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