Analisis Risiko Kematian Pasien Covid-19 Menggunakan Model Extended cox

Abstract

Globally, in 2021 there were 170,051,718 cases of COVID-19 and 3,540,437 patients died. The high mortality rate of patients infected with COVID-19 gives an idea to examine the analysis of the factors that influence the death of Covid-19 patients so that they can provide special treatment for patients who have these factors. The data used in this study were Covid-19 patient data obtained from the Mexican Government, with response variables namely time and status and predictor variables, namely patient laboratory results in the form of a history of illness that had been suffered by Covid-19. patients so that they adopted an extended model to evaluate the data. The data in this study is heterogeneous and the amount is large, so data clustering is carried out into 3 clusters, namely low emergency clusters, medium emergency clusters, and high emergency clusters using K-means clustering. Because the study didn’t find factors that affect the death of Covid-19 patients, two clusters were selected, namely the medium emergency cluster and the high emergency cluster. So that the factors that affect the death of Covid-19 patients in the emergency medium cluster are sorted by the highest hazard ratio, namely pneumonia, old age, chronic kidney disease, diabetes, COPD, immune system, hypertension, cardiovascular, obesity, sex, and asthma. In the high emergency cluster, sorted by the highest hazard ratio is the immune system, chronic kidney disease, cardiovascular disease, COPD, tobacco, hypertension, obesity, sex, and pneumonia.