天津医药 ›› 2023, Vol. 51 ›› Issue (10): 1122-1125.doi: 10.11958/20221631

• 临床研究 • 上一篇    下一篇

小儿免疫性血小板减少症疾病转归的影响因素及风险预测模型构建

周妮娜(), 顾健辉, 杨治平, 盛俞, 姜荣()   

  1. 南通大学附属医院儿内科(邮编226001)
  • 收稿日期:2022-10-12 修回日期:2023-01-19 出版日期:2023-10-15 发布日期:2023-10-18
  • 通讯作者: E-mail:luckyboyjiangrong@qq.com
  • 作者简介:周妮娜(1985),女,主治医师,主要从事儿童血液系统疾病诊断与治疗方面研究。E-mail:715233087@qq.com

Influencing factors and construction of risk prediction model of immune thrombocytopenia in children

ZHOU Nina(), GU Jianhui, YANG Zhiping, SHENG Yu, JIANG Rong()   

  1. Department of Pediatric, Affiliated Hospital of Nantong University, Nantong 226001, China
  • Received:2022-10-12 Revised:2023-01-19 Published:2023-10-15 Online:2023-10-18
  • Contact: E-mail:luckyboyjiangrong@qq.com

摘要:

目的 研究免疫性血小板减少症(ITP)患儿转归的影响因素,并构建风险预测模型。方法 选取166例ITP患儿为研究对象,比较不同疾病转归患儿的临床特征、实验室指标等,采用多因素Logistic回归分析ITP患儿疾病转归的影响因素,并构建ITP疾病转归的风险预测模型,Homser-Lemeshow检验模型拟合优度,绘制受试者工作特征(ROC)曲线分析该模型预测效能。结果 118例患儿转归良好,48例转归不良;与转归良好组比较,转归不良组年龄≥1岁比例、初诊ANA阳性比例、BUN水平升高,初诊血小板计数(PLT)≥20×109/L比例、初诊外周血淋巴细胞绝对数(ALC)、初诊骨髓产板巨核细胞百分比降低(P<0.05);多因素Logistic回归分析示,年龄≥1岁(95% CI:1.358~83.563)、较高的尿素氮(BUN)水平(95% CI:4.013~32.615)是ITP患儿疾病转归的危险因素,初诊PLT≥20×109/L(95% CI:0.036~0.519)、较高的初诊ALC(95% CI:0.197~0.571)是ITP患儿疾病转归的保护因素;预测模型Homser-Lemeshow检验χ2=8.486,P>0.05,预测模型预测ITP患儿疾病转归的AUC为0.963(95% CI:0.934~0.991,P<0.001),敏感度、特异度分别为95.83%、88.98%。结论 年龄≥1岁、较高的BUN水平是ITP患儿疾病转归的危险因素,初诊PLT≥20×109/L、较高的初诊ALC水平是保护因素,且根据影响因素构建的风险预测模型对ITP患儿疾病转归有良好的预测价值。

关键词: 血小板减少, 新生儿同种免疫性, 预后, 危险因素, 风险预测模型

Abstract:

Objective To study factors influencing the outcome of immune thrombocytopenia (ITP) in children, and construct a risk prediction model. Methods A total of 166 children with ITP were included in this study. Clinical characteristics and laboratory indicators of children with different outcomes were comparatively analyzed. Multivariate Logistic regression analysis was performed to screen factors influencing the outcome of children with ITP, and a risk prediction model was constructed based on analysis results. Hosmer-Lemeshow tested the goodness of fit of the model. The receiver operating characteristic (ROC) curve was plotted to analyze the predictive performance of the model. Results There were 118 children with good outcomes and 48 children with poor outcomes. Compared with the good outcome group, the proportions of age ≥1, ANA positive at first diagnosis and blood urea nitrogen (BUN) level were higher in the poor outcome group, while the proportion of platelet count (PLT) ≥20×109/L at first diagnosis, absolute lymphocyte count (ALC) at first diagnosis and the percentage of megakaryocytes in bone marrow at first diagnosis were lower in the poor outcome group (P<0.05). Multivariate Logistic regression analysis showed that age ≥1 (95% CI: 1.358-83.563) and higher BUN level (95% CI: 4.013-32.615) were risk factors for disease outcome in children with ITP. PLT ≥20×109/L at initial diagnosis (95% CI: 0.036-0.519) and higher ALC at initial diagnosis (95% CI: 0.197-0.571) were protective factors for disease outcome in children with ITP. Homser-lemeshow test showed χ2=8.486, P=0.387. The AUC of this model in predicting the outcome of children with ITP was 0.963 (95% CI: 0.934-0.991, P<0.001), and the sensitivity and specificity were 95.83% and 88.98%. Conclusion Age ≥1 and higher BUN level are risk factors for disease outcome in children with ITP. PLT ≥20×109/L at initial diagnosis and higher ALC level at initial diagnosis are protective factors. The risk prediction model constructed according to these influencing factors has good predictive valuse for disease outcome of children with ITP.

Key words: thrombocytopenia, neonatal alloimmune, prognosis, risk factors, risk prediction model

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