Development of Predictive Models Based on Biochemical Parameters to Triage COVID-19 Patients: A Study Conducted in a Tertiary Care Hospital

• Published in: Curēus (Palo Alto, CA) Vol. 16; no. 3; p. e56197
• Main Authors: Sinha, Mainak, Banerjee, Ayan, Kumar, Sushil, Mahto, Mala, Kumari, Bandana, Ranjan, Alok, Bansal, Akash
• Format: Journal Article
• Language: English
• Published: United States Cureus Inc 14.03.2024; Cureus
• Subjects: Business metrics; COVID-19; Creatinine; Dehydrogenases; Emergency Medicine; Infectious Disease; Lymphocytes; Mortality; Neutrophils; Pandemics; Patients; Probability; Proteins; Regression analysis; Sodium; Variables; United States > US; procalcitonin; python; covid 19; predictive models; machine learning; interleukin (il)-6

Background The COVID-19 disease continues to cause severe mortality and morbidity. Biochemical parameters are being used to predict the severity of the infection. This study aims to predict disease severity and mortality to help reduce mortality through timely intervention in a cost-effective way. M...