Dept of Medical Decision Making, Leiden University Medical Center, Leiden, The Netherlands.
Eur Respir J. 2013 Jan;41(1):53-9. doi: 10.1183/09031936.00205911. Epub 2012 May 31.
Our aim was to validate optimal action points in written action plans for early detection of asthma exacerbations. We analysed daily symptoms and morning peak expiratory flows (PEFs) from two previous studies. Potential action points were based on analysis of symptom scores (standard deviations) percentage of personal best PEF, PEF variability in relation to a run-in period or combinations of these measures. Sensitivity and specificity for predicting exacerbations were obtained for each action point. The numbers needed to treat to prevent one exacerbation and the time interval between reaching action point criteria and the start of the exacerbation were calculated. Based on these parameters, the optimal action points for symptoms, PEF and PEF plus symptoms were determined, and their performance compared with published guidelines' action points. The optimal action points were, for symptoms, statistical variability (standard deviations) and, for PEF, <70% of personal best. The combination of PEF plus symptoms performed best, with improved specificity and earlier detection. The main benefits associated with using these action points was to reduce false positive rates for detecting exacerbations. Early detection of asthma exacerbations can be improved using a composite action point comprising symptoms and PEF measurements over 1 week.
我们的目的是验证书面哮喘恶化预警计划中最优行动点的有效性。我们分析了来自两项先前研究的每日症状和清晨呼气峰流速（PEF）数据。潜在的行动点基于症状评分（标准差）、个人最佳 PEF 的百分比、PEF 变异与导入期的关系或这些措施的组合进行分析。为每个行动点预测哮喘恶化的敏感性和特异性。计算了每个预防一次恶化所需的治疗人数和达到行动点标准与恶化开始之间的时间间隔。基于这些参数，确定了症状、PEF 和症状加 PEF 的最优行动点，并将其与已发表指南的行动点进行比较。症状的最优行动点是统计学上的可变性（标准差），而对于 PEF，最优行动点是<个人最佳值的 70%。PEF 加症状的组合表现最佳，特异性和早期检测得到改善。使用这些行动点的主要好处是降低了检测哮喘恶化的假阳性率。通过使用包含症状和 PEF 测量值的复合行动点，可以改善哮喘恶化的早期检测。
