Subarachnoid Hemorrhagic Volume: A Biomarker for Prediction of Outcome and Complications
Rohan Sharma1, Fabian Fottinger4, Daniel Mandl4, Saif Salman1, Yujia Wei2, Vishal Patel2, Rabih Tawk3, William Freeman1
1Neurology, 2Radiology, 3Neurosurgery, Mayo Clinic, 4Paracelsus Medical Private University
Objective:
We conducted this study to identify correlation between aneurysmal subarachnoid hemorrhage (aSAH) volume, and other clinical covariates at the time of presentation with outcome and complications.
Background:
Aneurysmal subarachnoid hemorrhage (aSAH) has high rates of mortality and long-term complications. Existing grading and scoring system proposed to predict outcomes for aSAH are of limited utility due to imprecise or semi-quantitative measurements of SAH blood volume and/or unviability to translate into clinical practice.
Design/Methods:
We analyzed 205 patients with aSAH admitted at our Comprehensive Stroke Center (CSC) at Mayo Clinic Florida between 2012 and 2022. We have derived a mathematical model (Model 1) to measure aSAH basal cisterns blood volume using a derivation of the ABC/2 ellipsoid formula, where A = width/thickness, B = length, C = vertical extension) on non-contrast CT which is comparable to manual segmentation (Model 2) on non-contrast CT (NCCT) scans. We used this volumetric data with other clinical covariates including gender, age, intraventricular hemorrhagic volume, intraparenchymal hemorrhagic volume, modified Fisher’s Score, Hunt and Hess score and GCS in a multivariate model to establish correlation with outcome (defined by MRS score), in-hospital, mortality, delayed cerebral ischemia (DCI), need for acute CSF diversion (defined by EVD placement) and chronic mechanical ventilation (defined by tracheostomy placement). Multivariate logistic regression analysis with stepwise elimination of variables not contributing to the model (0.05 significance level for entry into the model) was used for entry into the model, followed by receiver operator characteristics (ROC) curve, and area under curve analysis.
Results:
We found that outcome and mortality were significantly correlated with age, GCS and volume of cisternal SAH. Also, DCI, need for acute CSF diversion and tracheostomy were significantly correlated to GCS and volume of cisternal SAH.
Conclusions:
Cisternal SAH volume is a biomarker that predicts outcome, mortality and complications in patients with aSAH.