Quantitative electroencephalography predicts delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a retrospective study.

PURPOSE

Delayed cerebral ischemia (DCI) is a common complication that occurs in aneurysmal subarachnoid hemorrhage (aSAH). This complication can lead to clinical deterioration and poor prognosis. The aim of this study is to explore the risk factors for DCI in aSAH patients in neurological ICU, develop a nomogram including quantitative electroencephalography (qEEG) parameters, and evaluate its performance.

METHODS

We retrospectively analyzed and processed Severe aneurysmal subarachnoid hemorrhage (SaSAH) patients from June 2022 to May 2024 who underwent bedside qEEG monitoring and analyzed the qEEG indices, brain CT, and clinical data of these patients. Logistic multivariate regression analysis was employed to identify the independent risk factors of DCI. A clinical prediction model in the form of a nomogram for DCI was developed using the R programming language and subsequently evaluated for its performance and quality.

RESULTS

A total of 145 patients with SaSAH were included in the analysis, comprising 101 patients in the training set and 44 patients in the validation set. 77 patients (53.10 %) developed DCI. Multivariate regression analysis revealed that GCS, modified Fisher grade, hypothermia, alpha/delta ratio (ADR) and PAV grade were independent risk factors for DCI. The nomogram exhibited excellent discriminative performance in both the training set (AUC = 0.84) and the validation set (AUC = 0.80).

CONCLUSION

Quantitative EEG can predict DCI following SaSAH, the resulting nomogram demonstrated substantial predictive value and may help target therapies to patients at highest risk of secondary brain injury. It needs to be further confirmed in the future by multi-center large sample studies.