Division of Infection Immunity and Respiratory Medicine, School of Biological Sciences, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, The University of Manchester, Manchester, UK.
Department of Medicine, Section of Paediatrics, Imperial College London, London, UK.
Clin Exp Allergy. 2019 Mar;49(3):292-298. doi: 10.1111/cea.13319. Epub 2019 Jan 4.
Current published asthma predictive tools have moderate positive likelihood ratios (+LR) but high negative likelihood ratios (-LR) based on their recommended cut-offs, which limit their clinical usefulness.
To develop a simple clinically applicable asthma prediction tool within a population-based birth cohort.
Children from the Manchester Asthma and Allergy Study (MAAS) attended follow-up at ages 3, 8 and 11 years. Data on preschool wheeze were extracted from primary-care records. Parents completed validated respiratory questionnaires. Children were skin prick tested (SPT). Asthma at 8/11 years (school-age) was defined as parentally reported (a) physician-diagnosed asthma and wheeze in the previous 12 months or (b) ≥3 wheeze attacks in the previous 12 months. An asthma prediction tool (MAAS APT) was developed using logistic regression of characteristics at age 3 years to predict school-age asthma.
Of 336 children with physician-confirmed wheeze by age 3 years, 117(35%) had school-age asthma. Logistic regression selected 5 significant risk factors which formed the basis of the MAAS APT: wheeze after exercise; wheeze causing breathlessness; cough on exertion; current eczema and SPT sensitisation(maximum score 5). A total of 281(84%) children had complete data at age 3 years and were used to test the MAAS APT. Children scoring ≥3 were at high risk of having asthma at school-age (PPV > 75%; +LR 6.3, -LR 0.6), whereas children who had a score of 0 had very low risk(PPV 9.3%; LR 0.2).
MAAS APT is a simple asthma prediction tool which could easily be applied in clinical and research settings.
目前已发表的哮喘预测工具，基于其推荐的截断值，具有中等阳性似然比（+LR）但高阴性似然比（-LR），这限制了它们的临床实用性。
在基于人群的出生队列中开发一种简单的临床适用的哮喘预测工具。
来自曼彻斯特哮喘和过敏研究（MAAS）的儿童在 3、8 和 11 岁时进行随访。从初级保健记录中提取幼儿喘息的数据。父母完成了经过验证的呼吸问卷。对儿童进行皮肤点刺试验（SPT）。8/11 岁（学龄期）哮喘定义为父母报告的（a）过去 12 个月内医生诊断的哮喘和喘息，或（b）过去 12 个月内≥3 次喘息发作。使用 3 岁时的特征进行逻辑回归，为学龄期哮喘预测建立哮喘预测工具（MAAS APT）。
在 3 岁时经医生确诊为喘息的 336 名儿童中，有 117 名（35%）患有学龄期哮喘。逻辑回归选择了 5 个显著的危险因素，它们构成了 MAAS APT 的基础：运动后喘息；喘息导致呼吸困难；运动时咳嗽；当前特应性皮炎和 SPT 致敏（最高得分为 5 分）。共有 281 名（84%）儿童在 3 岁时有完整的数据，用于测试 MAAS APT。得分≥3 的儿童患学龄期哮喘的风险较高（PPV>75%；+LR 6.3，-LR 0.6），而得分 0 的儿童风险非常低（PPV 9.3%；LR 0.2）。
MAAS APT 是一种简单的哮喘预测工具，易于在临床和研究环境中应用。
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