Scoring Model to Predict Functional Outcome in Poor-Grade Aneurysmal Subarachnoid Hemorrhage

Area of Science:

• Neurosurgery
• Neurology
• Critical Care Medicine

Background:

• Poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined by World Federation of Neurosurgical Societies (WFNS) grades IV-V, is associated with high disability and mortality rates.
• Accurate prognostication is crucial for managing these critically ill patients.

Purpose of the Study:

• To develop and validate a novel scoring model for precise outcome prediction in patients with poor-grade aSAH.
• To identify key predictors of poor prognosis in this patient population.

Main Methods:

• A scoring model was developed using multivariate logistic regression analysis on data from 147 poor-grade aSAH patients.
• Risk variables included modified Fisher grade, age, treatment strategy, WFNS grade, delayed cerebral ischemia, hydrocephalus, and cerebral herniation.
• The model was validated using a separate cohort of 68 patients.

Main Results:

• The developed scoring system identified significant predictors of poor prognosis (modified Rankin Scale [mRS] ≥3), including modified Fisher grade >2, age ≥65, conservative treatment, WFNS grade V, delayed cerebral ischemia, shunt-dependent hydrocephalus, and cerebral herniation.
• The model categorized patients into low (0-1 points), intermediate (2-3 points), and high (4-9 points) risk groups, with predicted poor prognosis rates of 11%, 52%, and 87%, respectively.
• The model demonstrated strong predictive accuracy with an area under the curve (AUC) of 0.844 in the derivation cohort and 0.831 in the validation cohort.

Conclusions:

• The newly developed scoring model offers improved prognostication for patients with poor-grade aSAH.
• This tool can assist clinicians in making informed decisions regarding further management and complementary treatments for aSAH patients.