Xing XueZhong, Gao Yong, Wang HaiJun, Huang ChuLin, Qu ShiNing, Zhang Hao, Wang Hao, Sun KeLin
Department of Intensive Care Unit, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
PLoS One. 2015 Jun 25;10(6):e0131329. doi: 10.1371/journal.pone.0131329. eCollection 2015.
The aim of this study was to evaluate the performance of Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score 3 (SAPS 3), and Acute Physiology and Chronic Health Evaluation IV (APACHE IV) in patients with cancer admitted to intensive care unit (ICU) in a single medical center in China.
This is a retrospective observational cohort study including nine hundred and eighty one consecutive patients over a 2-year period.
The hospital mortality rate was 4.5%. When all 981 patients were evaluated, the area under the receiver operating characteristic curve (AUROC, 95% Confidential Intervals) of the three models in predicting hospital mortality were 0.948 (0.914-0.982), 0.863 (0.804-0.923), and 0.873 (0.813-0.934) for SAPS 3, APACHE II and APACHE IV respectively. The p values of Hosmer-Lemeshow statistics for the models were 0.759, 0.900 and 0.878 for SAPS 3, APACHE II and APACHE IV respectively. However, SAPS 3 and APACHE IV underestimated the in-hospital mortality with standardized mortality ratio (SMR) of 1.5 and 1.17 respectively, while APACHE II overestimated the in-hospital mortality with SMR of 0.72. Further analysis showed that discrimination power was better with SAPS 3 than with APACHE II and APACHE IV whether for emergency surgical and medical patients (AUROC of 0.912 vs 0.866 and 0.857) or for scheduled surgical patients (AUROC of 0.945 vs 0.834 and 0.851). Calibration was good for all models (all p > 0.05) whether for scheduled surgical patients or emergency surgical and medical patients. However, in terms of SMR, SAPS 3 was both accurate in predicting the in-hospital mortality for emergency surgical and medical patients and for scheduled surgical patients, while APACHE IV and APACHE II were not.
In this cohort, we found that APACHE II, APACHE IV and SAPS 3 models had good discrimination and calibration ability in predicting in-hospital mortality of critically ill patients with cancer in need of intensive care. Of these three severity scores, SAPS 3 was superior to APACHE II and APACHE IV, whether in terms of discrimination and calibration power, or standardized mortality ratios.
本研究旨在评估急性生理与慢性健康状况评分系统II(APACHE II)、简化急性生理学评分3(SAPS 3)和急性生理与慢性健康状况评分系统IV(APACHE IV)在中国一家单一医疗中心重症监护病房(ICU)收治的癌症患者中的表现。
这是一项回顾性观察性队列研究,纳入了连续2年的981例患者。
医院死亡率为4.5%。对全部981例患者进行评估时,三种模型预测医院死亡率的受试者工作特征曲线下面积(AUROC,95%可信区间)分别为:SAPS 3为0.948(0.914 - 0.982),APACHE II为0.863(0.804 - 0.923),APACHE IV为0.873(0.813 - 0.934)。各模型的Hosmer - Lemeshow统计量p值分别为:SAPS 3为0.759,APACHE II为0.900,APACHE IV为0.878。然而,SAPS 3和APACHE IV低估了院内死亡率,标准化死亡率(SMR)分别为1.5和1.17,而APACHE II高估了院内死亡率,SMR为0.72。进一步分析表明,无论是急诊手术和内科患者(AUROC分别为0.912 vs 0.866和0.857)还是择期手术患者(AUROC分别为0.945 vs 0.834和0.851),SAPS 3的辨别能力均优于APACHE II和APACHE IV。所有模型对于择期手术患者或急诊手术和内科患者的校准均良好(所有p>0.05)。然而,就SMR而言,SAPS 3在预测急诊手术和内科患者以及择期手术患者的院内死亡率方面均准确,而APACHE IV和APACHE II则不然。
在本队列研究中,我们发现APACHE II、APACHE IV和SAPS 3模型在预测需要重症监护的癌症重症患者的院内死亡率方面具有良好的辨别和校准能力。在这三种严重程度评分中,无论是在辨别和校准能力方面,还是在标准化死亡率方面,SAPS 3均优于APACHE II和APACHE IV。