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中华实验和临床感染病杂志(电子版) ›› 2023, Vol. 17 ›› Issue (04) : 274 -281. doi: 10.3877/cma.j.issn.1674-1358.2023.04.009

论著

儿童难治性肺炎支原体肺炎所致塑型性支气管炎风险列线图模型的构建
杨梅(), 周春, 赵艾红, 王琴   
  1. 224700 建湖县,扬州大学建湖临床医学院儿科
    210014 南京市,南京市中西医结合医院儿科
  • 收稿日期:2023-04-04 出版日期:2023-08-15
  • 通信作者: 杨梅
  • 基金资助:
    2019年盐城市医学科技发展计划项目(No. YK2019079)

Construction of a risk nomograph model for plastic bronchitis caused by refractory mycoplasma pneumoniae pneumonia in children

Mei Yang(), Chun Zhou, Aihong Zhao, Qin Wang   

  1. Department of Pediatrics, Jianhu Clinical Medical College, Yangzhou University, Jianhu 224700, China
    Department of Pediatrics, Nanjing Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing 210014, China
  • Received:2023-04-04 Published:2023-08-15
  • Corresponding author: Mei Yang
引用本文:

杨梅, 周春, 赵艾红, 王琴. 儿童难治性肺炎支原体肺炎所致塑型性支气管炎风险列线图模型的构建[J]. 中华实验和临床感染病杂志(电子版), 2023, 17(04): 274-281.

Mei Yang, Chun Zhou, Aihong Zhao, Qin Wang. Construction of a risk nomograph model for plastic bronchitis caused by refractory mycoplasma pneumoniae pneumonia in children[J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2023, 17(04): 274-281.

目的

分析儿童难治性肺炎支原体肺炎(RMPP)所致塑型性支气管炎(PB)的发生率和主要危险因素,并构建定量风险列线图模型以指导临床早期进行高危分层。

方法

回顾性分析2020年2月至2023年2月扬州大学建湖临床医学院收治的350例诊断为RMPP患儿的临床资料,按照4︰1随机分为建模集(280例)与验证集(70例),根据纤维支气管镜和组织病理学表现将建模集分为PB组(120例)和无PB组(160例)。比较不同组别患者临床表现、血生化和胸部CT征象,最小绝对收缩和选择算子(LASSO)回归筛选最具差异的指标,多因素Logistic回归分析筛选主要危险因素,绘制列线图预测模型。采用受试者工作曲线(ROC)计算模型预测塑型性支气管炎曲线下面积(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

建模集诊断120例PB(42.9%、120/280),验证集诊断25例PB(35.7%、25/70),两组PB阳性率以及其他一般临床资料均具有可比性(P > 0.05)。单因素分析发现,建模集中PB组峰值体温(t = 3.659、P = 0.001)、发热持续时间(t = 5.021、P < 0.001)、低氧血症(χ2 = 4.060、P = 0.044)、糖皮质激素(χ2 = 7.154、P = 0.007)、静脉注射丙种球蛋白(χ2 = 16.169、P < 0.001)、肺不张(χ2 = 13.810、P < 0.001)和胸腔积液(χ2 = 11.118、P < 0.001)、中性粒细胞百分比(N%)(Z = 1.659、P< 0.001)、C-反应蛋白(CRP)(Z = 15.659、P < 0.001)、降钙素原(PCT)(Z = 9.654、P < 0.001)和白细胞介素6(IL-6)(Z = 23.324、P < 0.001)、丙氨酸氨基转移酶(ALT)(Z = 3.425、P < 0.001)、乳酸脱氢酶(LDH)(Z = 123.325、P < 0.001)和D-二聚体(Z = 5.246、P < 0.001)均显著高于无PB组,而血小板计数(PLT)显著降低(Z = 1.995、P < 0.001)。LASSO回归共筛选出6个非共线性指标,即峰值体温、肺不张、胸腔积液、N%、IL-6和LDH。Logistic回归分析显示,峰值体温(OR = 2.756、95%CI:2.003~3.567、P < 0.001)、肺不张(OR = 3.526、95%CI:2.869~4.123、P < 0.001)、胸腔积液(OR = 2.032、95%CI:1.456~2.758、P < 0.001)、N%(OR = 1.856、95%CI:1.235~2.632、P < 0.001)、IL-6(OR = 1.525、95%CI:1.124~2.201、P < 0.001)和LDH(OR = 1.302、95%CI:1.052~1.968、P < 0.001)均为RMPP所致PB的危险因素。R软件建立列线图模型,总分500分。受试者工作曲线(ROC)显示,模型预测建模集与验证集PB的曲线下面积(AUC)分别为0.902(95%CI:0.856~0.945、P < 0.001)和0.866(95%CI:0.823~0.914、P < 0.001)。校准曲线和决策曲线均显示模型有较好的吻合度和临床净获益比。

结论

RMPP患儿有较高的PB发生率,峰值体温、肺不张、胸腔积液、N%、IL-6和LDH均为其主要危险因素;本研究所建立的列线图模型对指导临床评估高危PB有较好的应用潜力。

Objective

To investigate the incidence and main risk factors of plastic bronchitis (PB) caused by refractory Mycoplasma pneumoniae pneumonia (RMPP) in children, and to construct a quantitative risk nomograph model for guiding early clinical high-risk stratification.

Methods

The clinical data of 350 children diagnosed as RMPP admitted to Jianhu Clinical Medical College, Yangzhou University from February 2020 to February 2023 were analyzed, retrospectively, and were divided into modeling set (280 cases) and validation set (70 cases) by 4︰1, randomly. The model set was divided into PB group (120 cases) and no PB group (160 cases) according to bronchofiberscopy and histopathological findings. The clinical manifestations, blood biochemistry and chest CT signs of patients in different groups were compared, the most different indicators were screened by LASSO regression, the main risk factors were screened by multivariate Logistic regression, and the prediction model was drawn by histogram. The area under the curve (AUC) of plastic bronchitis was predicted by receiver operating curve (ROC) calculation model. The goodness of fit of the model was evaluated by Hosmer-Lemeshow test. The consistency and benefit of the model were evaluated by calibration curve and decision curve.

Results

The modeling set diagnosed 120 cases of PB (42.9%, 120/280) and the verification set diagnosed 25 cases of PB (35.7%, 25/70). The positive rates of PB and other general clinical data were comparable between the two groups (all P > 0.05). Single-factor comparison showed that peak body temperature (t = 3.659, P = 0.001), fever duration (t = 5.021, P < 0.001), hypoxemia (χ2 = 4.060, P = 0.044), glucocorticoid (χ2 = 7.154, P = 0.007), intravenous gamma globulin (χ2 = 16.169, P < 0.001), atelectasis (χ2 = 13.810, P < 0.001), pleural effusion (χ2 = 11.118, P < 0.001), neutrophil percentage (N%) (Z =1.659, P < 0.001), C-reactive protein (CRP) (Z =15.659, P < 0.001), procalcitonin (PCT) (Z = 9.654, P < 0.001), interleukin 6 (IL-6) (Z = 23.324, P < 0.001), alanine aminotransferase (ALT) (Z = 3.425, P < 0.001), lactate dehydrogenase (LDH) (Z = 123.325, P < 0.001) and D-dimer (Z = 5.246, P < 0.001) were significantly higher than those without PB, while platelet count (PLT) was significantly decreased (Z = 1.995, P < 0.001). Total of 6 non-collinear indexes were selected by LASSO regression, namely peak body temperature, atelectasis, pleural effusion, N%, IL-6 and LDH. Multivariate Logistic regression showed that peak body temperature (OR = 2.756, 95%CI: 2.03-3.567, P < 0.001), atelectasis (OR = 3.526, 95%CI: 2.869-4.123, P < 0.001), pleural effusion (OR = 2.032, 95%CI: 1.456-2.758, P < 0.001), N% (OR = 1.856, 95%CI: 1.235-2.632, P < 0.001), IL-6 (OR = 1.525, 95%CI: 1.124-2.201, P < 0.001), and LDH (OR = 1.302, 95%CI: 1.052-1.968, P < 0.001) were all the risk factors to PB caused by RMPP. The nomogram model was established by R software, with a total score of 500 points. The AUC of the model for predicting PB in model set and validation set were 0.902 (95%CI: 0.856-0.945, P < 0.001) and 0.866 (95%CI: 0.823-0.914, P < 0.001), respectively. Both the calibration curve and the decision curve showed that the model had good degree of coincidence and clinical net benefit ratio.

Conclusions

Children with RMPP have a high incidence of PB, peak body temperature, atelectasis, pleural effusion, N%, IL-6 and LDH are all main risk factors; a nomograph model was developed that has good potential for guiding clinical evaluation of high-risk PB and is worth promoting.

表1 建模集与验证集患者临床资料
表2 建模集PB组与无PB组患者临床资料
指标 无PB组(160例) PB组(120例) 统计量 P
男/女(例) 88/72 58/62 χ2 = 1.221a 0.269
年龄( ± s,岁) 6.6 ± 2.1 6.9 ± 1.8 t = 1.032 0.238
峰值体温( ± s,℃) 38.9 ± 1.2 40.9 ± 1.1 t = 3.659 0.001
发热持续时间( ± s,d) 8.9 ± 2.2 9.8 ± 2.6 t = 5.021 < 0.001
低氧血症[例(%)] 16(10.0) 22(18.3) χ2 = 4.060a 0.044
糖皮质激素[例(%)] 116(72.5) 103(85.8) χ2 = 7.154a 0.007
IVIG [例(%)] 4(2.5) 19(15.8) χ2 = 16.169a < 0.001
肺不张[例(%)] 36(22.5) 52(43.3) χ2 = 13.810a < 0.001
胸腔积液[例(%)] 38(23.8) 51(42.5) χ2 = 11.118a 0.001
WBC [M(P25,P75),× 109/L)] 7.5(5.8,11.2) 7.8(6.2,13.4) Z = 0.526 0.349
N% [M(P25,P75),%] 73.4(68.9,77.5) 78.5(70.2,83.6) Z = 1.659 < 0.001
PLT [M(P25,P75),× 109/L)] 279.8(232.3,332.6) 245.6(203.5,315.6) Z = 1.995 < 0.001
CRP [M(P25,P75),mg/L] 19.9(11.2,32.2) 28.9(17.9,42.3) Z = 15.659 < 0.001
PCT [M(P25,P75),ng/ml] 0.24(0.09,0.51) 0.45(0.29,0.66) Z = 9.654 < 0.001
IL-6 [M(P25,P75),pg/ml] 30.2(19.8,55.6) 52.6(34.6,75.9) Z = 23.324 < 0.001
ALT [M(P25,P75),U/L] 13.5(9.8,21.1) 18.9(11.2,25.6) Z = 3.425 < 0.001
LDH [M(P25,P75),U/L] 356.9(246.5,552.3) 513.2(423.6,623.2) Z = 123.325 < 0.001
APTT [M(P25,P75),s] 27.6(17.8,32.9) 29.5(20.2,35.6) Z = 0.859 0.302
纤维蛋白原[M(P25,P75),g/L] 3.6(3.1,4.4) 3.8(3.3,4.6) Z = 0.785 0.269
D-二聚体[M(P25,P75),mg/L] 0.13(0.08,0.42) 0.34(0.16,0.55) Z = 5.246 < 0.001
IgE [M(P25,P75),IU/L] 114.5(100.5,149.8) 123.5(102.1,156.9) Z = 1.096 0.124
图1 PB危险因素的LASSO回归分析注:A:26个变量的LASSO系数分布,随着惩罚的增加,越来越多的变量系数被压缩,最后大多数可变系数被压缩为零。B:使用十倍交叉验证和最小化标准选择最佳惩罚系数λ,通过验证LASSO模型中的最优参数λ,绘制了二项式偏差曲线与对数(λ)的关系,并根据1个标准误差标准绘制了垂直虚线。通过最优lambda选择6个具有非零系数的变量
表3 PB危险因素的Logistic回归分析
图2 预测PB的列线图模型
图3 列线图预测PB的ROC曲线
图4 列线图预测PB的校准曲线
图5 列线图预测PB的决策曲线
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