that anxiety levels have increased and duration of sleep has decreased among health care workers during this pandemic, with cognitive dysfunction being more profound than somatic dysfunction.. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Impact of QR-Codes as a Disruptive Technology during the Covid-19 Contagion

Introduction In the world economy, QR codes became very popular, and their prominence is expanding rapidly. The QR-codes look a bit like barcodes, but are made up of square patterns. As businesses are increasingly embracing these technologies, QR codes are becoming more popular, QR code readers are being integrated into smartphones. Apple released iOS 11 to search QR codes using the smartphone camera back in 2017 which is now a game-changing marketing strategy for businesses and retailers. Objective: The objective of the paper is to conduct an extensive theoretical review on the growth of QR codes in the digital era and QR codes' reach as contactless payment solutions. Methodology: A bibliometric review by refereeing quality articles published in highly ranked journal. Conclusion: When the QR code reader was integrated into the new Android smartphone camera, it proved to be a key differentiator. Following the global COVID-19 contagion, there has been a nudge for contactless activities and remote resource allocation, such as online work, payments and online classes among others. QR-codes have seen a spectacular increase in usage across all aspects of life. © 2022 The authors.

Null-values imputation using different modification random forest algorithm

Today, the world lives in the era of information and data. Therefore, it has become vital to collect and keep them in a database to perform a set of processes and obtain essential details. The null value problem will appear through these processes, which significantly influences the behaviour of processes such as analysis and prediction and gives inaccurate outcomes. In this concern, the authors decide to utilise the random forest technique by modifying it to calculate the null values from datasets got from the University of California Irvine (UCL) machine learning repository. The database of this scenario consists of connectionist bench, phishing websites, breast cancer, ionosphere, and COVID-19. The modified random forest algorithm is based on three matters and three number of null values. The samples chosen are founded on the proposed less redundancy bootstrap. Each tree has distinctive features depending on hybrid features selection. The final effect is considered based on ranked voting for classification. This scenario found that the modified random forest algorithm executed more suitable accuracy results than the traditional algorithm as it relied on four parameters and got sufficient accuracy in imputing the null value, which is grown by 9.5%, 6.5%, and 5.25% of one, two and three null values in the same row of datasets, respectively.

A Template Matching Based Cough Detection Algorithm Using IMU Data From Earbuds

Coughing is a common symptom across different clinical conditions and has gained further relevance in the past years due to the COVID-19 pandemic. An automated cough detection for continuous health monitoring could be developed using Earbud, a wearable sensor platform with audio and inertial measurement unit (IMU) sensors. Though several previous works have investigated audio-based automated cough detection, audio-based methods can be highly power-consuming for wearable sensor applications and raise privacy concerns. In this work, we develop IMU-based cough detection using a template matching-based algorithm. IMU provides a low-power privacy-preserving solution to complement audio-based algorithms. Similarly, template matching has low computational and memory needs, suitable for on-device implementations. The proposed method uses feature transformation of IMU signal and unsupervised representative template selection to improve upon our previous work. We obtained an AUC (AUC-ROC) of 0.85 and 0.83 for cough detection in a lab-based dataset with 45 participants and a controlled free-living dataset with 15 participants, respectively. These represent an AUC improvement of 0.08 and 0.10 compared to the previous work. Additionally, we conducted an uncontrolled free-living study with 7 participants where continuous measurements over a week were obtained from each participant. Our cough detection method achieved an AUC of 0.85 in the study, indicating that the proposed IMU-based cough detection translates well to the varied challenging scenarios present in free-living conditions. © 2022 IEEE.

Enhancing a nutrition and self-management: An intervention program via teletherapy for teenager with ADHD. A pilot case study

Introduction: Several ADHD teenagers had difficult behavioral problems during countries closing down due to Covid-19 pandemic. One of these negative outcomes that parents cannot control children's behavior toward desired unhealthy food and the impulsive consequences. It was a great opportunity to convention a teletherapy program as a tool of intervention seeking for help to reduce uncontrolled self- management and nutrition, which may affect all sorts of childhood growth, development, health and behavior. Furthermore, it can affects daily life and academic success. Objective(s): We tried through our study to enhance the teletherapy as a therapeutic tool, during the first and second phase of Covid-19 pandemic, trying to help parents and patient to overcome the impulsive behavior by using a specific therapy technique based on nutrition and behavioral therapy Methods: Our case study is a young girl aged 12:4 Yrs. In middle bilingual Arabic/ American School. The therapeutic program designed via teletherapy program using multi-media and thru multi phases sessions, to increase focus attention, emotional control and reduce impulsivity. Result(s): The outcomes of the enhancing nutrition and behavior teletherapy program, showed significant improvement for the specific goal. Sensible change in the girl's impulsive behavior, more focusing, emotional control and more accepting about health nutrition habits. Conclusion(s): The important finding that intensive, focused nutation and self-management techniques provided via teletherapy as solitary program brought benefits to individual's, family and reduced impulsivity outcomes. In addition, family education to become an expert at learning simple techniques in daily life can brining a sense of pleasure for long life wellbeing.

Breaking the transverse-magnetic polarized light emission bottleneck of AlGaN LED using nano-patterned substrates and Al reflector

Ultraviolet light-emitting diodes based on Al-rich AlGaN semiconductors operating in the 210 nm-280 nm have drawn significant interest for many critical applications, including water purification, disinfection of air and surface as preventive measures of SARS COV-2, sterilization, etc. However, for the above-mentioned applications, the current technology still relies on toxic and inefficient mercury-based UV lamps. Driven by the immense need for an efficient, mercury-free, compact alternative technology, future water purification and disinfection technologies require the development of high-efficiency UV-C light-emitting diodes. To date, the external quantum efficiency (EQE) in AlGaN quantum well (QW) UV-LED heterostructures has been severely limited due to several factors including large densities of defects/dislocations, extremely low light extraction efficiency (LEE) of dominant transverse magnetic (TM) light, absorptive p -GaN contact, and total internal reflection (TIR). © 2022 IEEE.

Cardiac Comorbidities Impact on the Outcomes in Severe COVID-19 Infection

Background: COVID-19 is now a global pandemic, with the officially recorded number of affected individuals approaching 4 billion patients. Aim of the Work: Our purpose is to study the effect of cardiac comorbidities on the outcomes of severely infected COVID-19 patients. Patients and Methods: This study included 147 patients with severe COVID-19. All data were analyzed regarding demographic risk factors, associated diseases, mode of oxygen therapy administration, and echocardiography. Result(s): The death rate (DR) in patients with severe COVID-19 and no comorbidities was 7.7%. In patients who had only one risk factor as smoking, hypertension (HTN), or diabetes mellitus (DM), the DR was 16.7%, 33.3%, and 8.3%, respectively. The addition of one risk factor to HTN increased DR in the case of DM (36.8%) and in the case of smoking (40%). Regarding the outcomes, the percentage of the patients affected was as follows: impaired left ventricular ejection fraction (LVEF) <50% (19.7%), dilated right ventricular (RV) basal dimension (12.2%), decreased tricuspid annular plane systolic excursion <17 mm (8.2%), increased SPAP >30 mmHg (53.7%), and pericardial effusion (23.1%). Patients were subclassified according to the presence of HTN. The hypertensive group had increased LV wall thickness and LV end-systolic dimension and impaired LVEF and fraction of shortening than normotensive patients. DR for females and males treated by high-flow nasal cannula was (3.3% vs. 6.9%), continuous positive airway pressure (0% vs. 3.2%), and mechanical ventilation (100% vs. 90.5%). The suggested score was significantly higher in the death group (P < 00001). The DR increased markedly with the incremental rising score. Conclusion(s): Comorbidities, age, and delayed presentation with decreased oxygen saturation had a cumulative risk that can predict the outcome of COVID-19 patients. The presence of HTN alone or associated with other risk factors had a higher DR than other risk factors. Copyright © 2022 International Journal of the Cardiovascular Academy.