Esteban Cristóbal, Arostegui Inmaculada, Garcia-Gutierrez Susana, Gonzalez Nerea, Lafuente Iratxe, Bare Marisa, Fernandez de Larrea Nerea, Rivas Francisco, Quintana José M
Servicio de Neumologia, Hospital Galdakao-Usansolo, Barrio Labeaga s/n. 48960, Galdakao, Bizkaia, Spain.
Red de Investigación en Servicios Sanitarios y Enfermedades Crónicas (REDISSEC), Galdakao, Bizkaia, Spain.
Respir Res. 2015 Dec 22;16:151. doi: 10.1186/s12931-015-0313-4.
Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD.
We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50%) and validation samples (50%). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample.
Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0% to 55% in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95% CI: 0.783, 0.888) and 0.794 (95% CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95% CI: 0.776, 0.859) and 0.770 (95% CI: 0.716, 0.823) in the validation sample.
We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care.
NCT02434536.
创建一种易于使用的工具来识别慢性阻塞性肺疾病急性加重（eCOPD）后短期（30/60天）死亡率的预测因素，有助于临床医生选择特定的医疗护理措施以降低这些患者的死亡率。本研究的目的是开发并验证一种分类回归树（CART），以预测在急诊科（ED）因eCOPD接受评估的患者的短期死亡率。
我们进行了一项前瞻性队列研究，纳入了来自西班牙16家医院的参与者。招募了2008年6月至2010年9月期间在任何一家医院急诊科就诊的急性加重期COPD患者。患者被随机分为推导样本（50%）和验证样本（50%）。在推导样本中创建了基于递归划分算法的CART，并应用于验证样本。
2487例患者纳入研究，其中推导样本1252例，验证样本1235例。根据单变量分析结果，使用五个变量（基线呼吸困难、心脏病、出现矛盾呼吸或使用辅助吸气肌、年龄和格拉斯哥昏迷量表评分）构建CART。在五个CART类别中，出院后30天的死亡率从0%到55%不等。死亡率最低的分支由低基线呼吸困难和无心脏病组成。死亡率最高的分支是基线呼吸困难水平最高、到达急诊科时使用辅助吸气肌或出现矛盾呼吸且格拉斯哥评分<15的分支。推导样本中的受试者工作特征曲线下面积（AUC）为0.835（95%CI：0.783，0.888），验证样本中为0.794（95%CI：0.723，0.865）。通过添加查尔森合并症指数改进CART以预测60天死亡率风险，推导样本中的AUC为0.817（95%CI：0.776，0.859），验证样本中为0.770（95%CI：0.716，0.823）。
我们确定了几个易于确定的变量，使临床医生能够根据短期死亡率风险对eCOPD患者进行分类，这可为制定适当的临床护理提供有用信息。
NCT02434536。
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