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中华实验和临床感染病杂志(电子版)

中华实验和临床感染病杂志(电子版) ›› 2022, Vol. 16 ›› Issue (05) : 337 -343. doi: 10.3877/cma.j.issn.1674-1358.2022.05.008

论著

儿童腺病毒肺炎严重程度预测列线图的构建及验证
孙小艳1,†(), 赵淑玲1, 王晓莹1   
  1. 1. 221000　徐州市，徐州医科大学附属徐州儿童医院呼吸内科
  • 收稿日期:2022-04-27 出版日期:2022-10-15
  • 通信作者: 孙小艳

Construction and validation of a nomogram for predicting the severity of adenovirus pneumonia in children

Xiaoyan Sun1,†(), Shuling Zhao1, Xiaoying Wang1   

  1. 1. Department of Respiratory Medicine, Xuzhou Children’s Hospital Affiliated to Xuzhou Medical University, Xuzhou 221000, China
  • Received:2022-04-27 Published:2022-10-15
  • Corresponding author: Xiaoyan Sun
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引用本文：

孙小艳, 赵淑玲, 王晓莹. 儿童腺病毒肺炎严重程度预测列线图的构建及验证[J]. 中华实验和临床感染病杂志(电子版), 2022, 16(05): 337-343.

Xiaoyan Sun, Shuling Zhao, Xiaoying Wang. Construction and validation of a nomogram for predicting the severity of adenovirus pneumonia in children[J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2022, 16(05): 337-343.

目的

开发一款用于指导临床准确评估儿童腺病毒肺炎严重程度的列线图模型，并进行验证。

方法

采用回顾性、横断面临床观察法，纳入2019年8月至2021年8月于徐州医科大学附属徐州儿童医院诊断为腺病毒肺炎患儿共128例为研究对象，均符合儿童腺病毒性肺炎诊断和治疗指南（2019版）的标准；住院期间参照社区获得性肺炎诊断标准分为重症组（50例）和非重症组（78例），比较两组患儿的性别、年龄、体重、是否早产、发热持续时间、体温峰值、有无基础疾病、血清白细胞计数、中性粒细胞和淋巴细胞百分比、C-反应蛋白（CRP）、乳酸、白细胞介素（IL）-6、乳酸脱氢酶（LDH）、降钙素原（PCT）、CD4+ T和CD8+ T淋巴细胞百分比、CD4+/CD8+ T、CD16+CD56+和CD19+ T淋巴细胞百分比、有无混合感染。采用LASSO回归法对危险因素进行降维处理，采用多因素Logistic回归分析筛选独立危险因素，根据回归系数（β）绘制列线图预测模型。采用受试者工作曲线（ROC）计算模型预测重症腺病毒肺炎（SAP）曲线下面积（AUC），Hosmer-Lemeshow检验评估模型的拟合优度，Calibration曲线和Decision曲线评估模型的一致性和获益性。

结果

与非重症组比较，重症组患儿发热持续时间延长[5.2（3.0，8.5）d vs. 2.9（1.0，5.0）d：Z = 8.326、P < 0.001]、IL-6 [45.6（35.4，56.9） pg/ml vs. 30.2（25.2，38.6） pg/ml：Z = 15.326，P < 0.001]和LDH水平[452.6 （385.6，523.4）U/L vs. 365.9（302.1，445.2）U/L：Z = 9.625、P < 0.001]升高、CD4+ T [31.2（27.8，34.2）% vs. 35.5（33.2，38.9）%：Z = 7.526，P < 0.001]和CD4+/CD8+ T水平[1.2（1.0，1.4）vs. 1.4（1.1，1.6）：Z = 5.230、P = 0.004]下降、混合感染率增多[46.0%（23/50）vs. 19.2%（15/78）：χ2 = 10.460、P = 0.001]。LASSO回归共筛选出4个具有非零系数特征的变量，即发热持续时间、IL-6浓度、CD4+ T淋巴细胞百分比和混合感染。多因素Logistic回归分析显示，发热持续时间（OR = 3.125、95%CI：2.565~3.896、P < 0.001）、IL-6浓度（OR = 2.012，95%CI：1.428~2.639、P < 0.001）、CD4+ T淋巴细胞百分比（OR = 0.369、95%CI：0.124~0.678、P = 0.009）和混合感染（OR = 1.457、95%CI：1.124~1.895，P = 0.001）均为SAP的独立危险因素。建立列线图模型总分160分，ROC显示列线图预测SAP的AUC值为0.852（95%CI：0.779~0.901，P < 0.001）。Hosmer-Lemeshow检验值为0.786，提示模型拟合优度较高。Calibration曲线和Decision曲线显示模型一致性和获益性尚可。

结论

影响儿童腺病毒肺炎严重程度的主要因素有发热持续时间、IL-6浓度、CD4+ T淋巴细胞百分比和混合感染，以此开发的列线图预测模型来评估SAP，操作简单、可视化效果强，有较高的效能和拟合优度，一致性和获益性尚好，具有较好的临床应用价值。

关键词: 腺病毒肺炎, 列线图, 白细胞介素-6, 危险因素
Objective

To develop a nomogram model for guiding clinical accurate evaluation on the severity of adenovirus pneumonia in children, and carry out the internal validation.

Methods

Total of 128 children with adenoviral pneumonia diagnosis in Xuzhou Children’s Hospital Affiliated to Xuzhou Medical University from August 2019 to August 2021 were included, retrospectively, who all met the criteria of the guideline for the diagnosis and treatment of adenoviral pneumonia in children (2019 Edition). During hospitalization, according to the diagnostic criteria of community-acquired pneumonia, 128 cases were divided into severe group (50 cases) and non-severe group (78 cases). The gender, age, weight, premature delivery, duration of fever, peak body temperature, basic diseases, serum leukocyte count, percentage of neutrophils and lymphocytes, C-reactive protein (CRP), lactic acid, interleukin (IL)-6, lactate dehydrogenase (LDH), procalcitonin (PCT), percentage of CD4+ T and CD8+ T lymphocytes, CD4+/CD8+, CD16+CD56+ and CD19+ T lymphocytes, and mixed infection were compared between the two groups. The dimension of risk factors was reduced by LASSO regression, then the independent risk factors were screened by multivariate Logistic regression analysis, nomogram predictive model was drawn according to the regression coefficient (β). The area under the curve (AUC) of model for severe adenovirus pneumonia (SAP) prediction was calculated by receiver operating curve (ROC), and the goodness of fit of the model was evaluated by Hosmer-Lemeshow test, consistency and benefit of the model were evaluated by calibration curve and decision curve.

Results

Compared with non-severe group, Univariate comparison showed that the duration of fever was longer [5.2 (3.0, 8.5) d vs. 2.9 (1.0, 5.0) d; Z = 8.326, P < 0.001], concentrations of IL-6 [45.6 (35.4, 56.9) pg/ml vs. 30.2 (25.2, 38.6) pg/ml; Z = 15.326, P < 0.001] and LDH were higher [452.6 (385.6, 523.4) U/L vs. 365.9 (302.1, 445.2) U/L; Z = 9.625, P < 0.001], levels of CD4+ T [31.2 (27.8, 34.2)% vs. 35.5 (33.2, 38.9)%; Z = 7.526, P < 0.001] and CD4+/CD8+ were lower [1.2 (1.0, 1.4) vs. 1.4 (1.1, 1.6); Z = 5.230, P = 0.004], and the rate of mixed infection was higher in severe group [46.0% (23/50) vs. 19.2% (15/78); χ2 = 10.460, P = 0.001]. LASSO regression screened four variables with non-zero coefficients, namely duration of fever, IL-6 concentration, CD4+ T lymphocyte percentage and mixed infection. Multivariate Logistic regression analysis showed that duration of fever (OR = 3.125, 95%CI: 2.565-3.896, P < 0.001), IL-6 concentration (OR = 2.012, 95%CI: 1.428-2.639, P < 0.001), CD4+ T lymphocyte percentage (OR = 0.369, 95%CI: 0.124-0.678, P = 0.009) and mixed infection (OR = 1.457, 95%CI: 1.124-1.895, P = 0.001) were the independent risk factors for SAP. The total score of nomogram model was 160. ROC showed that the AUC value of nomogram for predicting SAP was 0.852 (95%CI: 0.779-0.901, P < 0.001). The Hosmer-Lemeshow test value was 0.786, suggesting that the goodness of fit of the model was high. The calibration curve and decision curve showed that the consistency and benefit of the model were acceptable.

Conclusions

The main factors affecting the severity of adenovirus pneumonia in children are the duration of fever, the concentration of IL-6, the percentage of CD4+ T lymphocytes and mixed infection. The developed nomogram prediction model to evaluate SAP has simple operation and strong visualization effect. It has high efficacy and goodness of fit, good consistency and benefit, and has good clinical application value.

Key words: Adenovirus pneumonia, Nomograph, Interleukin-6, Risk factor
表1 两组患儿的临床资料
临床资料 非重症组（78例） 重症组（50例） 统计量 P值
男/女 41/37 28/22 χ2 = 0.145 0.704a
年龄[M（P25，P75），岁] 3.8（1.5，8.0） 3.5（1.0，7.0） Z = 0.563 0.501
体重[M（P25，P75），kg] 6.9（4.0，20.5） 6.6（3.5，18.5） Z = 0.869 0.223
早产[例（%）] 4（5.1） 3（6.0） χ2 = 0.045 0.832b
发热持续时间[M（P25，P75），d] 2.9（1.0，5.0） 5.2（3.0，8.5） Z = 8.326 < 0.001
体温峰值[M（P25，P75），℃] 39.7（39.0，40.0） 39.9（39.2，41.5） Z = 0.965 0.102
营养不良[例（%）] 7（9.0） 5（10.0） χ2 = 0.038 0.745b
肝炎[例（%）] 4（5.1） 3（6.0） χ2 = 0.045 0.869b
肾病[例（%）] 3（3.8） 2（4.0） χ2 = 0.002 0.965b
白细胞计数[M（P25，P75），× 109/L）] 9.6（7.5，12.5） 10.2（7.9，14.0） Z = 0.785 0.253
中性粒细胞[M（P25，P75），%] 70.5（66.9，74.5） 72.3（68.5，75.5） Z = 0.635 0.421
淋巴细胞[M（P25，P75），%] 32.3（30.1，35.4） 35.6（30.8，36.6） Z = 0.741 0.326
CRP [M（P25，P75），mg/L] 13.0（8.5，16.5） 13.5（9.0，18.2） Z = 0.596 0.522
乳酸[M（P25，P75），mmol/L] 2.5（2.2，2.8） 2.6（2.3，2.9） Z = 0.326 0.648
IL-6 [M（P25，P75），pg/ml] 30.2（25.2，38.6） 45.6（35.4，56.9） Z = 15.326 < 0.001
LDH [M（P25，P75），U/L] 365.9（302.1，445.2） 452.6（385.6，523.4） Z = 9.625 < 0.001
PCT [M（P25，P75），μg/L] 0.2（0.1，0.3） 0.3（0.1，0.5） Z = 0.669 0.421
CD4+ T [M（P25，P75），%] 35.5（33.2，38.9） 31.2（27.8，34.2） Z = 7.526 < 0.001
CD8+ T [M（P25，P75），%] 26.6（25.0，30.1） 26.8（25.5，30.9） Z = 1.002 0.121
CD4+/CD8+ T [M（P25，P75）] 1.4（1.1，1.6） 1.2（1.0，1.4） Z = 5.230 0.004
CD16+CD56+ T [M（P25，P75），%] 13.0（11.8，14.5） 12.6（11.5，13.9） Z = 0.653 0.302
CD19+ T [M（P25，P75），%] 19.9（18.5，22.5） 21.2（19.0，23.5） Z = 0.845 0.203
混合感染[例（%）] 15（19.2） 23（46.0） χ2 = 10.460 0.001a
图1 SAP危险因素的LASSO回归分析
表2 SAP危险因素Logistic回归分析
危险因素 β值 SE值 Wald χ2值 P值 OR值 95%CI
发热持续时间 1.326 0.895 21.503 < 0.001 3.125 2.565~3.896
IL-6 0.854 0.458 10.102 < 0.001 2.012 1.428~2.639
CD4+ T －0.102 0.052 5.165 0.009 0.369 0.124~0.678
混合感染 0.526 0.301 7.071 0.001 1.457 1.124~1.895
常数项 0.085 0.033 6.659 0.001 — —
图2 SAP的列线图模型
图3 列线图模型预测SAP的ROC曲线
图4 列线图模型预测SAP发生的Calibration曲线
图5 列线图模型预测SAP发生的Decision曲线注：a：假设所有患儿均未采用列线图模型评估SAP发生风险；b：假设所有患儿均采用列线图模型评估SAP发生风险；c：列线图模型的决策曲线
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