Suppr超能文献

心脏骤停后患者获得良好神经功能结局的最佳平均动脉压。

Optimal mean arterial pressure for favorable neurological outcomes in patients after cardiac arrest.

作者信息

Lee Sijin, Lee Kwang-Sig, Han Kap Su, Song Juhyun, Lee Sung Woo, Kim Su Jin

机构信息

Department of Emergency Medicine, Korea University College of Medicine & Anam Hospital, 73, Goryeodae-Ro, Seongbuk-Gu, Seoul, Republic of Korea.

AI Center, Korea University College of Medicine, Seoul, Republic of Korea.

出版信息

J Intensive Care. 2025 Jul 31;13(1):42. doi: 10.1186/s40560-025-00814-x.

Abstract

BACKGROUND

Optimal mean arterial pressure (MAP) range after cardiac arrest remains uncertain. This study aimed to investigate the association between MAP and neurological outcomes during the early post-resuscitation period, with the goal of identifying optimal MAP range associated with favorable outcomes.

METHODS

This retrospective observational study included 291 post-cardiac arrest patients treated at a tertiary care center. Five machine learning models to predict favorable neurological outcomes using hourly MAP measurements during the first 24 h after return of spontaneous circulation (ROSC) were compared and Random Forest model was selected due to its superior performance. Variable importance and Shapley Additive exPlanations (SHAP) were used to investigate the association between MAP and favorable neurological outcomes. SHAP dependence plots were used to identify optimal MAP ranges associated with favorable outcomes. In addition, individual-level predictions were interpreted using local interpretable model-agnostic explanations (LIME) and SHAP force plots.

RESULTS

Machine learning analysis showed that MAP were associated with favorable neurological outcomes, with higher variable importance during the first 6 h after ROSC. SHAP analysis revealed an inverted U-shaped relationship between MAP and favorable neurological outcomes, with an optimal threshold of 79.56 mmHg (IQR: 73.70-82.54). This threshold remained consistent across both early (1-6 h: 79.26 mmHg) and later (7-24 h: 80.09 mmHg) hours. Individual-level explanations using SHAP and LIME highlighted that maintaining higher MAP during the early post-resuscitation period contributed positively to outcome predictions.

CONCLUSIONS

Machine learning analysis identified MAP as a major predictor of favorable neurological outcomes, with higher variable importance during the first 6 h after ROSC. MAP showed an inverted U-shaped relationship with favorable neurological outcomes, with an optimal threshold of approximately 80 mmHg.

摘要

背景

心脏骤停后的最佳平均动脉压(MAP)范围仍不确定。本研究旨在调查复苏后早期MAP与神经功能结局之间的关联,以确定与良好结局相关的最佳MAP范围。

方法

这项回顾性观察性研究纳入了在一家三级医疗中心接受治疗的291例心脏骤停后患者。比较了五种使用自主循环恢复(ROSC)后首24小时每小时MAP测量值预测良好神经功能结局的机器学习模型,并因随机森林模型性能优越而选择了该模型。使用变量重要性和Shapley加性解释(SHAP)来研究MAP与良好神经功能结局之间的关联。使用SHAP依赖图来确定与良好结局相关的最佳MAP范围。此外,使用局部可解释模型无关解释(LIME)和SHAP力图对个体水平的预测进行解释。

结果

机器学习分析表明,MAP与良好神经功能结局相关,在ROSC后的首6小时内变量重要性更高。SHAP分析显示MAP与良好神经功能结局之间呈倒U形关系,最佳阈值为79.56 mmHg(四分位间距:73.70 - 82.54)。该阈值在早期(1 - 6小时:79.26 mmHg)和后期(7 - 24小时:80.09 mmHg)均保持一致。使用SHAP和LIME进行的个体水平解释强调,在复苏后早期维持较高的MAP对结局预测有积极作用。

结论

机器学习分析确定MAP是良好神经功能结局的主要预测指标,在ROSC后的首6小时内变量重要性更高。MAP与良好神经功能结局呈倒U形关系,最佳阈值约为80 mmHg。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dc3/12315296/4e89234a7586/40560_2025_814_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验