Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450000, Henan, China.
Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China.
Sci Rep. 2022 Aug 12;12(1):13709. doi: 10.1038/s41598-022-17916-3.
Perioperative cardiac arrest (POCA) is associated with a high mortality rate. This work aimed to study its prognostic factors for risk mitigation by means of care management and planning. A database of 380,919 surgeries was reviewed, and 150 POCAs were curated. The main outcome was mortality prior to hospital discharge. Patient demographic, medical history, and clinical characteristics (anesthesia and surgery) were the main features. Six machine learning (ML) algorithms, including LR, SVC, RF, GBM, AdaBoost, and VotingClassifier, were explored. The last algorithm was an ensemble of the first five algorithms. k-fold cross-validation and bootstrapping minimized the prediction bias and variance, respectively. Explainers (SHAP and LIME) were used to interpret the predictions. The ensemble provided the most accurate and robust predictions (AUC = 0.90 [95% CI, 0.78-0.98]) across various age groups. The risk factors were identified by order of importance. Surprisingly, the comorbidity of hypertension was found to have a protective effect on survival, which was reported by a recent study for the first time to our knowledge. The validated ensemble classifier in aid of the explainers improved the predictive differentiation, thereby deepening our understanding of POCA prognostication. It offers a holistic model-based approach for personalized anesthesia and surgical treatment.
围手术期心脏骤停（POCA）与高死亡率相关。本研究旨在通过护理管理和计划来研究其预后因素，以降低风险。我们回顾了一个包含 380919 例手术的数据库，其中 150 例发生了 POCA。主要结局是在出院前的死亡率。患者的人口统计学、病史和临床特征（麻醉和手术）是主要特征。我们探讨了六种机器学习（ML）算法，包括逻辑回归（LR）、支持向量机（SVC）、随机森林（RF）、梯度提升机（GBM）、自适应增强（AdaBoost）和投票分类器（VotingClassifier）。最后一个算法是前五个算法的集成。k 折交叉验证和自举分别最小化了预测偏差和方差。解释器（SHAP 和 LIME）用于解释预测。集成在各个年龄段都提供了最准确和稳健的预测（AUC=0.90[95%CI，0.78-0.98]）。按重要性顺序确定了危险因素。令人惊讶的是，我们首次发现高血压合并症对生存有保护作用，这是最近的一项研究报道的。经过验证的集成分类器辅助解释器提高了预测的区分度，从而加深了我们对 POCA 预后的理解。它提供了一种基于整体模型的个性化麻醉和手术治疗方法。
