Dong Fen, Ren Xiaoxia, Huang Ke, Wang Yanyan, Jiao Jianjun, Yang Ting
Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, China.
Front Med (Lausanne). 2021 Apr 6;8:630870. doi: 10.3389/fmed.2021.630870. eCollection 2021.
In patients with chronic obstructive pulmonary disease (COPD), acute exacerbations affect patients' health and can lead to death. This study was aimed to develop a prediction model for in-hospital mortality in patients with acute exacerbations of COPD (AECOPD). A retrospective study was performed in patients hospitalized for AECOPD between 2015 and 2019. Patients admitted between 2015 and 2017 were included to develop model and individuals admitted in the following 2 years were included for external validation. We analyzed variables that were readily available in clinical practice. Given that death was a rare outcome in this study, we fitted Firth penalized logistic regression. C statistic and calibration plot quantified the model performance. Optimism-corrected C statistic and slope were estimated by bootstrapping. Accordingly, the prediction model was adjusted and then transformed into risk score. Between 2015 and 2017, 1,096 eligible patients were analyzed, with a mean age of 73 years and 67.8% male. The in-hospital mortality was 2.6%. Compared to survivors, non-survivors were older, more admitted from emergency, more frequently concomitant with respiratory failure, pneumothorax, hypoxic-hypercarbic encephalopathy, and had longer length of stay (LOS). Four variables were included into the final model: age, respiratory failure, pneumothorax, and LOS. In internal validation, C statistic was 0.9147, and the calibration slope was 1.0254. Their optimism-corrected values were 0.90887 and 0.9282, respectively, indicating satisfactory discrimination and calibration. When externally validated in 700 AECOPD patients during 2018 and 2019, the model demonstrated good discrimination with a C statistic of 0.8176. Calibration plot illustrated a varying discordance between predicted and observed mortality. It demonstrated good calibration in low-risk patients with predicted mortality rate ≤10% ( = 0.3253) but overestimated mortality in patients with predicted rate >10% ( < 0.0001). The risk score of 20 was regarded as a threshold with an optimal Youden index of 0.7154. A simple prediction model for AECOPD in-hospital mortality has been developed and externally validated. Based on available data in clinical setting, the model could serve as an easily used instrument for clinical decision-making. Complications emerged as strong predictors, underscoring an important role of disease management in improving patients' prognoses during exacerbation episodes.
在慢性阻塞性肺疾病(COPD)患者中,急性加重会影响患者健康并可能导致死亡。本研究旨在建立慢性阻塞性肺疾病急性加重(AECOPD)患者院内死亡的预测模型。对2015年至2019年因AECOPD住院的患者进行了一项回顾性研究。纳入2015年至2017年入院的患者以建立模型,纳入随后两年入院的患者进行外部验证。我们分析了临床实践中容易获得的变量。鉴于本研究中死亡是一种罕见结局,我们采用了Firth惩罚逻辑回归。C统计量和校准图对模型性能进行了量化。通过自抽样估计了乐观校正后的C统计量和斜率。据此,对预测模型进行调整,然后转换为风险评分。2015年至2017年期间,分析了1096例符合条件的患者,平均年龄73岁,男性占67.8%。院内死亡率为2.6%。与幸存者相比,非幸存者年龄更大,更多从急诊科入院,更频繁合并呼吸衰竭、气胸、缺氧-高碳酸血症性脑病,且住院时间更长(LOS)。最终模型纳入了四个变量:年龄、呼吸衰竭、气胸和住院时间。在内部验证中,C统计量为0.9147,校准斜率为1.0254。它们的乐观校正值分别为0.90887和0.9282,表明具有令人满意的区分度和校准度。在2018年至2019年期间对700例AECOPD患者进行外部验证时,该模型显示出良好的区分度,C统计量为0.8176。校准图显示预测死亡率与观察到的死亡率之间存在不同程度的不一致。在预测死亡率≤10%的低风险患者中显示出良好的校准度( = 0.3253),但在预测率>10%的患者中高估了死亡率( < 0.0001)。将风险评分20视为阈值,最佳约登指数为0.7154。已建立并外部验证了一个用于AECOPD院内死亡的简单预测模型。基于临床环境中的可用数据,该模型可作为临床决策中易于使用的工具。并发症是强有力的预测因素,强调了疾病管理在改善患者加重期预后方面的重要作用。