Approach to prediction and receiver operating characteristic analysis of a regression model for assessing the severity of the course Lyme borreliosis in children.

IF 1.4 Q3 RHEUMATOLOGY Reumatologia Pub Date : 2023-01-01 Epub Date: 2023-10-31 DOI:10.5114/reum/173115
Svetlana Oleksiivna Nykytyuk, Andriy Stepanovych Sverstiuk, Serhiy Ivanovich Klymnyuk, Dmytro Stepanovych Pyvovarchuk, Yuri Bogdanovich Palaniza
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Abstract

Introduction: Lyme borreliosis (LB) is a multisystemic zoonotic disease transmitted by the bite of infected tick vectors.The aim of the study is to develop a mathematical model for predicting the risk of severity of Lyme disease by the risk factor of the disseminated form of LB in children who have had a tick attack. To test the effectiveness of the formula for predicting the development of the disseminated stage of LB, we built a receiver operating characteristic (ROC) curve and determined the specificity and sensitivity of our model. The results of the examination of 122 patients with the confirmed local and disseminated stages of LB were taken as a basis.

Material and methods: To build a prognostic model for prediction of the risk of the developing of the stage in LB predicting the risk of severity of course in Lyme borreliosis (PRSCLB), 122 children (aged 13 ±3 years) with LB were examined using multivariate regression analysis, including 52 boys and 70 girls. Groups of patients: 79 children with erythema migrans, 16 with Lyme arthritis, and 27 with nervous system involvement by LB. The quality of the prognostic model was checked by the Nagelkerke R Square (Nagelkerke R2) and the acceptability of this model was assessed using ROC analysis.

Results: The method of multivariate regression analysis for predicting severe course and organ and system damage in LB in children, taking into account the factors and variants of the disease itself, makes it possible to develop a mathematical model for predicting the relative response factors (RRF) of severe forms of Lyme disease and will improve the effectiveness of treatment. This will create all the prerequisites for high-quality preventive measures and reduce the relative response factors rate.The initial data for predicting the severity of LB were 28 factors. According to the results of regression analysis, 24 factors were included in the model for predicting the severity of LB.

Conclusions: The results of the study showed that the multifactorial model predicts the severity and organ and system damage in LB in children with an accuracy of 95%. The ROC curve, which was built on the basis of the results, has an area under the curve of 0.94, which indicates the high efficiency of the model.

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评估儿童莱姆病病程严重程度的回归模型的预测方法和受试者工作特征分析。
简介:莱姆病是一种多系统的人畜共患疾病,由受感染的蜱虫叮咬传播。该研究的目的是建立一个数学模型,通过感染蜱虫的儿童传播型LB的危险因素来预测莱姆病严重程度的风险。为了检验该公式预测LB扩散阶段发展的有效性,我们建立了受试者工作特征(ROC)曲线,并确定了我们模型的特异性和敏感性。以122例确诊为局部和弥散性LB患者的检查结果为依据。材料与方法:采用多因素回归分析方法对122例(13±3岁)LB患儿(男52例,女70例)进行分析,以建立预测LB分期发展风险和预测PRSCLB病程严重程度风险的预后模型。患者组:迁移性红斑患儿79例,莱姆病患儿16例,LB累及神经系统患儿27例。采用Nagelkerke R平方(Nagelkerke R2)检查预后模型的质量,并采用ROC分析评估该模型的可接受性。结果:多因素回归分析预测儿童莱姆病严重病程和器官系统损害的方法,考虑疾病本身的因素和变异,可以建立预测莱姆病严重形式相对反应因子(RRF)的数学模型,提高治疗效果。这将为高质量的预防措施创造一切先决条件,并降低相对反应因子率。预测LB严重程度的初始数据为28个因素。根据回归分析结果,将24个因素纳入预测LB严重程度的模型。结论:本研究结果表明,多因素模型预测儿童LB的严重程度和器官系统损害的准确率为95%。在此基础上建立的ROC曲线曲线下面积为0.94,表明模型的效率较高。
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来源期刊
Reumatologia
Reumatologia Medicine-Rheumatology
CiteScore
2.70
自引率
0.00%
发文量
44
审稿时长
10 weeks
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