Objective. To explore the predictive value of milk fat globule epidermal growth factor 8 (MFG-E8) in the occurrence of delayed cerebral ischemia (DCI) after an aneurysmal subarachnoid hemorrhage (aSAH). Methods. We recruited 32 patients with aSAH as the case group and 24 patients with unruptured aneurysms as the control group. Serum MFG-E8 levels were measured by western blot and enzyme-linked immunosorbent assay. We analyzed the relationship between MFG-E8 levels and the risk of DCI. Results. The levels of serum MFG-E8 in the case group ( mean = 11160.9 pg/mL) were significantly higher than those in the control group ( mean = 3081.0 pg/mL, p < 0.001 ). MFG-E8 levels highly correlated with the World Federation of Neurosurgical Societies (WFNS) and modified Fisher scores ( r = − 0.691 and − 0.767 , respectively, p < 0.001 ). In addition, MFG-E8 levels in patients with DCI ( 5882.7 ± 3162.4 pg/mL) were notably higher than those in patients without DCI ( 15818.2 ± 3771.6 pg/mL, p < 0.001 ). A receiver operating characteristic curve showed that the occurrence of DCI could effectively be predicted by MFG-E8 (area under the curve = 0.976 , 95 % CI = 0.850 – 1.000 ). Kaplan–Meier survival analysis showed a remarkable decrease in the incidence of DCI in case group individuals with high levels of MFG-E8 (≥11160.9 pg/mL, p < 0.001 ). Conclusion. MFG-E8 may be a useful predictive marker for DCI after an aSAH and could be a promising surrogate end point.
Intracranial aneurysm (IA) can cause fatal subarachnoid hemorrhage (SAH) after rupture, and identifying patients with unruptured IAs is essential for reducing SAH fatalities. The epithelial–mesenchymal transition (EMT) may be vital to IA progression. Here, identified key EMT-related genes in aneurysms and their pathogenic mechanisms via bioinformatic analysis. The GSE13353, GSE75436, and GSE54083 datasets from Gene Expression Omnibus were analyzed with limma to identify differentially expressed genes (DEGs) among unruptured aneurysms, ruptured aneurysms, and healthy samples. The results revealed that three EMT-related DEGs (ADIPOQ, WNT11, and CCL21) were shared among all groups. Coexpression modules and hub genes were identified via weighted gene co-expression network analysis, revealing two significant modules (red and green) and 14 EMT-related genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses suggested that cytokine interactions were closely related. Gene set enrichment analysis revealed that unruptured aneurysms were enriched for the terms “inflammatory response” and “vascular endothelial growth”. Protein–protein interaction analysis identified seven key genes, which were evaluated with the GSE54083 dataset to determine their sensitivity and specificity. In the external validation set, we verified the differential expression of seven genes in unruptured aneurysms and normal samples. Together, these findings indicate that FN1, and SPARC may help distinguish normal patients from patients with asymptomatic IAs.
Objectives. Delayed cerebral ischemia (DCI) contributes to poor aneurysm prognosis. Subarachnoid hemorrhage and DCI have irreversible and severe consequences once they occur; therefore, early prediction and prevention are important. We investigated the risk factors for postoperative complications of DCI in patients with aneurysmal subarachnoid hemorrhage (aSAH) requiring mechanical ventilation in intensive care and validated a prediction model. Methods. We retrospectively analyzed patients with aSAH who were treated in a French university hospital neuro-ICU between January 2010 and December 2015. The patients were randomized into a training group (144) and verification groups (60). Nomograms were validated in the training and verification groups, where receiver operating characteristic curve analysis was used to verify model discrimination; calibration curve and Hosmer-Lemeshow test were used to determine model calibration; and decision curve analysis (DCA) was used to verify clinical validity of the model. Results. External ventricular drain (EVD), duration of mechanical ventilation, and treatment were significantly associated in the univariate analysis; EVD and rebleeding were significantly associated with the occurrence of DCI after aSAH. Binary logistic regression was used to select five clinicopathological characteristics to predict the occurrence of DCI in patients with aSAH requiring mechanical ventilation nomograms of the risk of DCI. Area under the curve values for the training and verification groups were 0.768 and 0.246, with Brier scores of 0.166 and 0.163, respectively. Hosmer-Lemeshow calibration test values for the training and verification groups were x 2 = 3.824 ( P = 0.923 ) and x 2 = 10.868 ( P = 0.285 ), respectively. Calibration curves showed good agreement. DCA indicated that the training and verification groups showed large positive returns in the broad risk range of 0-77% and 0-63%, respectively. Conclusions. The predictive model of concurrent DCI in aSAH has theoretical and practical values and can provide individualized treatment options for patients with aSAH who require mechanical ventilation.
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