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首页> 外文期刊>The journal of asthma >Characterization of asthma exacerbations in primary care using cluster analysis
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Characterization of asthma exacerbations in primary care using cluster analysis

机译：使用聚类分析表征初级保健中哮喘加重

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Rationale. Patients with a history of asthma exacerbations are at a higher risk for future episodes of severe asthma exacerbations. Characterization of asthma phenotypes could help improve asthma management, including reducing exacerbations. Aim. The aim of this study is to identify distinctive patient characteristics associated with a history of asthma exacerbations using cluster analysis. Methods. We used data assessing asthma control from two cross-sectional surveys of adult and pediatric patients in the primary care setting. A supervised cluster analysis with recursive partitioning approach was applied to identify characteristics that maximized the differences across subgroups. Results. The sample comprised 2205 adults and 2435 children and adolescents with asthma. Key predictors were identified in seven adult clusters including visiting an asthma specialist, number of hours worked, and excessive use of rescue medication. The rate ratio (RR) for having an exacerbation was significantly higher (2.88; 95% confidence interval (CI), 2.46-3.36) in Cluster 7, with more female patients reporting severe disease, high body mass index, sinus infections, gastroesophageal reflux disease, skin allergies, and lower asthma control score. Features identified in the six pediatric clusters included visiting an asthma specialist, missed school days, race/ethnicity, and age. The RR for having an exacerbation was higher in Cluster 6 (2.36; 95% CI, 2.11-2.64), with patients reporting more severe disease, sinus and skin allergies, and lower asthma control score. Conclusions. Identification of specific risk factors can be enhanced by using supervised cluster analysis. This approach allows grouping of patients with unique characteristics to help identify patients at higher risk of exacerbations.
机译：基本原理。有哮喘急性发作史的患者未来发生严重哮喘急性发作的风险较高。哮喘表型的表征可以帮助改善哮喘管理，包括减轻病情加重。目标。这项研究的目的是使用聚类分析确定与哮喘急性发作史相关的独特患者特征。方法。我们使用了在初级保健机构中对成人和儿童患者进行的两次横断面调查评估哮喘控制的数据。采用递归分区方法进行有监督的聚类分析，以识别可最大化子组间差异的特征。结果。样本包括2205名成人和2435名患有哮喘的儿童和青少年。在七个成年人群中确定了主要的预测因素，包括拜访哮喘病专家，工作时间和过度使用急救药物。在第7组中，急性发作的比率（RR）显着更高（2.88; 95％置信区间（CI），2.46-3.36），更多女性患者报告严重疾病，高体重指数，鼻窦感染，胃食管反流疾病，皮肤过敏和较低的哮喘控制评分。在六个小儿科群中确定的功能包括拜访哮喘病专家，放学时间，种族/民族和年龄。在第6组中，急性发作的RR较高（2.36; 95％CI，2.11-2.64），患者报告的疾病，鼻窦和皮肤过敏更为严重，哮喘控制评分较低。结论。通过使用有监督的聚类分析，可以增强对特定风险因素的识别。这种方法可以对具有独特特征的患者进行分组，以帮助确定病情加重的患者。

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