A COVID-19 mortality prediction model for Korean patients using nationwide Korean disease control and prevention agency database.

The experience of the early nationwide COVID-19 pandemic in South Korea led to an early shortage of medical resources. For efficient resource allocation, accurate prediction of the prognosis or mortality of confirmed patients is essential. Therefore, the aim of this study was to develop an accurate model for predicting COVID-19 mortality using epidemiolocal and clinical variables and for identifying a high-risk group of confirmed patients. Clinical and epidemiolocal variables of 4049 patients with confirmed COVID-19 between January 20, 2020 and April 30, 2020 collected by the Korean Disease Control and Prevention Agency were used. Among the 4049 total confirmed patients, 223 patients died, while 3826 patients were released from isolation. Patients who had the following risk factors showed significantly higher risk scores: age over 60 years, male sex, difficulty breathing, diabetes, cancer, dementia, change of consciousness, and hospitalization in the intensive care unit. High accuracy was shown for both the development set (n = 2467) and the validation set (n = 1582), with AUCs of 0.96 and 0.97, respectively. The prediction model developed in this study based on clinical features and epidemiological factors could be used for screening high-risk groups of patients and for evidence-based allocation of medical resources.

Mortality Risk within 14 Days after Coronavirus Disease 2019 Diagnosis in Dementia Patients: A Nationwide Analysis.

INTRODUCTION: The study evaluated the increased mortality risk within 14 days of coronavirus disease 2019 (COVID-19) diagnosis in dementia patients. METHODS: This retrospective study was conducted from February to April 2020 using the COVID-19 patients' database from the Korea Disease Control and Prevention Agency. The risk factors for early death within 14 days were determined using generalized logistic regression performed in a stepwise manner. Dementia patients diagnosed with COVID-19 were used for the study. The propensity score-matched cohort was included as controls. The differences in mortality within 14 days after COVID-19 diagnosis between the dementia patients and controls were evaluated. RESULTS: We enrolled 5,349 COVID-19 patients from the database; 224 had dementia as comorbidity. The mortality rate within 14 days after COVID-19 diagnosis in dementia patients and the controls was 23.7% versus 1.7%, respectively, before propensity score matching (PSM) (p < 0.001), and 23.7% versus 9.2% after PSM (p < 0.001). The hazard ratio (HR) for mortality within 14 days in COVID-19 patients with dementia was significant even after PSM (HR 5.104, 95% confidence interval 2.889-5.673, p < 0.001). The survival curve of dementia patients was steeply inclined within 14 days after COVID-19 diagnosis, resulting in 70.7% of all deaths in dementia patients. CONCLUSIONS: COVID-19 patients with dementia had a higher risk of early death within 14 days. Thus, prompt intervention is necessary for dementia patients after COVID-19 diagnosis.

Microstructured Surfaces for Reducing Chances of Fomite Transmission via Virus-Containing Respiratory Droplets.

Evaporation-induced particle aggregation in drying droplets is of significant importance in the prevention of pathogen transfer due to the possibility of indirect fomite transmission of the infectious virus particles. In this study, particle aggregation was directionally controlled using contact line dynamics (pinned or slipping) and geometrical gradients on microstructured surfaces by the systematic investigation of the evaporation process on sessile droplets and sprayed microdroplets laden with virus-simulant nanoparticles. Using this mechanism, we designed robust particle capture surfaces by significantly inhibiting the contact transfer of particles from fomite surfaces. For the proof-of-concept, interconnected hexagonal and inverted pyramidal microwall were fabricated using ultraviolet-based nanoimprint lithography, which is considered to be a promising scalable manufacturing process. We demonstrated the potentials of an engineered microcavity surface to limit the contact transfer of particle aggregates deposited with the evaporation of microdroplets by 93% for hexagonal microwall and by 96% for inverted pyramidal microwall. The particle capture potential of the interconnected microstructures was also investigated using biological particles, including adenoviruses and lung-derived extracellular vesicles. The findings indicate that the proposed microstructured surfaces can reduce the indirect fomite transmission of highly infectious agents, including norovirus, rotavirus, or SARS-CoV-2, via respiratory droplets.