检验医学 ›› 2022, Vol. 37 ›› Issue (10): 921-927.DOI: 10.3969/j.issn.1673-8640.2022.010.003

• 临床应用研究・论著 • 上一篇    下一篇

基于外周血炎症指标的列线图模型早期诊断新生儿败血症的价值

何学联1, 何子翼2, 刘月阳1, 余炎芝1, 张思颖1()   

  1. 1.重庆大学附属涪陵医院儿科,重庆 408000
    2.重庆市妇幼保健院质量管理科,重庆 401120
  • 收稿日期:2021-09-15 修回日期:2021-11-30 出版日期:2022-10-30 发布日期:2022-11-14
  • 通讯作者: 张思颖
  • 作者简介:张思颖,E-mail:zhigu133937@163.com
    何学联,女,1989年生,硕士,主任医师,主要从事临床儿科相关疾病的诊治工作。

Role of line chart model based on peripheral blood-derived inflammation markers in early diagnosis of neonatal septicemia

HE Xuelian1, HE Ziyi2, LIU Yueyang1, YU Yanzhi1, ZHANG Siying1()   

  1. 1. Department of Pediatrics,Fuling Hospital,Chongqing University,Chongqing 408000,China
    2. Department of Quality Management,Chongqing Maternal and Child Health Hospital,Chongqing 401120,China
  • Received:2021-09-15 Revised:2021-11-30 Online:2022-10-30 Published:2022-11-14
  • Contact: ZHANG Siying

摘要:

目的 基于外周血炎症指标构建诊断新生儿败血症的列线图模型,并评估其对新生儿败血症的早期诊断价值。方法 选取137例败血症患儿和114例非感染新生儿,从中随机选取96例败血症患儿(败血症组)和96例非感染新生儿(对照组);将另外41例败血症患儿和18例非感染新生儿纳入模型验证组。收集所有新生儿的临床资料,并检测其血常规[白细胞(WBC)计数、血红蛋白(Hb)、血小板(PLT)计数、淋巴细胞百分比(LYMPH%)、中性粒细胞百分比(NEUT%)、血细胞比容(HCT)]、C反应蛋白(CRP)、降钙素原(PCT)和白细胞介素6(IL-6)。采用Logistic回归分析评估新生儿发生败血症的危险因素,并构建列线图模型。采用受试者工作特征(ROC)曲线、决策曲线和校准曲线对该模型进行评价和验证。采用Kaplan-Meier生存曲线评价不同风险组败血症发生率。结果 败血症组与对照组之间WBC计数、PLT计数、Hb、NEUT%、CRP、PCT和IL-6差异均有统计学意义(P<0.05),LYMPH%和HCT差异均无统计学意义(P>0.05)。Logistic回归分析结果显示,CRP、PCT和IL-6水平升高是影响新生儿发生败血症的危险因素[比值比(OR)值分别为2.943、2.862和2.915,P<0.05]。列线图中各危险因素积分相加后的总分为239.78分,对应的新生儿败血症发生率为71.86%。列线图模型诊断新生儿败血症的C-index值为0.934,ROC曲线的曲线下面积为0.831,敏感性为82.1%,特异性为80.4%;校准曲线中理想曲线与实际曲线较为接近,模型的准确度较好;决策曲线的曲线下面积为0.792,该模型临床净获益率较高。根据列线图模型积分的临界值分为新生儿败血症发生率低风险(≤83.65分)、中风险(>83.65~≤157.89分)和高风险(>157.89分)3个组,败血症发生率分别为29.47%、45.57%和83.33%。结论 基于CRP、PCT和IL-6构建的列线图模型对新生儿败血症的早期诊断价值较高。

关键词: C反应蛋白, 降钙素原, 白细胞介素6, 新生儿败血症, 列线图模型

Abstract:

Objective To establish and evaluate a line chart model for the early diagnosis of neonatal septicemia by using peripheral blood-derived inflammation markers. Methods Totally,137 patients with neonatal septicemia and 114 non-infected newborns were enrolled,96 cases of neonatal septicemia patients were randomly selected as septicemia group,96 cases of non-infected newborns were selected as control group,and the remaining 59 newborns(41 cases of neonatal septicemia patients and 18 cases of non-infected newborns) were included in model verification group. The clinical data of all the newborns were collected,blood routine tests were performed,and the test items included white blood cell(WBC) count,hemoglobin(Hb),platelet(PLT) count,lymphocyte percentage(LYMPH%),neutrophil percentage(NEUT%),hematocrit(HCT),C-reactive protein(CRP),procalcitonin(PCT) and interleukin-6(IL-6). Logistic regression analysis was used to evaluate the risk factors of neonatal septicemia,and a line chart model was constructed. Receiver operating characteristic(ROC) curve,decision curve and calibration curve were used to evaluate and validate the model. Kaplan-Meier survival curve was used to evaluate the probability of neonatal septicemia in different risk groups. Results There was statistical significance in WBC count,PLT count,Hb,NEUT%,CRP,PCT and IL-6 between septicemia group and control group(P<0.05),but there was no statistical significance in LYMPH% and HCT(P>0.05). The results of Logistic regression analysis showed that the elevated levels of CRP,PCT and IL-6 were risk factors for neonatal septicemia [odds ratios(OR) were 2.943,2.862 and 2.915,respectively,P<0.05]. The total score of risk factors in the line chart was 239.78,and the corresponding incidence of neonatal septicemia was 71.86%. The C-index value of the line chart diagnosis model for neonatal septicemia was 0.934,the area under curve was 0.831,the sensitivity was 82.1%,and the specificity was 80.4%. The ideal curve in the calibration curve was close to the actual curve,the accuracy was good,the area under decision curve was 0.792,and the clinical net benefit rate of the model was high. According to the critical value of the line chart diagnosis model score,the occurrence probability of neonatal septicemia was classified into 3 groups,low risk(≤83.65),medium risk(>83.65-≤157.89) and high risk(>157.89) groups. The probability of neonatal septicemia was 29.47%,45.57% and 83.33%,respectively. Conclusions The line chart diagnosis model based on CRP,PCT and IL-6 is of value in early diagnosis of neonatal septicemia.

Key words: C-reactive protein, Procalcitonin, Interleukin-6, Neonatal septicemia, Line chart model