Department of Respiratory Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
Pneumologie/Allergologie, Medizinische Klinik 1, Klinikum der Johann Wolfgang Goethe-Universität, Frankfurt, Germany.
Respirology. 2019 Aug;24(8):765-776. doi: 10.1111/resp.13538. Epub 2019 Mar 21.
Exacerbations of chronic obstructive pulmonary disease (ECOPD) are associated with increased in-hospital and short-term mortality. Developing an easy-to-use model to predict adverse outcomes will be useful in daily clinical practice and will facilitate management decisions. We aimed to assess mortality rates and potential predictors for short-term mortality after severe ECOPD. Classification and Regression Tree (CART) model was used to identify predictors of adverse outcome.
A retrospective observational cohort study, including all patients admitted to Maastricht University Medical Center with ECOPD between June 2011 and December 2014 was performed. The last admission was taken into account, and its demographic, clinical and biochemical data were recorded.
A total of 364 hospitalized patients were enrolled. Mean (SD) age was 70.5 (10.2) years, 54.4% were male and mean FEV 45.2% (17.7) of predicted. The in-hospital and 90-day mortality were, respectively, 8.5 and 16.2%. Independent risk factors for 90-day mortality were: PaC0 (odds ratio (OR): 1.31; 95% confidence interval (CI): 1.00-0.35), age (OR: 1.09; CI: 0.06-0.11), body mass index (BMI) < 18.5 kg/m (OR: 2.72; 95% CI: 0.53-1.47) and previous admission for ECOPD in last 2 years (OR: 1.29; 95% CI: -0.14, -0.65). The CART model selected PaCO ≥ 9.1 kPa, age > 80 years, BMI < 18.5 kg/m and previous admission for ECOPD as the most discriminatory factors.
According CART analysis, high PaCO and age, low BMI and previous admission for ECOPD in last 2 years were the strongest predictors of 90-day mortality in patients with severe ECOPD. In absence of any of these factors, no patients died, suggesting that this model indeed enables risk stratification.
慢性阻塞性肺疾病（COPD）急性加重（AECOPD）与住院期间和短期死亡率增加相关。开发一种易于使用的模型来预测不良结局将有助于日常临床实践，并有助于管理决策。我们旨在评估重度 AECOPD 后短期死亡率的发生率和潜在预测因素。使用分类回归树（CART）模型来确定不良结局的预测因素。
进行了一项回顾性观察队列研究，纳入了 2011 年 6 月至 2014 年 12 月期间在马斯特里赫特大学医学中心因 AECOPD 住院的所有患者。考虑了最后一次入院，并记录了其人口统计学、临床和生化数据。
共纳入 364 例住院患者。平均（SD）年龄为 70.5（10.2）岁，54.4%为男性，FEV 预测值为 45.2%（17.7）。住院期间和 90 天死亡率分别为 8.5%和 16.2%。90 天死亡率的独立危险因素为：PaCO（比值比（OR）：1.31；95%置信区间（CI）：1.00-0.35）、年龄（OR：1.09；CI：0.06-0.11）、BMI<18.5 kg/m（OR：2.72；95%CI：0.53-1.47）和过去 2 年内因 AECOPD 入院（OR：1.29；95%CI：-0.14，-0.65）。CART 模型选择 PaCO ≥ 9.1 kPa、年龄>80 岁、BMI<18.5 kg/m 和过去 2 年内因 AECOPD 入院作为最具鉴别力的因素。
根据 CART 分析，高 PaCO、高龄、低 BMI 和过去 2 年内因 AECOPD 入院是重度 AECOPD 患者 90 天死亡率的最强预测因素。如果没有这些因素中的任何一个，就没有患者死亡，这表明该模型确实能够进行风险分层。
