Predictive model of risk factors of High Flow Nasal Cannula using machine learning in COVID-19.

ABSTRACT: With the rapid increase in the number of COVID-19 patients in Japan, the number of patients receiving oxygen at home has also increased rapidly, and some of these patients have died. An efficient approach to identify high-risk patients with slowly progressing and rapidly worsening COVID-19, and to avoid missing the timing of therapeutic intervention will improve patient prognosis and prevent medical complications. Patients admitted to medical institutions in Japan from November 14, 2020 to April 11, 2021 and registered in the COVID-19 Registry Japan were included. Risk factors for patients with High Flow Nasal Cannula invasive respiratory management or higher were comprehensively explored using machine learning. Age-specific cohorts were created, and severity prediction was performed for t

SUBMITTER: Matsunaga N 

PROVIDER: S-EPMC9352414 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature