Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score
Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score
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DOI：
10.1093/cid/ciaa414
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发表时间：
2020-09-15
影响因子：
11.8
通讯作者：
Qin, Enqiang
中科院分区：
文献类型：
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作者：
Ji, Dong;Zhang, Dawei;Qin, Enqiang
本研究旨在通过多因素分析明确2019冠状病毒病（COVID-19）的高危因素，建立疾病进展的预测模型，以帮助临床医生更好地选择治疗策略。方法回顾性收集2020年1月20日至2月22日阜阳市第二人民医院或中国人民解放军总医院第五医疗中心连续收治的所有COVID-19患者的临床资料。使用多变量Cox回归来确定与进展相关的危险因素，然后将其纳入nomogram以建立新的预测评分模型。ROC用于评估模型的性能。结果208例患者根据住院期间病情是否恶化分为稳定组（n = 168, 80.8%）和进展组（n = 40,19.2%）。单因素和多因素分析显示，合并症、年龄较大、淋巴细胞计数较低和出现时乳酸脱氢酶较高是COVID-19进展的独立高危因素。结合这4个因素，nomogram获得了较好的一致性指标。86(95%可信区间[CI]， .81-.91)，校准曲线拟合良好。建立了一种新的评分模型，命名为CALL；其在中华民国下的面积为。91 （95% ci, 0.86 - 0.94）。采用6点的截断值，阳性预测值为50.7%(38.9-62.4%)，阴性预测值为98.5%（94.7-99.8%）。结论使用CALL评分模型，临床医生可以提高COVID-19的治疗效果，降低病死率，更准确、高效地利用医疗资源。这项多中心回顾性研究显示，潜在的合并症、年龄较大、乳酸脱氢酶升高和淋巴细胞计数降低是与COVID-19进展相关的独立高危因素；一种新的评分模型（CALL评分）可以以最佳的敏感性和特异性预测病情进展。
Background We aimed to clarify high-risk factors for coronavirus disease 2019 (COVID-19) with multivariate analysis and establish a predictive model of disease progression to help clinicians better choose a therapeutic strategy.Methods All consecutive patients with COVID-19 admitted to Fuyang Second People's Hospital or the Fifth Medical Center of Chinese PLA General Hospital between 20 January and 22 February 2020 were enrolled and their clinical data were retrospectively collected. Multivariate Cox regression was used to identify risk factors associated with progression, which were then were incorporated into a nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the model.Results Overall, 208 patients were divided into a stable group (n = 168, 80.8%) and a progressive group (n = 40,19.2%) based on whether their conditions worsened during hospitalization. Univariate and multivariate analyses showed that comorbidity, older age, lower lymphocyte count, and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of .86 (95% confidence interval [CI], .81-.91) and well-fitted calibration curves. A novel scoring model, named as CALL, was established; its area under the ROC was .91 (95% CI, .86-.94). Using a cutoff of 6 points, the positive and negative predictive values were 50.7% (38.9-62.4%) and 98.5% (94.7-99.8%), respectively.Conclusions Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources.This multicenter retrospective study showed underlying comorbidity, older age, higher lactate dehydrogenase, and lower lymphocyte count were independent high-risk factors associated with COVID-19 progression; a novel scoring model (CALL score) can predict progression with optimal sensitivity and specificity.