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Development and validation of a nomogram prediction model for delayed cerebral edema after intracerebral hemorrhage
Fuqiang Zhai1, Haidong Gao1, Jixin Shou1
1Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Introduction:
To develop a risk prediction model of delayed cerebral edema after hypertensive cerebral hemorrhage based on serum inflammatory factors and hemodynamics, and to evaluate its clinical application value.
Material And Methods:
Multivariate logistic regression was used to analyze the risk factors of postoperative bleeding and build a nomogram prediction model, and a receiver operating characteristic (ROC) curve and calibration curve were drawn to evaluate the prediction efficiency of the nomogram model, which was verified in the validation set.
Results:
The results of univariate analysis revealed significant differences in interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), macrophage inflammatory protein-1α (MIP-1α), cerebral blood flow (CBF), cerebrovascular reactivity (CVR), high-mobility group Box 1 protein (HMGB1), and C-reactive protein (CRP) between patients with edema and those without edema in training (p < 0.05). Logistic regression analysis showed that IL-6, TNF-α, IL-1β, CBF, CVR, HMGB1 and CRP were independent risk factors for bleeding (p < 0.05). The nomogram model demonstrated good calibration and agreement between prediction and reality in both the training and validation sets (C-index index: 0.792 and 0.799). The results of the Hosmer-Lemeshow test were: χ2 = 16.582, p = 0.035 and χ2 = 7.472, p = 0.487. ROC curve analysis showed that the area under the curve (AUC) for predicting delayed cerebral edema was 0.794 in the training set and 0.796 in the validation set.
Conclusions:
The nomogram prediction model of delayed cerebral edema after hypertensive cerebral hemorrhage based on serum inflammatory factors (IL-6, TNF-α, IL-1β), hemodynamic parameters (CBF, CVR), and other related factors (HMGB1, CRP) was successfully established. The model can effectively predict the risk of delayed cerebral edema in patients with hypertensive cerebral hemorrhage.
