A comparison of severity of illness between the SARS-CoV-2 Omicron variant and Delta variant.

Background: The COVID-19 pandemic has disproportionally affected traditionally marginalized groups. Both the Delta and Omicron variants raised concern amongst public health officials due to potentially higher infectivity rates and disease severity than prior variants. This study sought to compare disease severity between adults infected with the Omicron variant and adults infected with the Delta variant who presented to the Emergency Department at an academic, safety-net hospital in Virginia. Methods: This retrospective cohort study used electronic medical record data of patients who presented to the Emergency Department and received a positive SARS-CoV-2 test between September 1, 2021, and January 31, 2022. Positive tests were stratified by genotypic variant through whole genome sequencing. Participants with the Omicron variant were propensity scores matched with individuals with the Delta variant. Results: Among 500 Delta and 500 Omicron participants, 279 propensity score-matched pairs were identified. Participants were predominantly unvaccinated, with medical comorbidities, and self-identified as Black. Individuals infected with the Delta variant had more severe disease compared to those with the Omicron variant, regardless of vaccination status. Patients with kidney, liver, and respiratory disease, as well as cancer, are at higher risk for severe disease. Patients with 2 doses of COVID-19 immunization trended toward less severe disease. Conclusions: Overall, these data further support the literature regarding the disproportionate effects of the COVID-19 pandemic on vulnerable patient populations - such as those with limited access to care, people of color, and those with chronic medical conditions - and can be used to inform public health interventions.

Prevalence and impact of metabolic syndrome on in-hospital outcomes in patients with acute myocardial infarction: A perspective from a developing country.

Acute myocardial infarction (AMI) often suffers from a high prevalence of metabolic syndrome (MetS). However, few studies in developing countries have focused on the effect of MetS on in-hospital outcomes in patients with AMI. We analyzed 199 patients with AMI who underwent primary percutaneous coronary intervention. This study aimed to determine the impact of MetS and factors related to in-hospital outcomes in patients with AMI. The study included 199 patients who met the criteria, with a mean age of 64.5 ±â€…11.3 years. Out Of the total number of patients, 136 (68.3%) were found to have MetS. Patients with MetS were more likely to be female, have a higher body mass index, larger waist circumference, and a higher prevalence of hypertension and diabetes than those without MetS. The rates of major complications, such as cardiogenic shock, heart failure, mechanical complications, and arrhythmias, were not significantly different between the 2 groups. MetS was not associated with in-hospital mortality with OR, 4.92 (95% CI 0.62-39.31, P = .13). In this study, increased waist circumference was associated with an increased all-cause mortality rate. However, the MetS group had a significantly higher rate of cardiovascular mortality than the group without MetS (P = .03). Among patients with AMI, the prevalence of metabolic syndrome was high. Patients with MetS did not exhibit an increased all-cause in-hospital mortality rate. Increased waist circumference is associated with increased all-cause mortality.

Prediction of obstructive coronary artery disease in patients undergoing heart valve surgery: A cross-sectional study in a tertiary care hospital.

Introduction: Estimating the probability of obstructive coronary artery disease in patients undergoing noncoronary cardiac surgery should be considered compulsory. Our study sought to evaluate the prevalence of obstructive coronary artery disease in patients undergoing valvular heart surgery and to utilize predictive methodology of concomitant obstructive coronary artery disease in these patients. Methods: The retrospective study cohort was derived from a tertiary care hospital registry of patients undergoing coronary angiogram prior to valvular heart operations. Decision tree, logistic regression, and support vector machine models were built to predict the probability of the appearance of obstructive coronary artery disease. A total of 367 patients from 2016 to 2019 were analyzed. Results: The mean age of the study population was 57.3±9.3 years, 45.2% of the patients were male. Of 367 patients, 76 (21%) patients had obstructive coronary artery disease. The decision tree, logistics regression, and support vector machine models had an area under the curve of 72% (95% CI: 62% - 81%), 67% (95% CI: 56% - 77%), and 78% (95% CI: 68% - 87%), respectively. Multivariate analysis indicated that hypertension (OR 1.98; P=0.032), diabetes (OR 2.32; P=0.040), age (OR 1.05; P=0.006), and typical angina (OR 5.46; P<0.001) had significant role in predicting the presence of obstructive coronary artery disease. Conclusion: Our study revealed that approximately one-fifth of patients who underwent valvular heart surgery had concomitant obstructive coronary artery disease. The support vector machine model showed the highest accuracy compared to the other model.

Chest X-ray Severity Score as a Putative Predictor of Clinical Outcome in Hospitalized Patients: An Experience From a Vietnamese COVID-19 Field Hospital.

Background Through the coronavirus disease 2019 (COVID-19) pandemic, portable radiography was particularly useful for assessing and monitoring the COVID-19 disease in Vietnamese field hospitals. It provides a convenient and precise picture of the progression of the disease. The purpose of this study was to evaluate the predictive value of chest radiograph reporting systems (Brixia and total severity score (TSS)) and the National Early Warning Score (NEWS) clinical score in a group of hospitalized patients with COVID-19. Methods This retrospective cohort study used routinely collected clinical data from polymerase chain reaction (PCR)-positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients admitted to Field Hospital District 8, Ho Chi Minh City, Vietnam, from August 2021 to September 2021. The initial chest radiographs were scored based on the TSS and Brixia scoring systems to quantify the extent of lung involvement. After the chest radiograph score was reported, two residents calculated the rate of all-cause in-hospital mortality with the consultation of expert radiologists. In this study, NEWS2 scores on hospital admission were calculated. The gradient boosting machines (GBMs) and Shapley additive exPlanations (SHAP) were applied to access the important variable and improve the accuracy of mortality prediction. The adjusted odds ratio for predictor was presented by univariate analysis and multivariate analysis. Results The chest X-rays (CXRs) at the admission of 273 patients (mean age 59 years +/-16, 42.1% were male) were scored. In the univariate analysis, age, vaccination status, previous disease, NEWS2, a saturation of peripheral oxygen (Sp02), the Brixia and TSS scores were significant predictors of mortality (p-value < 0.05). In multivariate analysis, there were statistically significant differences in mortality between age, Sp02, Brixia score, and patients with previous diseases were independent predictors of mortality and hospitalization. A gradient boosting machine was performed in the train data set, which showed that the best hyperparameters for predicting the mortality of patients are the Brixia score (exclude TSS score). In the top five predictors, an increase in Brixia, age, and BMI increased the logarithmic number of probability clarifying as death status. Although the TSS and Brixia scores evaluated chest imaging, the TSS score was not essential as the Brixia score (rank 6/11). It was clear that the BMI and NEWS2 score was positively correlated with the Brixia score, and age did not affect this correlation. Meanwhile, we did not find any trend between the TSS score versus BMI and NEWS2. Conclusion When integrated with the BMI and NEWS2 clinical classification systems, the severity score of COVID-19 chest radiographs, particularly the Brixia score, was an excellent predictor of all-cause in-hospital mortality.

Predicting Anxiety and Depression Among Patients With COVID-19 in Concentrated Isolation at Medical Camps in Vietnam: A Descriptive Cross-Sectional Study.

Introduction: This study aims to assess the requirement for anxiety and depression treatment for patients with coronavirus disease 2019 (COVID-19) in medical camps in Bac Giang province, Vietnam. This information can help improve the government policy to reduce anxiety and depression in patients with COVID-19. Methods: A total of patients with 427 COVID-19 participated in the survey conducted from 5 to 15 June 2021 in Bac Giang province. The survey included 17 questions about the general characteristics of the patients, 15 questions to assess common COVID-19 symptoms, the Patient Health Questionnaire-9 (PHQ-9), and General Anxiety Disorder-7 (GAD-7) scores, and four questions to assess hospital reviews, including facilities, food, medical staff, and living conditions. Logistics regression analyses were conducted to assess the association between COVID-19 symptoms and high anxiety and depression (HAD) status. Results: A logistic regression analysis evaluated the risk factors in need of intervention. Our study showed that lower hospital review scores (odd ratio = 0.98; 95% confident interval = 0.97-0.99) were found to be a risk needing intervention. It was also identified that older patients (odd ratio = 1.1; 95% confident interval = 1.03-1.18), women (odd ratio = 1.31; 95% confident interval = 1.09-1.31), patients who were primary income earners in the family (odd ratio = 1.15; 95% confident interval = 1.03-1.28), patients who had headaches (odd ratio = 1.16; 95% confident interval = 1.06-1.21), and patients who had joint pain (odd ratio = 1.17; 95% confident interval = 1.06- 1.3) were risk factors for HAD status. Conclusion: Our research shows that every 10-year age increase was associated with a 10% increase in the likelihood of HAD status. Study subjects being primary income earners were also associated with a 15% increased risk of having HAD status. This study showed that a decrease in family income due to COVID-19 caused an increase in high-level anxiety/depression status.

The effects of the COVID-19 lockdown on patients with chronic cardiovascular disease in Vietnam.

INTRODUCTION: We evaluated the impact of the lockdown policy during the COVID-19 pandemic on cardiovascular outpatients of a cardiology clinic in Vietnam from April to June 2020. We estimated the occurrence of different cardiovascular problems in general and the stability of blood pressure. METHODOLOGY: During the Covid-19 outbreak in Vietnam, we conducted a cross-sectional study to evaluate its impact on blood pressure stability of hypertensive patients treated as outpatients at the clinic of the University Medical Center (UMC), Ho Chi Minh City. RESULTS: The mean age of the recruited 493 patients was 62.2 ± 10.2 years. The stable blood pressure group consisted of 87% patients, while the unstable blood pressure group consisted of 13% patients. We found that 68% of the study population attended their follow-up appointments as scheduled: 87% with stable blood pressure versus only 13% with unstable blood pressure. Significant differences were noticed in body weight changes and cardiovascular problems between the two groups: body weight increase (22.6% vs. 10.2%), body weight decrease (3.2% vs. 6.7%), worsening of cardiovascular problems (35.5% vs. 17.9%) in the unstable and stable blood pressure groups, respectively. Multivariable regression analysis reflected the impact of the increase in body weight and occurrence of cardiovascular problems on the patients with unstable blood pressure. CONCLUSIONS: Our study provided concrete proof of the impact of the lockdown on chronic patients, which should warrant further surveys, and evaluation of the lockdown policy.

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021.

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19. Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021- Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo. Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pitfalls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation. Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control. Funding: The present study did not receive any external funding.