Statistical method to determine the need for hospitalization of COVID-19 patients

Abstract The growth rate of COVID-19 is causing worldwide concern. The development of indirect methods used to determine hospitalizations only for necessary cases is of fundamental importance to prevent overcrowding in the health system. The general objective of this article is to propose a statistical method, based on logistic regression, capable of indicating whether a patient who tests positive for COVID-19 should be directed to home isolation or be admitted to a hospital, based on blood tests and age. The data was collected from 5,645 blood tests of patients in March and April 2020. Based on the use of the independent variables ‘C-reactive protein,’ ‘neutrophils,’ and ‘monocytes,’ as well as the age of the patient affected by COVID-19, it is possible to predict with a reasonable degree of accuracy whether, upon arriving at the hospital and testing positive, the individual should be recommended to isolate at home or be admitted to a healthcare facility.

摘要 新型冠状病毒肺炎（COVID-19）的增长速率引发全球广泛关注。开发仅针对必要病例的住院判定间接方法，对防范医疗系统挤兑具有核心重要性。本文的总体目标是提出一种基于逻辑回归（logistic regression）的统计方法，能够依据血液检测结果与患者年龄，判断新冠病毒检测阳性的患者应接受居家隔离还是入院治疗。本研究数据采集自2020年3月至4月间的5645份患者血液检测样本。通过使用C反应蛋白（C-reactive protein）、中性粒细胞（neutrophils）、单核细胞（monocytes）等自变量，结合新冠感染者的年龄信息，可以以较高的准确率预测：当患者抵达医院且新冠检测结果呈阳性时，是否应建议其居家隔离，或是收入医疗场所接受治疗。