Predictive factors of COVID-19 pneumonia: a retrospective cross-sectional survey in a Japanese university hospital

Abstract BackgroundThe predictive factors of coronavirus disease 2019 (COVID-19) pneumonia, including clinical parameters with symptoms, vital signs, and laboratory data, have not been compared directly between cases with and without complicated pneumonia. AimsWe aimed to identify predictive factors for COVID-19 patients with complicated pneumonia, and determine which COVID-19 patients should undergo computed tomography (CT). MethodsThis retrospective cross-sectional survey was conducted at the Juntendo University Nerima Hospital in Tokyo, Japan. We recruited patients diagnosed with COVID-19 between 1 January and 31 December 2020 and all patients underwent blood tests and CT. Clinical information, including vital signs, symptoms, laboratory results, and CT findings, were extracted from medical charts. Factors potentially predicting COVID-19 pneumonia were analysed using Student’s t -test or the chi-squared test, and variables with a p- value of < 0.05 in the bi-variate analysis were entered into multivariate logistic regression models. ResultsAmong 221 included patients (119 males [53.8%]; mean age, 54.59 ± 18.61 years), 160 (72.4%) had pneumonia. The significant factors in the multi-variate analysis were the lactate dehydrogenase (odds ratio [OR], 3.41; 95% confidence interval [CI], 1.47–7.95; p 220 IU/L and > 3.0 mg/dL, respectively, are independent risk factors for COVID-19 pneumonia. The present results are extremely useful for deciding whether to perform CT among COVID-19 patients.