Supplementary Material for: Prediction model of in-hospital death for AECOPD patients admitted to ICU: the PD-ICU score

Introduction: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to intensive care unit (ICU) are exposed to poor clinical outcomes, and no specific prognostic models are available among these population. We aimed to develop and validate a risk score for prognosis prediction for these patients.
Methods: This was a multicenter observation study. AECOPD patients admitted to ICU were included for model derivation from a prospective, multicenter cohort study. Logistic regression analysis was applied to identify independent predictors for in-hospital death and establish the prognostic risk score. The risk score was further validated and compared with DECAF, BAP-65, CURB-65 and APACHE Ⅱ score in another multicenter cohort.
Results: Five variables were identified as independent predictors for in-hospital death in APCOPD patients admitted to ICU, and a corresponding risk score (PD-ICU score) was established, which was composed of Procalcitonin>0.5ug/L, Diastolic Blood Pressure<60mmHg, Need for Invasive Mechanical Ventilation, Disturbance of Consciousness and Blood Urea Nitrogen>7.2mmol/L. Patients were classified into three risk categories according to PD-ICU score. The in-hospital mortality of low-risk, intermediate-risk, and high-risk patients were 0.3%, 7.3%, and 27.9%, respectively. PD-ICU score displayed excellent discrimination ability with an area under the receiver operating characteristic curve (AUC) of 0.815 in the derivation cohort and 0.754 in the validation cohort which outperformed other prognostic models.
Conclusion: We derived and validated a simple and clinician-friendly prediction model (PD-ICU score) for in-hospital mortality among AECOPD patients admitted to ICU. With good performance and clinical practicability, this model may facilitate early risk stratification and optimal decision-making among these patients.

Introduction: 慢性阻塞性肺疾病急性加重期（acute exacerbation of chronic obstructive pulmonary disease, AECOPD）患者入住重症监护病房（intensive care unit, ICU）后临床预后不佳，且目前尚无针对该人群的特异性预后模型。本研究旨在开发并验证一款用于此类患者预后预测的风险评分模型。
Methods: 本研究为多中心观察性研究。从一项前瞻性多中心队列研究中纳入入住ICU的AECOPD患者，用于模型的推导构建。采用logistic回归分析（logistic regression analysis）识别院内死亡的独立预测因子，并建立预后风险评分模型。随后在另一项多中心队列中对该风险评分进行验证，并与DECAF、BAP-65、CURB-65及APACHE Ⅱ评分进行对比分析。
Results: 本研究共识别出5项可预测入住ICU的AECOPD患者院内死亡的独立预测因子，并据此建立了对应的风险评分模型（PD-ICU评分），该评分包含降钙素原＞0.5μg/L、舒张压＜60mmHg、有创机械通气需求、意识障碍及血尿素氮＞7.2mmol/L共5项指标。根据PD-ICU评分可将患者划分为3个风险层级：低危、中危及高危患者的院内死亡率分别为0.3%、7.3%及27.9%。PD-ICU评分展现出优异的区分能力，其在推导队列中的受试者工作特征曲线下面积（area under the receiver operating characteristic curve, AUC）为0.815，在验证队列中为0.754，性能优于其他预后评分模型。
Conclusion: 本研究成功推导并验证了一款简便易用、适合临床医师使用的预测模型——PD-ICU评分，用于预测入住ICU的AECOPD患者的院内死亡风险。该模型性能优异且临床实用性强，有望助力此类患者的早期风险分层与优化诊疗决策制定。