Fan Vincent S, Ramsey Scott D, Make Barry J, Martinez Fernando J
Health Services Research and Development Center of Excellence, VA Puget Sound Health Care System, Seattle, WA 98108-1597, USA.
COPD. 2007 Mar;4(1):29-39. doi: 10.1080/15412550601169430.
Using clinical and claims records from the National Emphysema Treatment Trial, we sought to identify factors that accurately predicted COPD exacerbations. This prospective cohort study consisted of subjects with severe emphysema randomized to medical therapy. Exacerbations were defined as a hospitalization or emergency department visit for COPD. Patient characteristics obtained before randomization were entered as independent variables in multivariable logistic regression models to estimate the risk of exacerbation. Discrimination was determined using the area under the receiver operator characteristic curve (AUC). Baseline measures included demographics, body mass index, pulmonary function, arterial blood gases, radiology studies, dyspnea (Shortness of Breath Questionnaire - SOBQ), health-related quality of life (St. George's Respiratory Questionnaire - SGRQ), 6-minute walk, exercise capacity, medication use, prior exacerbations and co-morbidity. In 610 participants, 26.6% had a COPD exacerbation over 1-year follow-up. In a model incorporating spirometry, PaO2, dyspnea, prior exacerbations and co-morbidity, a 5-point decrement in percent predicted FEV1 (OR 1.16, 95% CI 1.00-1.34) and a 5-point worsening in SOBQ (OR 1.08, 1.02-1.14) independently predicted exacerbations (AUC for full model 0.68). Combining physiologic variables, dyspnea, prior exacerbations and co-morbidity may be useful in identifying patients at high risk for COPD exacerbations.
利用国家肺气肿治疗试验的临床和理赔记录,我们试图确定能准确预测慢性阻塞性肺疾病(COPD)急性加重的因素。这项前瞻性队列研究的对象为重度肺气肿患者,他们被随机分配接受药物治疗。急性加重被定义为因COPD而住院或前往急诊科就诊。将随机分组前获得的患者特征作为自变量纳入多变量逻辑回归模型,以评估急性加重的风险。使用受试者工作特征曲线下面积(AUC)来确定判别能力。基线测量指标包括人口统计学特征、体重指数、肺功能、动脉血气、放射学检查、呼吸困难(气短问卷 - SOBQ)、健康相关生活质量(圣乔治呼吸问卷 - SGRQ)、6分钟步行距离、运动能力、药物使用情况、既往急性加重史和合并症。在610名参与者中,26.6%在1年的随访期内出现了COPD急性加重。在一个纳入肺活量测定、动脉血氧分压(PaO2)、呼吸困难、既往急性加重史和合并症的模型中,预计第一秒用力呼气容积(FEV1)百分比下降5个百分点(比值比[OR]为1.16,95%置信区间[CI]为1.00 - 1.34)以及SOBQ恶化5分(OR为1.08,1.02 - 1.14)可独立预测急性加重(完整模型的AUC为0.68)。综合生理变量、呼吸困难、既往急性加重史和合并症可能有助于识别COPD急性加重高风险患者。