Since December 2019, coronavirus disease 2019 (COVID-19) pandemic has spread from China all over the world and many COVID-19 outbreaks have been reported in long-term care facilities (LCTF). However, data on clinical characteristics and prognostic factors in such settings are scarce. We conducted a retrospective, observational cohort study to assess clinical characteristics and baseline predictors of mortality of COVID-19 patients hospitalized after an outbreak of SARS-CoV-2 infection in a LTCF. A total of 50 patients were included. Mean age was 80 years (SD, 12 years), and 24/50 (57.1%) patients were males. The overall in-hospital mortality rate was 32%. At Cox regression analysis, significant predictors of in-hospital mortality were: hypernatremia (HR 9.12), lymphocyte count < 1000 cells/µL (HR 7.45), cardiovascular diseases other than hypertension (HR 6.41), and higher levels of serum interleukin-6 (IL-6, pg/mL) (HR 1.005). Our study shows a high in-hospital mortality rate in a cohort of elderly patients with COVID-19 and hypernatremia, lymphopenia, CVD other than hypertension, and higher IL-6 serum levels were identified as independent predictors of in-hospital mortality. Given the small population size as major limitation of our study, further investigations are necessary to better understand and confirm our findings in elderly patients.
【저자키워드】 Infectious diseases, Epidemiology, 【초록키워드】 COVID-19, coronavirus disease, pandemic, Hospitalized, Mortality, Clinical characteristics, hypernatremia, IL-6, SARS-COV-2 infection, interleukin-6, cardiovascular disease, elderly patients, hypertension, lymphopenia, Spread, China, Lymphocyte count, serum, Cohort, COVID-19 outbreak, outbreak, Patient, age, predictor, Care, in-hospital mortality, retrospective, COVID-19 patient, Elderly patient, Prognostic factor, Observational cohort study, CVD, Serum level, in-hospital mortality rate, Cox regression analysis, males, reported, conducted, baseline, independent predictor, with COVID-19, 【제목키워드】 Mortality, Characteristics, clinical, predictor, Care, Elderly patient, with COVID-19,