Application of PROPDESC and MDP delirium risk prediction models in elderly surgical patients
10.3760/cma.j.cn115682-20221215-06015
- VernacularTitle:PROPDESC和MDP谵妄风险预测模型在老年手术患者中的应用研究
- Author:
Dandan ZHANG
1
;
Ping ZHANG
;
Yuanjun GUO
;
Yinhua SONG
;
Shunluan TANG
Author Information
1. 南方医科大学护理学院，广州 510515
- Keywords:
Aged;
Postoperative delirium;
Prediction model;
External validation;
Predicted performance;
Influencing factor;
Postoperative complication
- From:
Chinese Journal of Modern Nursing
2023;29(25):3394-3401
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore independent predictors of postoperative delirium in elderly patients by PRe-Operative Prediction of postoperative DElirium by appropriate SCreening (PROPDESC) and Mayo Delirium Prediction (MDP) , and analyze the predictive power of the two models.Methods:This study was a prospective Cohort study. Using the convenient sampling method, a total of 636 elderly surgical patients admitted to the Orthopedics, Gastroenterology, Cardiothoracic and Oncology Departments of Shantou Central Hospital from May to August 2022 were selected as the research objects. PROPDESC and MDP were used to predict postoperative delirium in elderly patients. The area under the receiver operating characteristic ( AUC) and diagnostic characteristics of the two predictive models were compared, and the single factor analysis and Logistic regression analysis were performed on 19 predictive factors of the two models to determine the independent influencing factors of postoperative delirium. Results:The AUC for external verification of the PROPDESC and MDP were 0.87 (95% CI: 0.84-0.90) and 0.89 (95% CI: 0.86-0.92) , respectively. The sensitivity of 71.79% and 80.34%, and specificity of 85.16% and 81.12%, respectively. Logistic regression analysis showed that emergency admission, age, sentence repetition and sequence subtraction in Montreal Cognitive Assessment (MoCA) were independent influencing factors for postoperative delirium ( P<0.05) . Conclusions:The predictive ability of PROPDESC and MDP models to predict postoperative delirium in elderly patients is satisfactory. On this basis, delirium risk assessment tools suitable for different surgical elderly populations in China can be constructed.
