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Significant risk factors for intensive care unit-acquired weakness: A processing strategy based on repeated machine
1Intensive Care Unit, People's Hospital of Qiandongnan Miao and Dong Autonomous Prefecture, Kaili 556000, Guizhou Province, China. 463082910@qq.com.
World Journal of Clinical Cases
|March 25, 2024
Summary
Intensive care unit-acquired weakness (ICU-AW) is often caused by prolonged mechanical ventilation and extended ICU stays. Minimizing these factors is key to preventing ICU-AW and improving patient recovery.
Area of Science:
- Critical Care Medicine
- Neurology
- Rehabilitation Medicine
Background:
- Intensive care unit-acquired weakness (ICU-AW) is a frequent complication impacting patient recovery and outcomes.
- Effective preventive strategies for ICU-AW are currently lacking.
Purpose of the Study:
- To identify key risk factors for ICU-AW using machine learning.
- To provide recommendations for ICU-AW prevention and treatment.
Main Methods:
- Patients were classified into ICU-AW and non-ICU-AW groups based on 14-day ICU stay data.
- Iterative machine learning, including a multilayer perceptron neural network, was used to analyze risk factors.
- Model performance was evaluated using receiver operating characteristic (ROC) curve analysis.
Main Results:
- Significant risk factors for ICU-AW included longer ICU stay, extended mechanical ventilation, and specific comorbidities (e.g., sepsis, organ failure).
- The most influential factors identified were length of ICU stay (100.0%) and duration of mechanical ventilation (54.9%).
- The neural network model demonstrated high predictive accuracy for ICU-AW (AUC=0.941, sensitivity=92.2%, specificity=82.7%).
Conclusions:
- Length of ICU stay and duration of mechanical ventilation are primary drivers of ICU-AW.
- Minimizing ICU stay and mechanical ventilation duration is a crucial preventive strategy for ICU-AW.
