ABSTRACT
BACKGROUND: COVID-19 continues to be an ongoing problem worldwide, especially for those who are disproportionately affected due to their social determinants of health, as they are often at a socioeconomic disadvantage. We are primarily interested in evaluating how education level, income, race, ethnicity, and obesity are correlated with acute COVID-19 severity, and anxiety, depression, and quality of life ≥ 6 months post-infection. Specifically, obesity (BMI > 30), has been previously identified as a risk factor for COVID- 19 regarding severity and mortality. We found it imperative to further investigate these demographic variables, as they are vital in understanding how social determinants of health are impacting COVID-19 outcomes. Insights from this study can assist with identifying gaps in care for those with poor social determinants of health, as well as help shape care for those who have been disproportionately affected. METHODS: We examined records of COVID-19 patients through the COVID-19 Recovery Clinic at George Washington University in Washington, D.C. that has been collecting data on patient short and long-term COVID-19 outcomes in various domains along with demographic information since November 2020. Using RStudio with calculations of descriptive data, odds ratios, and p-values using Fisher's exact test, we assessed education level, income, race, ethnicity, and obesity and looked at how they correlated with COVID-19 severity at diagnosis, presence of anxiety, depression and quality of life ≥ 6 months after acute infection. RESULTS: From our sample (n=150), we found African Americans had greater acute COVID-19 severity (OR=7.56, 95% CI 2.22, 25.68, p=0.0015) relative to white individuals. We also found that obesity was associated with higher levels of acute COVID-19 severity (OR=4.89, 95% CI 1.36, 17.60, p=0.022).Additionally, during acute COVID-19 infection, 7/32 (21.9%) obese patients compared to 9/112 (8.0%) non-obese patients were hospitalized (OR=3.79, 95%CI=1.23, 11.68, p=0.03).No significant association was found between anxiety, depression, quality of life or COVID- 19 severity and persistent symptoms. CONCLUSIONS: We observed associations between the African American race and more severe acute COVID-19 infection. Further, in the acute phase, we observed that obese patients were more likely than non-obsese patients to have more severe infection and be hospitalized. These findings highlight preexisting gaps in healthcare outcomes regarding social determinants of health. It is essential to analyze many of the potential longer-term effects of COVID-19 infection, as they remain poorly understood. We conclude that larger studies are necessary to better understand the effects of social determinants of health on both short and long-term outcomes of COVID-19.
ABSTRACT
BACKGROUND: During the COVID-19 pandemic, most attention has been focused on the acute phase of the disease, but lingering symptoms from the postacute sequelae of COVID-19 (PASC) merit concern. The George Washington University COVID-19 Recovery Clinic is documenting these presentations to better understand PASC and its precipitating factors. The group implemented definitions for six phenotype categories: pulmonary, cardiac, connective tissue, vascular, central nervous system (CNS), and other. This research seeks to identify pre-existing factors that could affect disease severity, understand their effect on PASC symptoms at 6-15 months post-infection, and determine associations between patient history and PASC phenotypes. METHODS: An IRB-approved, retrospective cohort study was performed from charts of adult patients with persistent symptoms after acute COVID-19. Data were ed from clinical history prior to COVID-19 diagnosis, during acute COVID-19, and during the post-acute phase, including laboratory results and responses from mental health assessment tools. PASC phenotypes were determined clinically and hospitalization was used as a proxy for disease severity. Descriptive statistics, unadjusted odds ratios, and significance tests (Fisher's exact test, Chi-square test, and Mann-Whitney U test) were calculated using RStudio (4.1.1). RESULTS: Study participants with persistent symptoms at 6-15 months postinfection (n=116) had a mean age of 45.16 (SD 13.23), of which 70% were female, 60% were Caucasian, 12% were African-American, 9% were Asian, and 3% were Hispanic/Latino. When including all patients who had persistent symptoms at 1-15 months post-infection, those with obesity (BMI ≥30) or type 2 diabetes were much more likely to undergo a severe acute phase of COVID19 (OR 12.75;95% CI 1.91-84.95;p=0.02;n=61 and OR 34.67;95% CI 4.43-271.46;p<0.001;n=61 respectively). At 6-15 months post-infection, those suffering from a pulmonary PASC phenotype were more likely to have smoked (OR 3.27;95% CI 1.18-9.11;p=0.02;n=91). At the same period, those presenting with at least one CNS phenotype had a significantly higher level of C-reactive protein (CRP) than those without a CNS phenotype presentation (Mean 3.70 mg/L, SD 5.19 vs. Mean 1.26 mg/L, SD 2.36;p=0.009;n=53). Additionally, acute phase severity was not significantly associated with the presence of PASC. CONCLUSIONS: Our research further demonstrates the increased risk of severe acute COVID-19 among patients with obesity and type 2 diabetes. Furthermore, we show that those with a smoking history were more likely to continue to have pulmonary symptoms of COVID-19 at 6-15 months postinfection. Additionally, our study suggests that there may be a relationship between CRP and persistent CNS symptoms. A better understanding of these associations can help predict the full burden of COVID-19 and improve clinical guidance.
ABSTRACT
Background Patients are hesitant to enter a dental hospital because of the significant danger of cross infection and illness transmission due to rapid spread of corona virus. Objective To assess knowledge regarding Covid-19, oral health practices and circumstances on dental treatment during a pandemic. Method Cross sectional study was conducted among patients visiting dental department of Dhulikhel hospital from September to October 2020. Questionnaires were interviewed following safety protocols regarding the pandemic and descriptive analysis was performed. Both verbal and written consent as well as ethical approval was taken before the study. Result A total 411 patients aged 14 to 75 years old from 14 different districts across Nepal participated in the study. All of the patient were free of Covid-19 symptoms and had strong knowledge and awareness about disease transmission. During the crisis 96% of the people maintain good oral hygiene while 25.8% acquire new dental problems where majority experienced oral discomfort and swelling, 93.2% of them did not attend a dental clinic or hospital in the interim owing to fear and inaccessibility. Majority of the participants were impressed by the safety precautions and preparations during treatment and 99.3% strongly suggest or pledge to visit dental department if necessary during the pandemic. Conclusion Dental patient visiting Dhulikhel hospital is highly aware of current health crisis, possible transmission and preventive measures. Proper safe hospital setup can encourage them to seek dental treatment during crisis. Dental pain and swelling in Endodontic department recorded most common dental emergency during this pandemic.
ABSTRACT
The COVID-19 pandemic has been spreading and affecting worldwide. On 30th January 2020 India reported its first coronavirus confirmed case. The main aim of the proposed work is to devise an algorithm for prediction of Covid-19 cases in India. In this paper, we propose to use time-series algorithms, Autoregressive Integrated Moving Average (ARIMA) and Autoregressive (AR). We have simulated the designed algorithm with the dataset of COVID-19 till 20th February, 2021 for the wave1 and from 01st March, 2021 till 25th September, 2021 we collected data for wave2 and generated 6-days forecasts of confirmed, recovered and death cases. During the 1st wave we observed that there might be another wave 2, after analyzing the wave1 dataset, of coronavirus as result shows that Covid-19 confirmed cases are rising rapidly. Proposed research observations show that the death rate is decreasing, and recovery rate is increasing, one of the possible reasons is herd immunity and vaccination. We are comparing actual cases with forecasting coronavirus cases. ARIMA based models are showing promising results over AR based models. The most difficult part doing this work is to identify parameters due to sudden increase-decrease trend in coronavirus cases. The proposed work reports quality scoring metrics of forecasting for both the models. This will help future researchers to find the best outcome among Auto Regressive Integrated Moving Average (ARIMA) and Auto Regressive (AR) based models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Background and Aims: Cardiovascular comorbidities are common in patients with COVID-19 and these patients are at higher risk of morbidity and mortality. It is not known if the presence of cardiovascular co-morbid conditions poses independent risk or whether this is mediated by other factors. Methods: This is a retrospective follow up study done at Shahid Gangalal National Heart Centre (SGNHC). The main objective of this study was to study the clinical profile, baseline comorbidities, and outcome of cardiac patients and health care worker diagnosed with COVID 19. This study retrospectively evaluated case records of all cardiovascular disease (CVD) patients admitted at SGNHC with COVID 19 cases from 1st case diagnosed on July at SGNHC till September 2020. Results: During this study period, 90 patients with COVID 19 with cardiovascular disease were admitted. The mean age of the study population was 52.3±19 years with 65.6% being male. Among the study population 52 (57.8%) had past history of cardiovascular disease, hypertension in 18 (20%) cases, diabetes in 8 (8.9%) cases. Among the patients with cardiovascular diagnosis, acute coronary syndrome was most common cardiovascular diagnosis in 23 (25.6% cases) followed by rheumatic heart disease in 21 (23.4%) cases, dilated cardiomyopathy in 7 (7.8% cases), ischemic cardiomyopathy with reduced ejection fraction (EF) in 7 (7.8%) cases, post coronary artery bypass graft (CABG) in 8 (8.9%), post valve replacement in 5 (5.5%), congenital heart disease in 3.3% cases and complete heart block in 3.3% cases. Most of the cases were symptomatic with moderate illness in 46.7% cases, mild illness in 41.4% cases and severe/critical illness in 11.1% cases. Among COVID patients with cardiovascular disease, the mortality was 11.1%. Conclusion: Patients with cardiovascular disease with COVID 19 have more severe COVID 19 symptoms and has higher COVID 19 related death, so strict vigilance and early intervention is needed to improve its outcome.