过敏性鼻炎合并支气管哮喘儿童预测模型的构建与验证。

IF 2.5 4区 医学 Q3 ALLERGY
Qi Zhang, Fengqin Xu, Fuzhe Chen
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引用次数: 0

摘要

本研究旨在探讨支气管哮喘患儿变应性鼻炎并发症的影响因素,建立预测变应性鼻炎发生的nomogram模型。回顾性分析2020年8月至2024年8月我院收治的支气管哮喘患儿190例。按7:3的比例随机分为训练组(133例)和验证组(57例)。根据是否伴有变应性鼻炎,将建模组儿童分为变应性鼻炎组(n=44)和非变应性鼻炎组(n=89)。190例支气管哮喘患儿中有62例合并变应性鼻炎,发生率为32.63%。在训练队列中,与非变应性鼻炎组的儿童相比,变应性鼻炎组的家庭吸烟者百分比、c反应蛋白(CRP)、白细胞计数(WBC)和中性粒细胞/淋巴细胞(NLR)显著高于非变应性鼻炎组(P < 0.05)。多变量logistic回归分析显示:家庭中吸烟者;IgE;早期使用抗生素;CRP、WBC、NLR升高均为支气管哮喘患儿变应性鼻炎并发症的危险因素(P < 0.05)。基于上述危险因素构建了nomogram预测模型。训练组和验证组的c -指数分别为0.919 (95% CI: 0.742 ~ 0.934)和0.841 (95% CI: 0.773 ~ 0.902)。训练组和验证组的Hosmer-Lemeshow检验结果均为P < 0.05,模型拟合良好。DCA结果显示,训练组和验证组具有良好的阈值概率和临床净收益。家中吸烟者、IgE、CRP、WBC、NLR水平均为支气管哮喘患儿变应性鼻炎并发症的危险因素。基于这些危险因素的nomogram模型可能是预测支气管哮喘患儿变应性鼻炎的一种有价值的临床工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction and validation of a predictive model for allergic rhinitis complicating children with bronchial asthma.

This study aimed to investigate the factors influencing the complication of allergic rhinitis in children with bronchial asthma and to construct a nomogram model to predict the occurrence of allergic rhinitis. A total of 190 children with bronchial asthma admitted to our hospital from August 2020 to August 2024 were retrospectively analyzed. The children were randomly divided into the training cohort (133 cases) and validation cohort (57 cases) in a ratio of 7:3. The children in the modeling set were divided into an allergic rhinitis group (n=44) and a nonallergic rhinitis group (n=89) depending on the presence or absence of concomitant allergic rhinitis. A total of 62 cases in 190 children with bronchial asthma had complications with allergic rhinitis, with an incidence of 32.63%. In the training cohort, compared with the children in the nonallergic rhinitis group, percentage of smokers in the household, C-reactive protein (CRP), white blood cell count (WBC), and neutrophils/lymphocytes (NLR) were significantly higher in the allergic rhinitis group (P < 0.05). Multivariable logistic regression analysis showed that smokers in the household; IgE; early use of antibiotics; and elevated CRP, WBC, and NLR were all risk factors for the complication of allergic rhinitis in children with bronchial asthma (P < 0.05). A nomogram prediction model was constructed based on the above risk factors. The C-index of the nomogram was 0.919 (95% CI: 0.742-0.934) and 0.841 (95% CI: 0.773-0.902) for the training cohort and validation cohort, respectively. The Hosmer-Lemeshow test results of the training and validation cohorts were both P > 0.05, suggesting a good model fit. The results of DCA showed that the training and validation cohorts had good threshold probability and clinical net benefit. Smokers in the household, IgE, CRP, WBC, and NLR levels were all risk factors for the complication of allergic rhinitis in children with bronchial asthma. A nomogram model based on these risk factors may be a valuable clinical tool for predicting allergic rhinitis in children with bronchial asthma.

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来源期刊
CiteScore
3.70
自引率
0.00%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Founded in 1972 by Professor A. Oehling, Allergologia et Immunopathologia is a forum for those working in the field of pediatric asthma, allergy and immunology. Manuscripts related to clinical, epidemiological and experimental allergy and immunopathology related to childhood will be considered for publication. Allergologia et Immunopathologia is the official journal of the Spanish Society of Pediatric Allergy and Clinical Immunology (SEICAP) and also of the Latin American Society of Immunodeficiencies (LASID). It has and independent international Editorial Committee which submits received papers for peer-reviewing by international experts. The journal accepts original and review articles from all over the world, together with consensus statements from the aforementioned societies. Occasionally, the opinion of an expert on a burning topic is published in the "Point of View" section. Letters to the Editor on previously published papers are welcomed. Allergologia et Immunopathologia publishes 6 issues per year and is included in the major databases such as Pubmed, Scopus, Web of Knowledge, etc.
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