Abstract: Objective To explore the influencing factors of stress hyperglycemia in patients with acute exacerbation of chronic obstructive pulmonary disease（AECOPD）,and to construct a risk prediction nomogram model. Methods A retrospective study was conducted among 444 AECOPD patients in the emergency intensive care of a tertiary class A hospital in Urumqi from March 2021 to March 2023,and the independent risk factors of stress hyperglycemia in AECOPD patients were explored through univariate analysis and Logistic regression analysis. A risk prediction model was established and incorporated into the nomogram. The prediction performance of the model was tested using the receiver operating characteristic curve（ROC）,and the Hosmer-Lemeshow test was used to determine the goodness of fit of the model. Results The incidence of stress hyperglycemia in AECOPD patients was 24.5%. Logistic regression analysis showed that age,smoking,history of cerebrovascular disease,mechanical ventilation,Acute Physiology and Chronic Health EvaluationⅡ score at admission,coefficient of variation of blood glucose and C-reactive protein were independent influencing factors for stress hyperglycemia in AECOPD patients（P<0.05）. The individual nomogram prediction model was established based on Logistic regression. The area under the receiver operating characteristic curve was 0.823（95%CI：0.780~0.865）,the Hosmer-Lemeshow test P=0.354,the best cutoff value was 0.514,the sensitivity was 0.872,and the specificity was 0.642. The Bootstrap method was used for internal validation,and the C-index was 0.817,indicating that the model had a good prediction effect. Conclusion The prediction model constructed in this study has a good prediction effect,which can provide a reference for effectively evaluating the risk of stress hyperglycemia in patients with AECOPD.

Key words: Acute Exacerbation of Chronic Obstructive Pulmonary Disease, Stress Hyperglycemia, Root Cause Analysis, Nomogram, Nurse Care