Objectives We aimed to develop a simple algorithm to help early identification of SARS-CoV-2 infection patients with severe progression tendency. Methods The univariable and multivariable analysis were computed to identify the independent predictors of COVID-19 progression. The prediction model was established in a retrospective training set of 322 COVID-19 patients and was re-evaluated in a prospective validation set of 317 COVID-19 patients. Results The multivariable analysis identified age (OR = 1.061, p = 0.028), lactate dehydrogenase (LDH) (OR = 1.006, p = 0.037), and CD4 count (OR = 0.993, p = 0.006) as the independent predictors of COVID-19 progression. Consequently, the age-LDH-CD4 algorithm was derived as (age × LDH)/CD4 count. In the training set, the area under the ROC curve (AUROC) of age-LDH-CD4 model was significantly higher than that of single CD4 count, LDH, or age (0.92, 0.85, 0.80, and 0.75, respectively). In the prospective validation set, the AUROC of age-LDH-CD4 model was also significantly higher than that of single CD4 count, LDH, or age (0.92, 0.75, 0.81, and 0.82, respectively). The age-LDH-CD4 ≥ 82 has high sensitive (81%) and specific (93%) for the early identification of COVID-19 patients with severe progression tendency. Conclusions The age-LDH-CD4 model is a simple algorithm for early identifying patients with severe progression tendency following SARS-CoV-2 infection, and warrants further validation.

中文翻译：

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简单的算法有助于早期识别具有严重进展倾向的 SARS-CoV-2 感染患者


目的 我们旨在开发一种简单的算法来帮助早期识别具有严重进展倾向的 SARS-CoV-2 感染患者。方法进行单变量和多变量分析，以确定 COVID-19 进展的独立预测因素。该预测模型是在 322 名 COVID-19 患者的回顾性训练集中建立的，并在 317 名 COVID-19 患者的前瞻性验证集中重新评估。结果多变量分析确定年龄（OR = 1.061，p = 0.028）、乳酸脱氢酶（LDH）（OR = 1.006，p = 0.037）和 CD4 计数（OR = 0.993，p = 0.006）作为新冠肺炎的独立预测因素。 19级进展。因此，年龄-LDH-CD4 算法导出为（年龄×LDH）/CD4 计数。在训练集中，age-LDH-CD4模型的ROC曲线下面积（AUROC）显着高于单个CD4计数、LDH或年龄的ROC曲线下面积（AUROC）（分别为0.92、0.85、0.80和0.75）。在前瞻性验证集中，age-LDH-CD4模型的AUROC也显着高于单个CD4计数、LDH或年龄的AUROC（分别为0.92、0.75、0.81和0.82）。年龄-LDH-CD4≥82对于早期识别有严重进展倾向的COVID-19患者具有高敏感性（81%）和特异度（93%）。结论age-LDH-CD4 模型是一种简单的算法，可用于早期识别 SARS-CoV-2 感染后具有严重进展倾向的患者，值得进一步验证。