Outcome prediction in aneurysmal subarachnoid hemorrhage with world federation of neurological societies grade V (OPAS-V).

Aneurysmal 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.

A multicenter study with retrospective and prospective data collected from 201 (derivation cohort) and 26 (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.

OPAS-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 0.727 (95% confidence interval: 0.441-1) and overall accuracy of 0.885.

This 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.
Cardiovascular diseases
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Authors

Yamada Yamada, Nishida Nishida, Takenaka Takenaka, Yamazaki Yamazaki, Nakagawa Nakagawa, Takagaki Takagaki, Yano Yano, Nakamura Nakamura, Toyota Toyota, Fujinaka Fujinaka, Taki Taki, Fujita Fujita, Kishima Kishima
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