Ding Guangqian, Kuang Ailing, Zhou Zhongbo, Lin Youping, Chen Yi
Department of Intensive Care Medicine, Binhaiwan Central Hospital of Dongguan, Guangdong Province, China; The Key Laboratory for Prevention and Treatment of Critical Illness in Dongguan City, Guangdong Province, China.
Department of Emergency, Binhaiwan Central Hospital of Dongguan, Dongguan City, Guangdong Province, China.
Am J Emerg Med. 2024 May;79:172-182. doi: 10.1016/j.ajem.2024.02.022. Epub 2024 Feb 19.
The survivors of cardiac arrest experienced vary extent of hypoxic ischemic brain injury causing mortality and long-term neurologic disability. However, there is still a need to develop robust and reliable prognostic models that can accurately predict these outcomes.
To establish reliable models for predicting 90-day neurological function and mortality in adult ICU patients recovering from cardiac arrest.
We enrolled patients who had recovered from cardiac arrest at Binhaiwan Central Hospital of Dongguan, from January 2018 to July 2021. The study's primary outcome was 90-day neurological function, assessed and divided into two categories using the Cerebral Performance Category (CPC) scale: either good (CPC 1-2) or poor (CPC 3-5). The secondary outcome was 90-day mortality. We analyzed the relationships between risk factors and outcomes individually. A total of four models were developed: two multivariable logistic regression models (models 1 and 2) for predicting neurological function, and two Cox regression models (models 3 and 4) for predicting mortality. Models 2 and 4 included new neurological biomarkers as predictor variables, while models 1 and 3 excluded. We evaluated calibration, discrimination, clinical utility, and relative performance to establish superiority between the models.
Model 1 incorporates variables such as gender, site of cardiopulmonary resuscitation (CPR), total CPR time, and acute physiology and chronic health evaluation II (APACHE II) score, while model 2 includes gender, site of CPR, APACHE II score, and serum level of ubiquitin carboxy-terminal hydrolase L1 (UCH-L1). Model 2 outperforms model 1, showcasing a superior area under the receiver operating characteristic curve (AUC) of 0.97 compared to 0.83. Additionally, model 2 exhibits improved accuracy, sensitivity, and specificity. The decision curve analysis confirms the net benefit of model 2. Similarly, models 3 and 4 are designed to predict 90-day mortality. Model 3 incorporates the variables such as site of CPR, total CPR time, and APACHE II score, while model 4 includes APACHE II score, total CPR time, and serum level of UCH-L1. Model 4 outperforms model 3, showcasing an AUC of 0.926 and a C-index of 0.830. The clinical decision curve analysis also confirms the net benefit of model 4.
By integrating new neurological biomarkers, we have successfully developed enhanced models that can predict 90-day neurological function and mortality outcomes more accurately.
心脏骤停幸存者经历了不同程度的缺氧缺血性脑损伤，导致死亡和长期神经功能残疾。然而，仍需要开发强大且可靠的预后模型，以准确预测这些结果。
建立可靠的模型，用于预测从心脏骤停中恢复的成年ICU患者90天的神经功能和死亡率。
我们纳入了2018年1月至2021年7月在东莞滨海湾中心医院从心脏骤停中恢复的患者。该研究的主要结局是90天的神经功能，使用脑功能分类（CPC）量表进行评估并分为两类：良好（CPC 1-2）或不良（CPC 3-5）。次要结局是90天死亡率。我们分别分析了危险因素与结局之间的关系。共开发了四个模型：两个用于预测神经功能的多变量逻辑回归模型（模型1和模型2），以及两个用于预测死亡率的Cox回归模型（模型3和模型4）。模型2和模型4将新的神经生物标志物作为预测变量，而模型1和模型3则排除了这些标志物。我们评估了校准、区分度、临床实用性和相对性能，以确定模型之间的优越性。
模型1纳入了性别、心肺复苏（CPR）部位、总CPR时间和急性生理与慢性健康状况评估II（APACHE II）评分等变量，而模型2包括性别、CPR部位、APACHE II评分和泛素羧基末端水解酶L1（UCH-L1）的血清水平。模型2优于模型1，其受试者操作特征曲线（AUC）下面积为0.97，而模型1为0.83。此外，模型2的准确性、敏感性和特异性均有所提高。决策曲线分析证实了模型2的净效益。同样，模型3和模型4旨在预测90天死亡率。模型3纳入了CPR部位、总CPR时间和APACHE II评分等变量，而模型4包括APACHE II评分、总CPR时间和UCH-L1的血清水平。模型4优于模型3，其AUC为0.926，C指数为0.830。临床决策曲线分析也证实了模型4的净效益。
通过整合新的神经生物标志物，我们成功开发了增强模型，能够更准确地预测90天的神经功能和死亡率结局。
