基于逻辑回归的COVID-19患者高危影响因素分析

Analysis of High Risk Factors for COVID-19 Patients Based on Logistic Regression

利用墨西哥某医疗单位提供的COVID-19患者信息,建立逻辑回归模型,分析导致患者高危的风险因素和潜在风险因素,并预测患者是否处于高风险状态。通过对1048576名患者数据进行处理、分析,结果显示接受呼吸机治疗、因感染新冠病毒患上肺炎、年龄70岁及以上是导致患者处于高风险状态的主要风险因素。引入变量交叉的分析表明患有糖尿病、高血压、心血管病、慢性阻塞性肺病或免疫抑制且年龄30岁及以下、接受呼吸机治疗且年龄90岁及以上、因感染新冠病毒患上肺炎且在家接受治疗、怀孕且患有哮喘是导致患者处于高风险状态的主要潜在风险因素。

Using the information of COVID-19 patients provided by a medical institution in Mexico,a logistic regression model was established to analyze the risk factors and potential risk factors of the patients at high risk,and predict whether the patients were at high risk.The data of 1048576 patients were analyzed,and the results showed that receiving ventilator treatment,COVID-19 acquired pneumonia,and age over 70 years were the main risk factors for patients at high risk.The crossover analysis with variables introduced showed that patients with diabetes,hypertension,cardiovascular disease,chronic obstructive pulmonary disease or immunosuppression and age below 30 years,receiving mechanical ventilation and age over 90 years,pneumonia caused by COVID-19 and treated at home,pregnancy and asthma were the main potential risk factors leading to patients at high risk.