In South Korea, 4.5% patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were readmitted to hospitals after discharge. However, there is insufficient research on risk factors for readmission and management of patients after discharge is poor. In this study, 7590 confirmed coronavirus disease (COVID-19) patients were defined as a target for analysis using nationwide medical claims data. The demographic characteristics, underlying diseases, and the use of medical resources were used to examine the association with readmission through the chi-square test and then logistic regression analysis was performed to analyze factors affecting readmission. Of the 7590 subjects analyzed, 328 patients were readmitted. The readmission rates of men, older age and patients with medical benefits showed a high risk of readmission. The Charlson Comorbidity Index score was also related to COVID-19 readmission. Concerning requiring medical attention, there was a higher risk of readmission for the patients with chest radiographs, computed tomography scans taken and lopinavir/ritonavir at the time of their first admission. Considering the risk factors presented in this study, classifying patients with a high risk of readmission and managing patients before and after discharge based on priority can make patient management and medical resource utilization more efficient. This study also indicates the importance of lifestyle management after discharge.

S ince the fi rst reported outbreak in Wuhan, China, on December 31, 2019, severe acute respiratory syndrome coronavirus 2 has infected >210 million persons and resulted in nearly 4.4 million deaths worldwide as of August 2021 (1). Many countries have responded to the coronavirus disease (COVID-19

Background: Metabolic syndrome (MetS) is reportedly a crucial risk factor for coronavirus disease 2019 . Since the epidemiological studies that examine this association are few and include small samples, we investigated the relationship between MetS and COVID-19 severity and death using a larger sample in the Republic of Korea. Methods: We analyzed 66,321 patients, 4,066 of whom had COVID-19. We used chi-square tests to examine patients' characteristics. We performed logistic regression analysis to analyze differences in COVID-19 infection and clinical outcomes according to the presence of MetS. Results: Although MetS was not significantly associated with COVID-19 risk, acquiring MetS was significantly associated with the risk of severe COVID-19 outcomes (odds ratio [OR], 1.97; 95% confidence interval [CI], 1.34 to 2.91; P=0.001). The mortality risk was significantly higher in COVID-19 patients with MetS (OR, 1.74; 95% CI, 1.17 to 2.59; P=0.006). Patients with abnormal waist circumference were approximately 2.07 times more likely to develop severe COVID-19 (P<0.001), and high-density lipoprotein cholesterol (HDL-C) levels were significantly associated with COVID-19; the mortality risk due to COVID-19 was 1.74 times higher in men with an HDL-C level of <40 mg/dL and in women with an HDL-C level of <50 mg/dL (P=0.012). Conclusion: COVID-19 is likely associated with severity and death in patients with MetS or in patients with MetS risk factors. Therefore, patients with MetS or those with abnormal waist circumference and HDL-C levels need to be treated with caution.

Objective To identify risk factors for intensive care unit (ICU) admission and mechanical ventilator usage among confirmed coronavirus disease (COVID-19) patients and estimate the effects of mitigation efforts on ICU capacity in Korea. Patients and Methods Data on profiles and medical history of all confirmed COVID-19 patients in the past 1 year were extracted from the Korean National Health Insurance System’s claims database to assess risk factors for ICU admission and ventilator use. We used a time-series epidemic model to estimate the ICU census in Daegu from the reported hospital data. Findings Multivariate regression analysis revealed male sex, old age, and residing in Daegu city as significant risk factors for ICU admission. The number of patients requiring ICU admission exceeded the bed capacity across all Daegu hospitals before March 9, 2020, and therefore, critically ill patients were transferred to nearby hospitals outside Daegu. This finding was consistent with our prediction that the ICU census in Daegu would peak on March 16, 2020, at 160 through mitigation efforts, without which it would have reached 300 by late March 2020. Conclusion Older age and male sex were risk factors for ICU admission. In addition, the geographic location of the hospital seems to contribute to the severity of the COVID-19 patients admitted to the ICU and to the ICU capacity.

Background: With the delayed eradication of coronavirus disease 2019 (COVID-19), people with disabilities, a socially vulnerable class of individuals, face aggravated hardships caused by a pause in support services and lack of care due to stricter social distancing policies combined with the challenges of their disabilities. Given this background, we aim to investigate COVID-19 infection rates and mortality among people with disabilities, who face heightened physical and mental health threats amidst the COVID-19 pandemic. Methods: Gender, age, health insurance premiums, the Charlson Comorbidity Index, the severity of the disability, and the type of disability were compared among people with disabilities who had been infected with or died from COVID-19 using the nationally representative National Health Insurance Service (NHIS)-COVID database (DB). Results: We found that the COVID-19 infection rate was higher among those with low income, those with severe disability, and those with "other" disabilities (i.e., speech disabilities, hepatic dysfunction, respiratory dysfunction, facial disfigurement, intestinal fistular/urinary disability, epilepsy, intellectual disability, autistic disorder, and mental disorders). The mortality rate was markedly higher (i.e., 15.90 times higher, odds ratio [OR]: 15.90, 95% confidence interval [CI]: 6.16 - 41.06) among people aged 80 years or older as compared with those aged 60 years or younger. The odds for mortality were 2.49 times higher (OR: 2.49, 95% CI: 1.33 - 4.64) among people with severe disabilities as compared with mild disabilities. Conclusions: Among people with disabilities, we found that COVID-19 infection rates differed according to income level, severity of the disability, and disability type, while the COVID-19 mortality rate differed according to age and severity of the disability.