Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage with World Federation of Neurological Societies grade V(OPAS-V)

Abstract BackgroundAneurysmal subarachnoid hemorrhage (aSAH) with World Federation of Neurological Societies (WFNS) grade V has a high mortality rate and poor prognosis. Some patients with WFNS grade V aSAH have had good outcomes after aggressive treatment; however, outcome predictions based on routine examinations and findings obtained at admission are yet to be reported. This study aimed to develop a decision tree model for predicting outcomes of patients with WFNS grade V aSAH to aid decision-making for treatment strategy. MethodsA multicenter study with retrospective and prospective data collected from 201 (derivation cohort) and 12 (validation cohort) patients with WFNS grade V aSAH, respectively, was conducted. Clinical outcomes were divided into good (Modified Rankin Scale [mRS] score at the time of discharge: 0–2) and poor (mRS score: 3–6) outcomes. A decision tree model was developed for the derivation cohort using the classification and regression tree method with clinical data including laboratory findings; it was named OPAS-V (Outcome Prediction in Aneurysmal Subarachnoid hemorrhage with WFNS grade V). The performance of the model was evaluated by area under the curve (AUC) and overall accuracy in both cohorts. ResultsOPAS-V comprised 3 metrics; the percentage of lymphocytes (<49.9% or not), age (>50 yrs or not), and glucose to potassium ratio (≥3.2 or not). The model achieved an AUC of 0.828 (95% confidence interval: 0.712–0.944) and overall accuracy of 0.930. Moreover, the model performed well in the validation cohort with an AUC of 0.700 (95% confidence interval: 0.200–1) and overall accuracy of 0.833. ConclusionsThis study developed the first decision tree model for predicting outcomes of patients with WFNS grade V aSAH, based on simple findings obtained at admission. This may aid clinicians in determining treatment strategies for severe conditions such as WFNS grade V aSAH.