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Are peak flow and symptom measures good predictors of asthma hospitalizations and unscheduled visits?

机译:高峰流量和症状指标是否可以很好地预测哮喘住院和非计划就诊?

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Epidemiologic studies of pediatric respiratory health often include objective measures such as peak expiratory flow (PEF), and subjective measures such as symptom reports. These measures, however, are poorly correlated with each other, and there is little evidence that PEF is useful in predicting important health outcomes. Within a cohort of 791 inner-city children with asthma, we examined correlations between a series of five peak flow measures and five symptom scores obtained from 2-week diaries. The strongest correlations were found between "total peak flow lability" defined as: [(diary maximum - diary minimum)/diary mean] and "% of days with chest tightness" (r = 0.31). Logistic models evaluated peak flow and symptoms as predictors of an important health outcome: hospitalization or emergency department or unscheduled clinic visit for asthma within 30 days of starting the diary. Each of the peak flow and symptom measures was significantly related to utilization. However, the predictive power of each measure was low (range of area under ROC curve, 0.54-0.67). Models including only peak flow or symptoms had greater prediction than models with risk factors such as atopy, asthma persistence, and age. The prediction from a model with the risk factors and symptoms was not improved by adding a peak flow measure to the model (increase in area under ROC, 0.67-0.68). Stratified analyses suggest that prediction was similar in the fall vs. winter, spring, and summer months. Greater prediction of health outcomes was found among more persistent asthmatics and children who were nonatopic. These findings suggest that in a research setting, peak flow monitoring in children did not add prediction beyond that obtained from symptom reports. Pediatr Pulmonol. 2001; 31:190-197. Published 2001 Wiley-Liss, Inc.
机译:小儿呼吸健康的流行病学研究通常包括客观措施,例如峰值呼气量(PEF),以及主观措施,例如症状报告。但是,这些措施之间的关联性很差,几乎没有证据表明PEF可用于预测重要的健康结局。在一个791名内城区哮喘儿童的队列中,我们检查了一系列5个峰值流量测量值与2周日记中获得的5个症状评分之间的相关性。在“总峰值流量不稳定性”定义为[[(最大日记-最小日记)/日记平均值]和“有胸闷的天数百分比”之间(r = 0.31),发现最强的相关性。逻辑模型评估峰值流量和症状可作为预测重要健康结局的指标:开始日记后30天内住院或急诊或计划外就诊哮喘。峰值流量和症状指标均与利用率显着相关。但是,每种量度的预测能力均很低(ROC曲线下的面积范围为0.54-0.67)。仅包含峰值流量或症状的模型比具有特应性,哮喘持续性和年龄等危险因素的模型具有更好的预测。通过向模型添加峰值流量度量(ROC下面积增加0.67-0.68),无法改善具有风险因素和症状的模型的预测。分层分析表明,秋季与冬季,春季和夏季的预测相似。在更持久的哮喘患者和非特应性儿童中发现了对健康结局的更好预测。这些发现表明,在研究环境中,对儿童的峰值流量监控并未增加从症状报告中获得的预测。小儿科薄荷油。 2001年; 31:190-197。 2001年出版的Wiley-Liss,Inc.

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