Department of Radiology, Cochin Hospital, APHP, France.
Department of Radiology, Ambroise Paré Hospital, APHP, France.
Respir Med. 2020 Dec;175:106206. doi: 10.1016/j.rmed.2020.106206. Epub 2020 Nov 5.
Covid-19 pneumonia CT extent correlates well with outcome including mortality. However, CT is not widely available in many countries. This study aimed to explore the relationship between Covid-19 pneumonia CT extent and blood tests variations. The objective was to determine for the biological variables correlating with disease severity the cut-off values showing the best performance to predict the parenchymal extent of the pneumonia.
Bivariate correlations were calculated between biological variables and grade of disease extent on CT. Receiving Operating Characteristic curve analysis determined the best cutoffs for the strongest correlated biological variables. The performance of these variables to predict mild (<10%) or severe pneumonia (>50% of parenchyma involved) was evaluated.
Correlations between biological variables and disease extent was evaluated in 168 patients included in this study. LDH, lymphocyte count and CRP showed the strongest correlations (with 0.67, -0.41 and 0.52 correlation coefficient, respectively). Patients were split into a training and a validation cohort according to their centers. If one variable was above/below the following cut-offs, LDH>380, CRP>80 or lymphocyte count <0.8G/L, severe pneumonia extent on CT was detected with 100% sensitivity. Values above/below all three thresholds were denoted in 73% of patients with severe pneumonia extent. The combination of LDH<220 and CRP<22 was associated with mild pneumonia extent (<10%) with specificity of 100%.
LDH showed the strongest correlation with the extent of Covid-19 pneumonia on CT. Combined with CRP±lymphocyte count, it helps predicting parenchymal extent of the pneumonia when CT scan is not available.
Covid-19 肺炎的 CT 范围与结局(包括死亡率)密切相关。然而,在许多国家,CT 并不广泛应用。本研究旨在探讨 Covid-19 肺炎 CT 范围与血液检查变化之间的关系。目的是确定与疾病严重程度相关的生物学变量,确定最佳截断值来预测肺炎实质范围。
计算了生物学变量与 CT 上疾病程度分级之间的双变量相关性。接受者操作特征曲线分析确定了与疾病严重程度相关性最强的生物学变量的最佳截断值。评估了这些变量预测轻度(<10%)或重度肺炎(>50%的肺部受累)的性能。
在这项研究中,评估了 168 例患者的生物学变量与疾病范围之间的相关性。LDH、淋巴细胞计数和 CRP 显示出最强的相关性(分别为 0.67、-0.41 和 0.52 相关系数)。根据患者所在中心将患者分为训练和验证队列。如果一个变量高于/低于以下截断值,即 LDH>380、CRP>80 或淋巴细胞计数<0.8G/L,则 CT 检测到严重肺炎范围的敏感性为 100%。有 73%的严重肺炎范围患者的三个阈值均高于/低于。LDH<220 和 CRP<22 的组合与轻度肺炎范围(<10%)相关,特异性为 100%。
LDH 与 CT 上 Covid-19 肺炎的范围相关性最强。结合 CRP±淋巴细胞计数,当 CT 扫描不可用时,有助于预测肺炎实质范围。