Construction of nomogram prediction model for postoperative delirium in elderly patients with chronic subdural hematoma
10.3760/cma.j.cn115682-20200821-05010
- VernacularTitle:老年慢性硬膜下血肿患者术后谵妄列线图预测模型构建
- Author:
Liyun DU
1
;
Yinan CAO
;
Huiying WU
Author Information
1. 中国医科大学附属盛京医院手术室，沈阳 110004
- Keywords:
Aged;
Delirium;
Chronic subdural hematoma;
Nomogram
- From:
Chinese Journal of Modern Nursing
2021;27(18):2418-2424
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a nomogram prediction model for the risk of postoperative delirium in elderly patients with chronic subdural hematoma.Methods:A total of 450 elderly patients with chronic subdural hematoma who were admitted into Shengjing Hospital of China Medical University from January 2017 to January 2020 were selected as the research objects. The patients were divided into the delirium group ( n=135) and the non-delirium group ( n=315) according to whether they had delirium. The indexes of patients in two groups were compared and analyzed. Univariate analysis and multivariate Logistic regression analysis were used to investigate the independent risk factors for postoperative delirium in elderly patients with chronic subdural hematoma, and a prediction model for the risk of delirium was establish based on independent risk factors. ROC curve and calibration curve were used to evaluate the discriminant ability and predictive effectiveness of the model. Results:In 450 elderly patients with chronic subdural hematoma after surgery, 135 cases of delirium occurred postoperatively, and the incidence of delirium was 30.0%. Univariate analysis showed that there were statistically significant differences in delirium incidence among patients with different ages, alcoholism history, Markwalder grade and postoperative pain grade (χ 2=23.069, 27.325, 36.081, 44.834; P<0.05) . Logistic regression analysis showed that advanced age, preoperative Markwalder grade Ⅳ, history of alcoholism and severe postoperative pain were independent risk factors for postoperative delirium ( P<0.05) . A nomogram prediction model for postoperative delirium risk in elderly patients with chronic subdural hematoma was established based on independent risk factors. The Bootstrap internal verification method proved that the prediction accuracy of the model was good ( C- index was 0.904) , and the area under the ROC curve calculated by the Nomogram model was 0.904. Conclusions:The delirium risk nomogram prediction model constructed in this study has good accuracy, discrimination and good predictive ability. It can improve the screening efficiency for elderly patients with chronic subdural hematoma who are at high risk of developing delirium after surgery.
