Prediction models for respiratory outcomes in patients with COVID-19: integration of quantitative computed tomography parameters, demographics, and laboratory features.

Background: We aimed to develop integrative machine-learning models using quantitative computed tomography (CT) parameters in addition to initial clinical features to predict the respiratory outcomes of coronavirus disease 2019 (COVID-19). Methods: This was a retrospective study involving 387 patients with COVID-19. Demographic, initial laboratory, and quantitative CT findings were used to develop predictive models of respiratory outcomes. High-attenuation area (HAA) (%) and consolidation (%) were defined as quantified percentages of the area with Hounsfield units between -600 and -250 and between -100 and 0, respectively. Respiratory outcomes were defined as the development of pneumonia, hypoxia, or respiratory failure. Multivariable logistic regression and random forest models were developed for each respiratory outcome. The performance of the logistic regression model was evaluated using the area under the receiver operating characteristic curve (AUC). The accuracy of the developed models was validated by 10-fold cross-validation. Results: A total of 195 (50.4%), 85 (22.0%), and 19 (4.9%) patients developed pneumonia, hypoxia, and respiratory failure, respectively. The mean patient age was 57.8 years, and 194 (50.1%) were female. In the multivariable analysis, vaccination status and levels of lactate dehydrogenase, C-reactive protein (CRP), and fibrinogen were independent predictors of pneumonia. The presence of hypertension, levels of lactate dehydrogenase and CRP, HAA (%), and consolidation (%) were selected as independent variables to predict hypoxia. For respiratory failure, the presence of diabetes, levels of aspartate aminotransferase, and CRP, and HAA (%) were selected. The AUCs of the prediction models for pneumonia, hypoxia, and respiratory failure were 0.904, 0.890, and 0.969, respectively. Using the feature selection in the random forest model, HAA (%) was ranked as one of the top 10 features predicting pneumonia and hypoxia and was first place for respiratory failure. The accuracies of the cross-validation of the random forest models using the top 10 features for pneumonia, hypoxia, and respiratory failure were 0.872, 0.878, and 0.945, respectively. Conclusions: Our prediction models that incorporated quantitative CT parameters into clinical and laboratory variables showed good performance with high accuracy.

Causing trouble and being transmissible: COVID-19 survivors' experiences of stigma and discrimination in South Korea.

Background: The stigma associated with coronavirus disease (COVID-19) is relatively neglected in policies for handling the disease. Stigmatization occurs only within specific social contexts in local societies. Objective: This study aims to examine COVID-19 survivors' experiences of social stigma and discrimination in South Korea in the first 2 years of the pandemic. Methods: Semi-structured interviews were conducted. Results: Of 52 participants, 45 reported that they had to cope with stigma and discrimination in their intimate social relationships, workplaces, and children's schools, ranging from subtle actions to job loss. Sexual minorities who were involved in mass disease transmission in the early part of the pandemic experienced a higher level of stigmatization. The stigmatization dealt with in this study was related to two themes: survivors' sense of causing trouble and possibility of transmission. Conclusion: By intertwining this stigma with the experiences of public health measures through the voices of survivors, this study reveals the local context of East Asia in terms of culture-specific aspects of COVID-19-related stigma.

COVID-19 drugs: potential interaction with ATP-binding cassette transporters P-glycoprotein and breast cancer resistance protein.

Background: The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2, has resulted in acute respiratory distress, fatal systemic manifestations (extrapulmonary as well as pulmonary), and premature mortality among many patients. Therapy for COVID-19 has focused on the treatment of symptoms and of acute inflammation (cytokine storm) and the prevention of viral infection. Although the mechanism of COVID-19 is not fully understood, potential clinical targets have been identified for pharmacological, immunological, and vaccinal approaches. Area covered: Pharmacological approaches including drug repositioning have been a priority for initial COVID-19 therapy due to the time-consuming nature of the vaccine development process. COVID-19 drugs have been shown to manage the antiviral infection cycle (cell entry and replication of proteins and genomic RNA) and anti-inflammation. In this review, we evaluated the interaction of current COVID-19 drugs with two ATP-binding cassette transporters [P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP)] and potential drug-drug interactions (DDIs) among COVID-19 drugs, especially those associated with P-gp and BCRP efflux transporters. Expert opinion: Overall, understanding the pharmacodynamic/pharmacokinetic DDIs of COVID-19 drugs can be useful for pharmacological therapy in COVID-19 patients.

Post-Intensive Care Syndrome in Non-COVID-19 ICU Survivors during the COVID-19 Pandemic in South Korea: A Multicenter Prospective Cohort Study.

A prospective observational cohort study investigated the prevalence of post-intensive care syndrome (PICS) among non-COVID-19 ICU survivors during the COVID-19 pandemic. Adults who had been admitted to the ICU for more than 24 h were enrolled, and followed-up at 3, 6, and 12 months post-discharge. PICS (mental health, cognitive, and physical domains) was measured using the Hospital Anxiety and Depression Scale, Posttraumatic Diagnosis Scale, Montreal Cognitive Assessment, and Korean Activities of Daily Living (ADL) scale. Data were analyzed from 237 participants who completed all three follow-up surveys. The prevalence of PICS was 44.7%, 38.4%, and 47.3%, at 3, 6, and 12 months of discharge, respectively. The prevalence of PICS in the mental health and cognitive domains decreased at 6 and increased at 12 months. The prevalence of PICS in the physical domain declined over time. Changes in PICS scores other than ADL differed significantly according to whether participants completed follow-up before or after December 2020, when COVID-19 rapidly spread in South Korea. In the recent group, anxiety, depression, post-traumatic stress disorder, and cognition scores were significantly worse at 12 months than at 6 months post-discharge. The COVID-19 pandemic may have adversely affected the recovery of non-COVID-19 ICU survivors.

COVID-19 drugs: potential interaction with ATP-binding cassette transporters P-glycoprotein and breast cancer resistance protein

Background The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2, has resulted in acute respiratory distress, fatal systemic manifestations (extrapulmonary as well as pulmonary), and premature mortality among many patients. Therapy for COVID-19 has focused on the treatment of symptoms and of acute inflammation (cytokine storm) and the prevention of viral infection. Although the mechanism of COVID-19 is not fully understood, potential clinical targets have been identified for pharmacological, immunological, and vaccinal approaches. Area covered Pharmacological approaches including drug repositioning have been a priority for initial COVID-19 therapy due to the time-consuming nature of the vaccine development process. COVID-19 drugs have been shown to manage the antiviral infection cycle (cell entry and replication of proteins and genomic RNA) and anti-inflammation. In this review, we evaluated the interaction of current COVID-19 drugs with two ATP-binding cassette transporters [P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP)] and potential drug-drug interactions (DDIs) among COVID-19 drugs, especially those associated with P-gp and BCRP efflux transporters. Expert opinion Overall, understanding the pharmacodynamic/pharmacokinetic DDIs of COVID-19 drugs can be useful for pharmacological therapy in COVID-19 patients.

Use of the Monoclonal Antibody Regdanvimab to Treat Patients Hospitalized with COVID-19: Real-World Data during the Delta Variant Predominance.

Regdanvimab is the only monoclonal antibody available in Korea that targets severe acute respiratory syndrome coronavirus 2. We retrospectively evaluated the clinical characteristics of 374 adults hospitalized with coronavirus disease 2019 (COVID-19) who were treated with regdanvimab from September through December 2021. In total, 322 (86.1%) patients exhibited risk factors for disease progression. Most patients (91.4%) improved without additional treatment. No patient died or was transferred to intensive care. This study shows that regdanvimab prevented disease progression in high-risk patients with mild to moderate COVID-19 infections during Delta variant predominance.

Quantitative Computed Tomography Parameters in Coronavirus Disease 2019 Patients and Prediction of Respiratory Outcomes Using a Decision Tree.

Background: Chest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build decision trees for predicting respiratory outcomes using the quantitative CT parameters. Methods: Patients hospitalized for COVID-19 were classified based on the level of disease severity: (1) no pneumonia or hypoxia, (2) pneumonia without hypoxia, (3) hypoxia without respiratory failure, and (4) respiratory failure. High attenuation area (HAA) was defined as the quantified percentage of imaged lung volume with attenuation values between -600 and -250 Hounsfield units (HU). Decision tree models were built with clinical variables and initial laboratory values (model 1) and including quantitative CT parameters in addition to them (model 2). Results: A total of 387 patients were analyzed. The mean age was 57.8 years, and 50.3% were women. HAA increased as the severity of respiratory outcome increased. HAA showed a moderate correlation with lactate dehydrogenases (LDH) and C-reactive protein (CRP). In the decision tree of model 1, the CRP, fibrinogen, LDH, and gene Ct value were chosen as classifiers whereas LDH, HAA, fibrinogen, vaccination status, and neutrophil (%) were chosen in model 2. For predicting respiratory failure, the decision tree built with quantitative CT parameters showed a greater accuracy than the model without CT parameters. Conclusions: The decision tree could provide higher accuracy for predicting respiratory failure when quantitative CT parameters were considered in addition to clinical characteristics, PCR Ct value, and blood biomarkers.

Impact of prior vaccination on clinical outcomes of patients with COVID-19.

Fully vaccinated people remain at risk of Coronavirus Disease 2019 (COVID-19). We examined association between prior vaccination and clinical outcomes in patients with COVID-19. Overall, 387 patients with mild-to-severe COVID-19 were enrolled. Patients were considered fully vaccinated at least 14, 7, and 14 days after receiving the second dose of ChAdOx1 nCoV-19 or mRNA-1273, second dose of BNT162b2, or single dose of Ad26.COV2.S, respectively. The primary outcomes (risk of pneumonia, requirement of supplemental oxygen, and progression to respiratory failure) were compared between vaccinated and unvaccinated patients. Logistic regression analysis was performed to identify factors associated with the outcomes. There were 204 and 183 patients in the vaccinated and unvaccinated groups, respectively. The vaccinated group was significantly older and had more comorbidities than the unvaccinated group. Patients in the unvaccinated group were significantly more likely to develop pneumonia (65.6% vs. 36.8%) or require supplemental oxygen (29.0 vs. 15.7%) than the vaccinated group. The vaccinated group had a significantly shorter time from symptom onset to hospital discharge than the unvaccinated group (10 vs. 11 days; p<0.001). The proportion of patients who progressed to respiratory failure did not differ significantly between groups. In multivariable analyses, vaccination was associated with an approximately 70% and 82% lower likelihood of pneumonia and supplemental oxygen requirement, respectively. Being vaccinated was associated with a significantly lower risk of pneumonia and severe disease when breakthrough infection developed. Our findings support continuous efforts to increase vaccine coverage in populations.

Development and Feasibility Test of a Mouth Contactless Breathing Exercise Solution Using Virtual Reality: A Randomized Crossover Trial.

PURPOSE: The purpose of this study was to develop a novel mouth contactless breathing exercise solution based on virtual reality (VR), and to test its feasibility. METHODS: We developed the Virtual Reality-based Breathing Exercise System (VR-BRES), a self-regulating biofeedback breathing exercise with gaming characteristics and a soft stretch sensor. The feasibility and efficacy of the VR-BRES prototype were investigated through a randomized crossover trial. Fifty healthy adults participated in the trial, and their respiratory parameters and user evaluation of the VR-BRES were compared with conventional deep breathing (CDB) exercises. RESULTS: The respiratory parameters, forced vital capacity (Z = 4.82, 4.95, p < .001), forced expiratory volume in one second (t = 6.02, 6.26, p < .001), and peak expiratory flow (t = 5.35, 5.68, p < .001) were significantly higher during breathing exercises using the VR-BRES. User evaluation was also significantly higher for the VR-BRES in terms of efficiency (Z = 3.86, p < .001), entertainingness (Z = 5.00, p < .001), and intention to use (Z = 3.22, p = .001) compared to CDB. However, there was no difference in convenience between the two methods (Z = -0.90, p = .369). CONCLUSION: The VR-BRES has the potential to be an efficient breathing exercise solution. We recommend a clinical study that evaluates the effects of the VR-BRES for a certain period of time for people who need breathing exercises.