To evaluate the predictive effect of T-lymphoid subsets on the conversion of common covid-19 to severe. The laboratory data were collected retrospectively from common covid-19 patients in the First People’s Hospital of Zaoyang, Hubei Province, China and the Third People’s Hospital of Kunming, Yunnan Province, China, between January 20, 2020 and March 15, 2020 and divided into training set and validation set. Univariate and multivariate logistic regression was performed to investigate the risk factors for the conversion of common covid-19 to severe in the training set, the prediction model was established and verified externally in the validation set. 60 (14.71%) of 408 patients with common covid-19 became severe in 6–10 days after diagnosis. Univariate and multiple logistic regression analysis revealed that lactate ( P = 0.042, OR = 1097.983, 95% CI 1.303, 924,798.262) and CD8 + T cells ( P = 0.010, OR = 0.903, 95% CI 0.835, 0.975) were independent risk factors for general type patients to turn to severe type. The area under ROC curve of lactate and CD8 + T cells was 0.754 (0.581, 0.928) and 0.842 (0.713, 0.970), respectively. The actual observation value was highly consistent with the prediction model value in curve fitting. The established prediction model was verified in 78 COVID-19 patients in the verification set, the area under the ROC curve was 0.906 (0.861, 0.981), and the calibration curve was consistent. CD8 + T cells, as an independent risk factor, could predict the transition from common covid-19 to severe.
【저자키워드】 SARS-CoV-2, viral infection, 【초록키워드】 T cells, Diagnosis, risk factor, CD8, China, T cell, Patient, predict, Lactate, COVID-19 patient, ROC Curve, Predictive, observation, Logistic regression analysis, 95% CI, laboratory data, multivariate logistic regression, independent risk factor, collected, evaluate, was performed, subset, turn, 【제목키워드】 CD8, T cell, predicted,