Abstract: Objective To analyze the risk factors for the occurrence of subsyndromal delirium in mechanically ventilated patients and construct a nomogram risk prediction model to predict the occurrence of subsyndromal delirium. Methods Convenience sampling was used to select 434 mechanically ventilated patients admitted to the ICU of a tertiary hospital in Guizhou Province from July 2021 to June 2022,who were categorized into the subdelirium syndrome group（n=136）and the non-subdelirium syndrome group（n=298）using the ICU Patient Ambi-guity of Consciousness Assessment Scale. We explored the independent risk factors for the occurrence of subde-lirium syndrome through univariate and multifactorial logistic regression analyses,established a risk prediction model,developed a nomogram,and validated the model both internally and externally. Results Multifactorial logistic regression analysis revealed that age（OR=1.029）,acute physiological and chronic health status score（OR=1.267）,whether restrained（OR=1.029）,intensive care pain score（OR=2.487）,Richards-Campbell sleep scale score（OR=1.150）,Richmond agitation-sedation score（OR=1.500）were independent risk factors for the development of subdelirium. The consistency index of the nomogram model for the occurrence of subdelirium in mechanically ventilated patients in the ICU was 0.956,with a sensitivity of 86.2% and a specificity of 94.1%. Conclusion The risk prediction model construc-ted in this study can effectively predict the occurrence of subdelirium syndrome in mechanically ventilated patients,which provides a reference for clinical medical personnel to scientifically predict the occurrence of subdelirium.

Key words: Mechanically Ventilated, Subsyndromal Delirium, Nomogram, Prediction Model, Critical Care Nursing