Walewski Katherine M, Cicutto Lisa, D'Urzo Anthony D, Heslegrave Ronald J, Chapman Kenneth R
The Division of Respiratory Medicine, Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
J Asthma. 2004 Feb;41(1):77-83. doi: 10.1081/jas-120026064.
Compliance with anti-asthma medication is essential in controlling symptoms and exacerbations in patients with asthma. Unfortunately, not all patients adhere to their treatment regimen, and it is difficult for clinicians to estimate a patient's compliance, since there is no simple and accurate method currently available to assist in its assessment. The objective of this study was to assess the validity and accuracy of utilizing clinical information regarding a patient's prescription refill frequency, inhaler emptying rate, reported forgetfulness, and short-acting bronchodilator usage to predict daily, anti-inflammatory intake. A questionnaire based on the clinical information described above was administered verbally to asthma patients with varying disease severities. Patient responses were compared to the patient's own pharmacy records. Questions that correlated significantly with pharmacy records were subsequently fit into a multiple regression model. Out of 147 eligible participants, 70 completed the questionnaire and had comprehensive pharmacy data available. There was a significant correlation between daily anti-inflammatory intake as estimated by pharmacy records and daily anti-inflammatory intake as determined by inhaler emptying rate (p<0.05), reported forgetfulness (p<0.05), and short-acting bronchodilator usage (p<0.05). These items were fit into a multiple regression model, which was predictive of daily anti-inflammatory intake as determined by pharmacy records. The sensitivity and specificity of our regression model in detecting non-compliance was 44% and 86%, respectively. We conclude that by inquiring into a patient's inhaler emptying rate, reported forgetfulness, and short-acting bronchodilator usage, a clinician may be able to more accurately estimate a patient's daily intake of anti-inflammatory medication.
坚持使用抗哮喘药物对于控制哮喘患者的症状和病情加重至关重要。不幸的是，并非所有患者都能坚持其治疗方案，而且临床医生很难评估患者的依从性，因为目前没有简单准确的方法来辅助进行评估。本研究的目的是评估利用有关患者处方 refill 频率、吸入器清空率、报告的遗忘情况和短效支气管扩张剂使用情况的临床信息来预测每日抗炎药物摄入量的有效性和准确性。基于上述临床信息的问卷以口头方式发放给不同疾病严重程度的哮喘患者。将患者的回答与患者自己的药房记录进行比较。随后将与药房记录有显著相关性的问题纳入多元回归模型。在147名符合条件的参与者中，70人完成了问卷并拥有完整的药房数据。药房记录估计的每日抗炎药物摄入量与吸入器清空率确定的每日抗炎药物摄入量之间存在显著相关性（p<0.05）、报告的遗忘情况（p<0.05）和短效支气管扩张剂使用情况（p<0.05）。这些项目被纳入多元回归模型，该模型可预测药房记录确定的每日抗炎药物摄入量。我们的回归模型检测不依从性的敏感性和特异性分别为44%和86%。我们得出结论，通过询问患者的吸入器清空率、报告的遗忘情况和短效支气管扩张剂使用情况，临床医生可能能够更准确地估计患者每日抗炎药物的摄入量。
