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在重症肺炎中使用人工智能对胸部肌肉质量的集群分析

Yoon-Hee Choi¹, Dong Hyun Kim², Eun-Tae Jeon³

¹Department of Physical Medicine and Rehabilitation, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Republic of Korea.

Scientific reports

|July 23, 2024

概括

使用人工智能增强的CT扫描来评估胸部肌肉质量,可以预测严重肺炎患者的结果. 较高的肌肉质量与更好的输出成功和较低的死亡率相关,提供了一种新的预后工具.

科学领域:

医疗成像医学成像
密集护理医学密集护理医学
生物标志物生物标志物

背景情况:

严重的肺炎在重症监护病房 (ICU) 中具有显著的发病率和死亡率挑战.
目前的预后工具可能无法完全捕捉重症肺炎患者的结果.
胸部肌肉质量是一个潜在的,但尚未充分利用的,患者健康状况的指标.

研究的目的:

通过CT扫描评估胸部肌肉质量的研究,作为严重肺炎患者临床结果的预测生物标志物.
评估人工智能驱动的肌肉质量分析在预测输出管成功和住院死亡率方面的有效性.
将肌肉质量指标的预测性能与已建立的分数系统 (如APACHE II和SOFA) 进行比较.

主要方法:

对778名患有严重社区肺炎的ICU患者的回顾性分析 (2016年1月 - 2021年12月).
胸部CT扫描的AI增强的3D细分,以量化胸部肌肉质量.
根据肌肉质量概况对患者进行分组,并评估与临床结果的相关性 (输出管成功,住院死亡率).

主要成果:

根据胸部肌肉质量确定了三个不同的患者群.
较高的肌肉质量 (集群1) 与较低的住院死亡率 (8%与集群3的29%相比) 和改善的输出成功率有显著的关联.
与传统得分相比,结合肌肉质量指标的预测模型显示出更高的性能 (AUC 0.844用于输出成功,0.696用于死亡率).

结论:

使用人工智能增强的CT分析评估的胸部肌肉质量,在严重的肺炎中作为一种强有力的预后生物标志物.
这种人工智能驱动的方法为预测患者结果的传统评分系统提供了一个有希望的替代方案或补充.
将胸肌质量评估纳入临床实践可以加强个性化管理,改善严重肺炎患者的治疗结果.

关键词:

气道输出管是气道的输出管.在重症监护病房的重症监护病房.机器学习是机器学习.死亡率死亡率死亡率肌肉肌肉肌肉肌肉肺炎是一种肺炎.骨的骨架部分

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