Long COVID in children

Recently concerns have been raised regarding delayed and persistent clinical manifestations following acute COVID infection. The term "Long COVID” refers to a syndrome with multisystem manifestations, persisting beyond 3months of the onset of acute COVID when other likely causes are excluded. Recently, the World Health Organization proposed a definition for adults that included persistent or fluctuating symptoms, impacting daily life, for at least 2months, following acute COVID, that could not be explained by other diagnoses. The condition is better understood among adults, but similar presentations have also been reported in children less frequently. These include fatigue, muscular weakness, shortness of breath, sleeping difficulty, depression, and anxiety. However, there are insufficient epidemiologic studies on Long COVID in children, and the limited data have various methodological limitations. There is no confirmatory diagnostic test and no specific pharmacological treatment for Long COVID. Therefore, individualized symptomatic treatment and multidisciplinary rehabilitation should be attempted. Severe physical or psychiatric manifestations require an urgent referral and appropriate management. Vaccination for the prevention of COVID, as per the local guidelines, is suggested. © 2023 Elsevier Inc. All rights reserved.

Diagnosis of pediatric COVID-19

Accurate diagnosis of SARS-CoV-2 infection is critical for the management of individuals with suspected COVID-19 diseases, as well as instituting public health measures. The experience gained over twoyears of the pandemic has led to a better appreciation of the scope and utility of various diagnostic modalities. Laboratory tests to diagnose COVID-19 in human beings can be broadly categorized as direct and indirect tests. In children (as in adults), RT-PCR is the current gold standard for diagnosis. RT-PCR detects footprints of the virus and its variants. However, its sensitivity is still less than desired. Rapid antigen tests are less accurate than RT-PCR, but the quick availability of results helps in outbreak control. Antibody tests can be used for retrospective diagnosis of infection, but currently available tests do not correlate with protection conferred by vaccination. The initial hype around chest computed tomography scans for diagnosis has now settled, and it is no longer considered a primary diagnostic modality. There are nonspecific changes in many hematological and biochemical parameters, which are more useful for monitoring disease progression than diagnosis. © 2023 Elsevier Inc. All rights reserved.

Innovations in the Indian Healthcare Industry to Brave the Vuca Times

Volatility, Uncertainty, Complexity, Ambiguity-in a VUCA world the moment of surprise is everywhere, making things extremely unpredictable and planning and strategizing far more challenging. The healthcare industry is witnessing seismic shifts as medicine becomes more personalised, health data becomes valuable, and data sharing becomes essential, demanding the healthcare sector to re-strategise. This research aims to understand the various innovations and change-management techniques based on technology that have been adopted by healthcare industries in today's VUCA world while exploring the innovations needed to drive the Indian healthcare sector in the years to come. Thus, it examines and highlight the implications of the rising emphasis being placed on innovations in the healthcare industry - helping the sector to re-strategise and face the changes in today's VUCA world with greater clarity. This paper is also designed to call attention to and discuss contemporary perspectives taken by top healthcare organisations in India before and during the COVID-19 pandemic. This research is based on secondary data, including intensive analysis of research papers, media articles and grey literature reports, along with examining the recent innovations undertaken by the top healthcare companies and hospitals in India. The findings suggest that moving away from a supply-driven healthcare system toward a patient-centred system is necessary, and therefore organisations in India have to embrace innovation, agility, and adaptability in unison to brave the VUCA times.

Covid-19 Bivalent Booster Effectiveness in People with and without Immune Dysfunction

Background: Data on the effectiveness of the bivalent booster vaccine against COVID-19 breakthrough infection and severe outcomes is limited. Method(s): Using patient-level data from 54 sites in the U.S. National COVID Cohort Collaborative (N3C), we estimated bivalent booster effectiveness against breakthrough infection and outcomes between 09/01/2022 (bivalent vaccine approval date) to 12/15/2022 (most recent data release of N3C) among patients completed 2+ doses of mRNA vaccine. Bivalent booster effectiveness was evaluated among all patients and patients with and without immunosuppressed/compromised conditions (ISC;HIV infection, solid organ/ bone marrow transplant, autoimmune diseases, and cancer). We used logistic regression models to compare the odds of breakthrough infection (COVID-19 diagnosis after the last dose of vaccine) and outcomes (hospitalization, ventilation/ECMO use, or death <=28 days after infection) in the bivalent boosted vs. non-bivalent boosted groups. Models controlled for demographics, comorbidities, geographic region, prior SARS-CoV-2 infection, months since the last dose of non-bivalent vaccine, and prior non-bivalent booster. Result(s): By 12/15/2022, 2,414,904 patients had received 2+ doses of mRNA vaccination, 75,873 of them had received a bivalent booster vaccine, and 24,046 of them had a breakthrough infection. At baseline, the median age was 52 (IQR 36-67) years, 40% male, 63% white, 10% Black, 12% Latinx, 3.5% Asian American/Pacific Islander, and 14% were patients with ISC. Patients received a bivalent booster were more likely to be female and had comorbidities. Bivalent booster was significantly associated with reduced odds of breakthrough infection and hospitalization (Figure). The adjusted odds ratios comparing bivalent vs. non-bivalent group were 0.28 (95% CI 0.25, 0.32) for all patients and 0.33 (95% CI: 0.26, 0.41) for patients with ISC. Compared to the nonbivalent group, the bivalent group had a lower incidence of COVID-19-related hospitalization (151 vs. 41 per 100,000 persons), invasive ventilation/ECMO use (7.5 vs. 1.3 per 100,000 persons), or death (11 vs. 1.3 per 100,000 persons) in all patients during the study period;the incidence of severe outcomes after bivalent boosting was similar among patients with and without ISC. Conclusion(s): A bivalent booster vaccine was highly effective against COVID-19 breakthrough infection and severe outcomes among patients received 2+ doses of mRNA vaccine and offered similar protection in patients with and without ISC. (Figure Presented).

PiMS: A Pre-ML Labelling Tool

Machine Learning (ML) techniques in clinical decision support systems are scarce due to the limited availability of clinically validated and labelled training data sets. We present a framework to (1) enable quality controls at data submission toward ML appropriate data, (2) provide in-situ algorithm assessments, and (3) prepare dataframes for ML training and robust stochastic analysis. We developed and evaluated PiMS (Pandemic Intervention and Monitoring Systems): a remote monitoring solution for patients that are Covid-positive. The system was trialled at two hospitals in Melbourne, Australia (Alfred Health and Monash Health) involving 109 patients and 15 clinicians.

A Study on Metaverse in Education

Most nations have used online meeting software platforms for distant education in some capaci ty during the COVID-19 epidemic. These software applications do, however, have substantial drawbacks that hinder engagement and fall short of simulating the classroom environment. Many of these restrictions are resolved by the newly forming Metaverse. In education in Metaverse, learners have the opportunity to engage with digital content and each other in a more interactive and immersive way. For example, learners can participate in virtual simulations, role -playing activities, and collaborative projects with other learners from around the world. They can also access a wide range of digital resources, such as virtual textbooks, lectures, and assessments, all within the same platform. This paper reviews different Metaverse models, frameworks for applying Metaverse in the field of education. © 2023 IEEE.

COVID-19 Infection Is Associated with Poor Outcomes in Patients with Intracerebral Hemorrhage (preprint)

Background: Patients with ischemic stroke and concomitant coronavirus 2019 (COVID-19) infection have worse outcomes than those without this infection. However, research on the impact of COVID-19 infection on outcomes following hemorrhagic stroke remains limited. We aim to study whether concomitant COVID-19 infection leads to worse outcomes in spontaneous intracerebral hemorrhage (ICH).Design: We conducted an observational study using data from Get With The Guidelines Stroke, an ongoing, multi-center, nationwide quality assurance registry. Methods: We implemented a two-stage design: first, we compared outcomes of ICH patients with and without COVID-19 infection admitted during the pandemic (from March 2020 to February 2021). Second, we compared the same outcomes between ICH patients admitted before (March 2019 to February 2020) and during (March 2020 and February 2021) the pandemic. Main outcomes were poor functional outcome (defined as a modified Rankin Scale of 4 to 6 [mRS] at discharge), mortality and discharge to skilled nursing facility (SNF) or hospice. Results: The first stage included 60,091 COVID-19-negative and 1,326 COVID-19-positive ICH patients. In multivariable analyses, ICH patients with versus without COVID-19 infection had 68% higher odds of poor outcome (OR 1.68, 95%CI 1.41-2.01), 51% higher odds of mortality (OR 1.51, CI 1.33-1.71) and 66% higher odds of being discharged to a SNF/hospice (OR 1.66, 95%CI 1.43-1.93). The second stage included 62,743 pre-pandemic and 64,681 intra-pandemic ICH cases. In multivariable analyses, ICH patients admitted during versus before the COVID-19 pandemic had a 10% higher odds of poor outcome (OR 1.10, 95%CI 1.07-1.14), 5% higher mortality (OR 1.05, 95%CI 1.02-1.08) and no significant difference in the risk of being discharged to SNF/hospice (OR 0.93, 95%CI 0.90-0.95). Conclusions: The pathophysiology of the COVID-19 infection and changes in healthcare delivery during the pandemic played a role in worsening outcomes in this patient population. Further research is needed to identify these factors and understand their effect on the long-term outcome.

Predicting the financial behavior of Indian salaried-class individuals

COVID-19 has caused not only unprecedented health crises but also economic crises among individuals across the world. White-collar (salaried-class) employees with a fixed salary face financial insecurity due to job loss, pay cuts and uncertainty in retaining a job. This study examines the financial behavior of Indian white-collar salariedclass investors to their cognitive biases. In addition, the mediating effect of financial self-efficacy on cognitive biases and financial behavior is examined. Respondents were given structured questionnaires (google forms) through emails and WhatsApp for data collection. SPSS and R-PLS are used to analyze the data. Conservatism (r = -.603, p < 0.05) and herding bias (r = -.703, p < 0.05) have a significant negative correlation with financial behavior. Financial self-efficacy has a significant positive correlation (r =.621. p < 0.050). Conservatism and herding predicted 60.5% and 62.2% of the variance, respectively. The direct and indirect paths between conservatism bias, financial self-efficacy, and financial behavior are significant. The paths between herding, financial self-efficacy and financial behavior are also significant. © Ankita Mulasi, Jain Mathew, Kavitha Desai, 2022.

Novolutions in Covid-19: a Mocktail of decision dilemmas a live case analysis

A live case study incorporates experiential learning through a modified version of the case method pedagogy that treats students as consultants (Roth & Smith, 2009). It is defined by Simpkins (2001, p 1) as a case-based teaching method using a "current problem or issue that a company is investigating where the company provides information regarding the problem/issue seeking input to assist in management decisions. ” This case on Novolutions is presented as one applicable for Management Education in the area of decision-making in crisis situations. The case showcases the feedback of 33 students, organized into 5 teams, attending a graduate course in Business Analytics as part of their master's degree program in management. They were presented with a Live Case Study featuring decision-making issues encountered during the COVID-19 pandemic by an Indian entrepreneur-duo running a bootstrapped product company, Novolutions, which manufactures the Hippie Mocktail.

Change in quality of life, sleep, and physical activity during COVID-19: A longitudinal study of adolescent athletes.

CONTEXT: The abrupt cessation of school and sport participation during the COVID-19 pandemic may have negative implications for adolescent mental health. OBJECTIVE: (1) To compare mental, physical, and social health and behaviors during pandemic-related stay-at-home mandates with the same measures collected 1-2 years prior. (2) To assess the relationship of physical activity and sleep during the pandemic with anxiety, fatigue, and peer relationship changes between assessment timepoints. DESIGN: Prospective cohort study, repeated-measures. SETTING: Pediatric sports medicine center. PARTICIPANTS: High school athletes (n=39; 16.2±0.9 years of age; 64% female). MAIN OUTCOME MEASURES: Patient Reported Outcome Measurement System (PROMIS) anxiety, fatigue, and peer relationships short forms and the Pittsburgh Sleep Quality Index (PSQI) were completed at two timepoints (initial assessment: May 2018 or 2019; follow-up assessment: May/June 2020). Physical activity frequency and duration, and frequency of interaction with other individuals (family, peers, sport coaches, etc.), were self-reported at follow-up assessment for the two weeks prior to school/sport closure and the two weeks prior to questionnaire completion. RESULTS: Higher levels of anxiety (5.5±4.0 vs. 3.6±3.4; p=0.003) and fatigue (5.4±3.7 vs. 2.3±2.5; p<0.001), and worse sleep quality (6.6±2.9 vs. 4.3±2.3; p<0.001) were observed during the pandemic compared to previous assessments. Reductions in physical activity were observed between assessments (exercise duration: 86.4±41.0 vs 53.8±30.0 minutes). Sleep quality, but not physical activity, during the pandemic predicted changes in fatigue (p = 0.03, ß = 0.44 [0.06, 0.83]) and peer relationships (p = 0.01, ß = -0.65 [-1.16, -0.15]) from initial to follow-up assessment. CONCLUSIONS: Mental and physical health declined during stay-at-home mandates, compared to assessments 1-2 years earlier. Physical activity behaviors and sources of social interaction underwent significant changes following school and sport cessation. Quality sleep may provide some protection against declining adolescent mental health during the pandemic, although this relationship requires further investigation.

Safety and Efficacy of Topical Lovastatin Plus Cholesterol Cream vs Topical Lovastatin Cream Alone for the Treatment of Disseminated Superficial Actinic Porokeratosis: A Randomized Clinical Trial.

Importance: Disseminated superficial actinic porokeratosis (DSAP) is an inherited or sporadic disorder of keratinization associated with germline variations. There is no effective standard of care therapy for DSAP, but treatment with topical lovastatin combined with cholesterol cream has shown promise. Objectives: To evaluate and compare the safety and efficacy of topical lovastatin 2% plus cholesterol 2% cream (lovastatin-cholesterol) and topical lovastatin 2% cream (lovastatin) alone in adults diagnosed with DSAP. Design, Setting, and Participants: This patient- and assessor-blinded, randomized clinical trial was conducted at the Medical University of South Carolina between August 3, 2020, and April 28, 2021. Nonpregnant adults with a previous clinical or histological diagnosis of DSAP were eligible. Data were blindly analyzed after study completion. Interventions: Participants were randomized to once- or twice-daily application of either lovastatin-cholesterol cream (n = 17) or lovastatin cream (n = 14) to symptomatic regions for 12 weeks. Main Outcomes and Measures: The primary efficacy measure was the effect of the treatment on DSAP at the end of treatment (12 weeks) as measured by the DSAP General Assessment Severity Index (DSAP-GASI; scored from 0-4, with 0 indicating clear and 4 indicating severe). Treatment efficacy was based on investigator-standardized photographs provided by the participants because of the need for evaluation via telehealth during the COVID-19 pandemic. Secondary efficacy measures included patient-reported outcomes, application frequency, and adverse events (AEs). Results: Of the 87 participants screened, 32 were enrolled. One participant randomized to receive lovastatin-cholesterol did not receive the intervention, leaving 17 participants (mean [range] age, 59.2 [40-83] years; 13 females [76.5%]; all White) allocated to receive lovastatin-cholesterol treatment and 14 participants (13 female [92.9%]; mean (range) age, 53.7 [33-71] years; all White) to receive lovastatin treatment. Twelve participants in each treatment group qualified for the analysis. Disease severity decreased from week 1 to week 12 by 50.0% (from 3.08 [95% CI, 2.57-3.60] to 1.54 (95% CI, 1.04-2.05] points on the DSAP-GASI; P < .001) in the lovastatin-cholesterol group and 51.4% (from 2.92 [95% CI, 2.40-3.43] to 1.50 [95% CI, 0.99-2.01] points; P < .001) in the lovastatin group. There was no significant difference between the treatment groups according to application frequency at the end of 12 weeks. Adverse events reported included myalgia (n = 2), elevation in the creatine kinase level (n = 1), application discomfort (n = 4), and rash (n = 1). No serious AEs occurred, and all participants with an AE were able to complete the study. Conclusions and Relevance: This randomized clinical trial found improvements in DSAP severity in both treatment groups, without serious AEs, indicating a limited benefit with the addition of cholesterol. These results suggest that lovastatin cream may be a new primary treatment option for patients diagnosed with DSAP. Trial Registration: ClinicalTrials.gov Identifier: NCT04359823.

Association of statin use with outcomes of patients admitted with COVID-19: an analysis of electronic health records using superlearner.

IMPORTANCE: Statin use prior to hospitalization for Coronavirus Disease 2019 (COVID-19) is hypothesized to improve inpatient outcomes including mortality, but prior findings from large observational studies have been inconsistent, due in part to confounding. Recent advances in statistics, including incorporation of machine learning techniques into augmented inverse probability weighting with targeted maximum likelihood estimation, address baseline covariate imbalance while maximizing statistical efficiency. OBJECTIVE: To estimate the association of antecedent statin use with progression to severe inpatient outcomes among patients admitted for COVD-19. DESIGN, SETTING AND PARTICIPANTS: We retrospectively analyzed electronic health records (EHR) from individuals ≥ 40-years-old who were admitted between March 2020 and September 2022 for ≥ 24 h and tested positive for SARS-CoV-2 infection in the 30 days before to 7 days after admission. EXPOSURE: Antecedent statin use-statin prescription ≥ 30 days prior to COVID-19 admission. MAIN OUTCOME: Composite end point of in-hospital death, intubation, and intensive care unit (ICU) admission. RESULTS: Of 15,524 eligible COVID-19 patients, 4412 (20%) were antecedent statin users. Compared with non-users, statin users were older (72.9 (SD: 12.6) versus 65.6 (SD: 14.5) years) and more likely to be male (54% vs. 51%), White (76% vs. 71%), and have ≥ 1 medical comorbidity (99% vs. 86%). Unadjusted analysis demonstrated that a lower proportion of antecedent users experienced the composite outcome (14.8% vs 19.3%), ICU admission (13.9% vs 18.3%), intubation (5.1% vs 8.3%) and inpatient deaths (4.4% vs 5.2%) compared with non-users. Risk differences adjusted for labs and demographics were estimated using augmented inverse probability weighting with targeted maximum likelihood estimation using Super Learner. Statin users still had lower rates of the composite outcome (adjusted risk difference: - 3.4%; 95% CI: - 4.6% to - 2.1%), ICU admissions (- 3.3%; - 4.5% to - 2.1%), and intubation (- 1.9%; - 2.8% to - 1.0%) but comparable inpatient deaths (0.6%; - 1.3% to 0.1%). CONCLUSIONS AND RELEVANCE: After controlling for confounding using doubly robust methods, antecedent statin use was associated with minimally lower risk of severe COVID-19-related outcomes, ICU admission and intubation, however, we were not able to corroborate a statin-associated mortality benefit.

PiMS: A Pre-ML Labelling Tool

Machine Learning (ML) techniques in clinical decision support systems are scarce due to the limited availability of clinically validated and labelled training data sets. We present a framework to (1) enable quality controls at data submission toward ML appropriate data, (2) provide in-situ algorithm assessments, and (3) prepare dataframes for ML training and robust stochastic analysis. We developed and evaluated PiMS (Pandemic Intervention and Monitoring Systems): a remote monitoring solution for patients that are Covid-positive. The system was trialled at two hospitals in Melbourne, Australia (Alfred Health and Monash Health) involving 109 patients and 15 clinicians. © 2022 IEEE.

Multiclass Categorisation of Respiratory Sound Signals Using Neural Network

Respiratory diseases have seriously impacted human life in the last couple of years;as Covid 19 arrived, many lost their beloved ones. Since respiratory diseases directly attack the patient's lungs, it is becoming risky day by day for human life and doctors because a confined number of resources are available in hospitals to detect these respiratory diseases, and detection of these diseases is a difficult job to the doctors. Therefore early-stage diagnosis can help the doctor in saving human lives. Researchers are continuously trying to help doctors by designing efficient and more accurate tools for detecting different types of respiratory diseases. This paper uses a convolution-based deep learning model to classify these respiratory diseases using patient respiratory sound signals with Mel frequency cepstral coefficients (MFFCs) as a feature vector. In this paper, we have tried to keep our neural network model as simple as possible with less trainable parameters and good classification accuracy. The model performance is measured in terms of sensitivity, specificity, average score, and harmonic score. © 2022 IEEE.

Association of symptom characteristics and comorbid conditions with viral RNA positivity of Covid-19 patients in Kasaragod district in Kerala, India: A retrospective cohort study.

Background Symptoms of Covid-19 are known to be non-specific ranging from asymptomatic cases to severe illness affecting multiple organ systems. The duration of viral RNA positivity and transmission varies in individuals. We describe the association between symptom characteristics and comorbid conditions with viral RNA positivity of SARSCoV-2 affected individuals. Methods We conducted a record-based retrospective cohort study of 179 patients found to be positive for Covid-19 in Kasaragod district in Kerala. We included details of all patients found positive during the initial phases of the pandemic and recorded details regarding symptoms, duration of viral RNA positivity and the occurrence of transmission. The data were analysed using SPSS. Results Any symptom was present in 68%. Fever (43%) was the most common symptom while 50% had at least one respiratory symptom. Increased duration of viral RNA positivity was found to be associated with presence of comorbid conditions. The majority of individuals who transmitted disease (75%) had some symptom, predominantly a respiratory symptom. Conclusion Respiratory symptoms are seen in half of the patients and viral RNA positivity was for a longer duration in patients with comorbid conditions.

Analysis of Sars-Cov-2-Specific T-Cell Responses Using Novel Single- Cell Multiplexed Isolight in Covid-19 Convalescents

Purpose: COVID-19 has poor outcomes in transplant recipients with reduced antibody responses. However, the exact cellular immune response against SARS-CoV-2 remains largely unclear. We developed novel assays to analyze differential cellular immune responses in individual subjects and groups. Method(s): We assessed the T cell proliferative responses against spike, membrane, and nuclear proteins of SARS-CoV-2, or a mixture of all these peptides (mix) using 3H-thymidine incorporation and CFSE dilution assays. We have also established a SARS-CoV-2-specific multiplexed cytokine IsoLight at single-cell resolution. This is a very powerful technology that employs IsoPlexis' IsoCodechip with 12,000 micro-chambers. Each microchamber is pre-coated with a 32-plex antibody array to capture secreted cytokines. The results were evaluated using IsoSpeak software. Result(s): COVID-19 convalescent subjects (n=3) showed a very strong proliferative response to S/M/N and mix peptides of SARS-CoV-2 when compared to uninfected normal subjects who had only marginal proliferative responses. CFSE dilution assays demonstrated that spike and mix proteins markedly increased the proliferation of CD3 cells comprised of both CD4 and CD8 subsets. In the IsoLight assay, single-cell functional heterogeneity mapping 3D tSNE analysis showed a distinct combinatorial cytokine secretion pattern in stimulated cells compared to unstimulated controls (Fig.1). Polyfunctional activity topography-Principal component analysis (PAT-PCA) revealed that IFN-g, IL2, and MIP-1b drove the polyfunctional heterogeneity. When the percentage of polyfunctional cells (>=2 cytokines/cell), and polyfunctional strength index (PSI) were evaluated, CD8 cells secreted high levels of effector and chemoattractive cytokines while CD4 cells secreted effector and stimulatory cytokines. Most importantly, the depth and breadth of T cell responses, particularly the cytokine polyfunctionality correlated with the severity of the disease the patients had experienced. Conclusion(s): This novel COVID19-specific IsoLight cytokine assay is a powerful technology that can be utilized for in-depth analysis of T cell polyfunctionality at the single-cell level and for further differentiating the anti-SARS-CoV-2 immune capabilities of vulnerable individuals such as transplant patients.

DIARRHEA, ELEVATED AST, AND ELEVATION OF INFLAMMATORYRELATED BIOMARKERS IS A PREDICTOR FOR MORTALITY IN MINORITY HOSPITALISED COVID-19 PATIENTS

Background and Aims: Initial reports on US COVID-19 showed different outcomes in different races. In this study, we use a diverse large cohort of hospitalized COVID-19 patients to determine predictors of mortality. Methods: We analyzed data from hospitalized COVID- 19 patients (n=5,852) from 8 hospitals. Demographics, comorbidities, symptoms and laboratory data were collected. Results: The cohort contained 3,662 (61.7%) African Americans (AA), 286 (5%) American Latinx (LAT), 1,407 (23.9%), European Americans (EA), and 93 (1.5%) American Asians (AS). Survivors and dead patients' mean ages were 58 and 68 for AA, 58 and 77 for EA, 44 and 61 for LAT, and 51 and 63 for AS. Mortality rates for AA, LAT, and EA were 14.8%, 7.3%, and 16.3%. Mortality increased among patients with the following characteristics: age, male gender, New York region, cardiac disease, COPD, diabetes mellitus, hypertension, history of cancer, immunosuppression, elevated lymphocytes, CRP, ferritin, D-Dimer, creatinine, troponin, and procalcitonin. Use of mechanical ventilation, respiratory failure, shortness of breath (SOB) (p<0.01), fatigue (p=0.04), diarrhea (p=0.02), and increased AST (p<0.01), significantly correlated with death in multivariate analysis. Male sex and EA and AA race/ethnicity had a higher frequency of death. Diarrhea was among the most common GI symptom amongst AAs (6.8%). When adjusting for comorbidities, significant variables were age (over 45 years old), male sex, EA, patients hospitalized in Indiana, Michigan, Georgia, and District of Columbia. When adjusting for disease severity, significant variables were age over 65 years old, male sex, EA as well as having SOB, elevated CRP, and D-dimer. Glucocorticoid usage was associated with an increased risk of COVID- 19 death in our cohort. Conclusion: Among this large cohort of hospitalized COVID-19 patients enriched for African Americans, predictors of mortality include male gender, diarrhea, elevated AST, comorbidities, respiratory symptoms and failure, and elevation of inflammatory- related biomarkers. These findings may reflect the extent of systemic organ involvement by SARS-CoV-2 and subsequent progression to multi-system organ failure. High mortality in AA in comparison with LAT is likely related to a high frequency of comorbidities and older age among AA.

Impact of COVID-19-Related Distress on Anxiety and Depression of College Students

The current study explores the impact of COVID-19 related distress factors on the mental well-being of college students. For the purpose of the study, mental well-being is measured through the depression symptoms and general anxiety levels of the students. The study used judgemental sampling to identify the respondents of the study. The final sample consisted of 147 respondents and the data was analysed on SPSS. The results suggested that while COVID-19 distress factors were not significant in predicting the level of depression symptoms experienced by the students, the general anxiety levels were significantly impacted by the distress factors. The findings are particularly useful for the teachers and institutions working to connect and teach through online platforms. © 2022, Commonwealth of Learning. All rights reserved.