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Chinese Journal of Behavioral Medicine and Brain Science ; (12): 996-1001, 2022.
Article in Chinese | WPRIM | ID: wpr-956193

ABSTRACT

Objective:To analyze the risk factors for postoperative delirium in patients with glioma, and construct and validate a nomogram prediction model.Methods:A total of 304 glioma surgery patients admitted to the Department of Neurosurgery of Shandong Provincial Hospital from January 2021 to January 2022 were involved in this research. The training set (234 patients) and the validation set (70 patients) were divided according to the leave-out method. Patients in the training set and validation set were divided into delirium and non-delirium groups using the confusion assessment method (CAM) as the criteria.Clinical data of patients in the two study groups in the training set were analyzed.The risk factors for postoperative delirium were clarified by Logistic regression analysis, and an early warning model for postoperative delirium in glioma was established. The calibration curve and ROC curve were used for internal and external validation in the training set and validation set to evaluate the accuracy and discrimination of the prediction model.Results:Multivariate Logistic regression analysis showed that age>60 ( OR=4.089, 95% CI=1.898-9.103, P<0.001), diabetes ( OR=2.825, 95% CI=1.316-6.186, P=0.008), hypertension ( OR=2.176, 95% CI=1.041-4.587, P=0.008), smoking ( OR=2.432, 95% CI=1.063-5.648, P=0.036), history of epileptic seizures ( OR=4.457, 95% CI=1.924-10.689, P=0.001), poor lung function ( OR=2.452, 95% CI=1.132-5.374, P=0.023), visual analog scale (VAS)>7 points ( OR=3.394, 95% CI=1.591-7.456, P=0.002), anxiety or depression ( OR=2.746, 95% CI=1.285-5.976, P=0.010) and operation duration>4 h ( OR=2.731, 95% CI=1.255-6.062, P=0.012) were the independent risk factors of brain glial postoperative delirium.Based on the above risk factors a nomogram nursing early warning model was established.The area under the ROC curve (AUC) of internal verification was 0.852, and AUC of external verification was 0.914. Conclusion:The early-warning model for postoperative delirium in glioma patients can effectively predict the risk of delirium after glioma surgery, and it has certain clinical promotion value.

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