Intensive care unit-acquired weakness:Unveiling significant risk factors and preemptive strategies through machine learning  

作　　者：Xiao-Yu He Yi-Huan Zhao Qian-Wen Wan Fu-Shan Tang 

机构地区：[1]Department of Clinical Pharmacy,Key Laboratory of Basic Pharmacology of Guizhou Province and School of Pharmacy,Zunyi Medical University,Zunyi 563006,Guizhou Province,China

出　　处：《World Journal of Clinical Cases》2024年第35期6760-6763,共4页世界临床病例杂志（英文）

摘　　要：This editorial discusses an article recently published in the World Journal of Clinical Cases,focusing on risk factors associated with intensive care unit-acquired weak-ness(ICU-AW).ICU-AW is a serious neuromuscular complication seen in criti-cally ill patients,characterized by muscle dysfunction,weakness,and sensory impairments.Post-discharge,patients may encounter various obstacles impacting their quality of life.The pathogenesis involves intricate changes in muscle and nerve function,potentially leading to significant disabilities.Given its global significance,ICU-AW has become a key research area.The study identified critical risk factors using a multilayer perceptron neural network model,highlighting the impact of intensive care unit stay duration and mechanical ventilation duration on ICU-AW.Recommendations were provided for preventing ICU-AW,empha-sizing comprehensive interventions and risk factor mitigation.This editorial stresses the importance of external validation,cross-validation,and model tran-sparency to enhance model reliability.Moreover,the application of machine learning in clinical medicine has demonstrated clear benefits in improving disease understanding and treatment decisions.While machine learning presents oppor-tunities,challenges such as model reliability and data management necessitate thorough validation and ethical considerations.In conclusion,integrating ma-chine learning into healthcare offers significant potential and challenges.Enhan-cing data management,validating models,and upholding ethical standards are crucial for maximizing the benefits of machine learning in clinical practice.

关 键 词：Intensive care unit-acquired weakness Risk factors Machine learning Clinical medicine Treatment decision 

分 类 号：R47[医药卫生—护理学]