Construction and validation of a risk prediction model for ICU delirium in patients with brain tumor surgery
10.3760/cma.j.cn115682-20220119-00316
- VernacularTitle:脑肿瘤术后患者ICU谵妄风险预测模型的构建及验证
- Author:
Xuemei LI
1
;
Xinqi WANG
;
Li XU
;
Xiaofei YE
;
Weiying ZHANG
Author Information
1. 同济大学医学院，上海 200092
- Keywords:
Intensive Care Units;
Postoperative brain tumor surgery;
ICU delirium;
Risk prediction model
- From:
Chinese Journal of Modern Nursing
2022;28(29):3991-3997
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a risk prediction model for ICU delirium in patients with brain tumor surgery, and to verify the application value of the model in predicting the risk of ICU delirium in patients with brain tumor.Methods:Using the convenient sampling method, a total of 336 postoperative patients with brain tumors who were admitted to Neurosurgery ICU of East Hospital Affiliated to Tongji University from December 2020 to July 2021 were selected as the modeling group. Patients were divided into the delirium group ( n=101) and the non-delirium group ( n=235) according to the occurrence of ICU delirium. The patients were evaluated using Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Richmond Agitation Sedation Score (RASS) . Univariate analysis and binomial logistic regression analysis were used to explore the influencing factors of ICU delirium in patients after brain tumor surgery and to construct a predictive model. The area under receiver operating characteristic curve ( AUC) and Calibration curve were used to evaluate the discrimination and calibration of the model. The model was validated by 1 000 Bootstrap self-sampling methods. According to the same criteria, a total of 144 patients with brain tumors from August to November 2021 were selected as the validation group to verify the model. Results:The predictors that finally entered the model were age ( OR=1.033) , length of stay in neurosurgical ICU ( OR=1.298) , length of operation ( OR=1.006) , use of benzodiazepines ( OR=5.850) , physical restraint ( OR=2.820) , tumor diameter ( OR=1.385) and bilateral brain tumor mass ( OR=3.604) . The prediction model of AUC was 0.935 (95% CI: 0.911-0.960, P<0.01) , the Youden index was 0.747, the sensitivity was 92.1% and the specificity was 82.6%. The internal validation consistency index of the Bootstrap method was 0.916, and the calibration curve fit the ideal curve well. The model validation results showed that the sensitivity was 86.4%, the specificity was 85.0%. Conclusions:The prediction model of delirium risk in ICU patients after brain tumor surgery has good predictive performance, which can provide reference for medical staff to take preventive management measures in the early stage.
