Construction of prediction model for secondary brain injury caused by cerebral hemorrhage
10.3969/j.issn.1009-0754.2025.04.010
- VernacularTitle:脑出血继发性脑损伤预测模型构建
- Author:
Yan LU
1
;
Fan YANG
;
Hui JIN
Author Information
1. 226000 江苏 南通,上海大学附属南通医院(南通市第六人民医院)重症医学科
- Keywords:
Cerebral hemorrhage;
Secondary brain injury;
Influencing factors;
Nomogram;
Prediction model
- From:
Journal of Navy Medicine
2025;46(4):362-367
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the influencing factors of secondary brain injury(SBI)in patients with cerebral hemorrhage,and to build and verify a nomogram prediction model,so as to provide a basis for reducing the occurrence of SBI and improving the prognosis of patients with cerebral hemorrhage.Methods A total of 151 patients with cerebral hemorrhage who were admitted to Affiliated Nantong Hospital of Shanghai University(The Sixth People's Hospital of Nantong)from January 2020 to September 2023 were retrospectively analyzed and randomly assigned(8∶2)to training set(121 cases)and validation set(30 cases).SBI occurred in 46 patients(SBI group,37 in the training set and 9 in the validation set)within 7 days of the onset of cerebral hemorrhage,and the other 105 patients did not suffer from SBI(non-SBI group,84 in the training set and 21 in the validation set).The clinical data of the patients were collected,and the factors affecting the occurrence of SBI were analyzed.A nomogram model was constructed to predict the risk of SBI.The area under the receiver operating characteristic(ROC)curve(AUC)was used to analyze the predictive efficacy of the model for SBI.Results Univariate analysis showed that the proportion of patients aged≥60 years old,bleeding volume≥20 ml,Glasgow coma score<10,and systemic immune-inflammation index(SII)≥952.31×109/L in the SBI group were higher than those in the non-SBI group(all P<0.05).Binary Logistic regression analysis showed that age(OR=4.489,95%CI:2.364-8.521),amount of bleeding(OR=3.804,95%CI:1.693-8.546)and SII level(OR=5.642,95%CI:1.864-17.075)were independent risk factors for SBI(all P<0.05).Bootstrap internal validation of the nomogram prediction model based on the above influencing factors showed that the C-index was 0.841(95%CI:0.792-0.931),and the calibration curve for predicting SBI was close to the ideal curve(P>0.05).The ROC curve of the training set showed that the sensitivity,specificity,and AUC of the nomogram model for predicting the occurrence of SBI was 87.50%,90.50%,and 0.882(95%CI:0.799-0.965),respectively.The ROC curve of the validation set showed that the sensitivity,specificity,and AUC of the nomogram model for predicting the occurrence of SBI were 89.20%,86.90%,and 0.874(95%CI:0.788-0.959),respectively.Conclusion Age,hematoma volume and SII level are independent risk factors for SBI in patients with cerebral hemorrhage.The risk prediction model based on the above factors can effectively evaluate the risk of SBI.
