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Abstract
Prognosis of patients with high-grade aneurysmal subarachnoid hemorrhage (aSAH) is only insufficiently displayed by current standard prognostic scores. This study aims to evaluate the role of pupil status for mortality prediction and provide improved prognostic models. Anonymized data of 477 aSAH patients admitted to our medical center from November 2010 to August 2018 were retrospectively analyzed. Identification of variables independently predicting in-hospital mortality was performed by multivariable logistic regression analysis. Final regression models included Hunt & Hess scale (H&H), pupil status and age or in a simplified variation only H&H and pupil status, leading to the design of novel H&H-Pupil-Age score (HHPA) and simplified H&H-Pupil score (sHHP), respectively. In an external validation cohort of 402 patients, areas under the receiver operating characteristic curves (AUROC) of HHPA (0.841) and sHHP (0.821) were significantly higher than areas of H&H (0.794; p < 0.001) or World Federation of Neurosurgical Societies (WFNS) scale (0.775; p < 0.01). Accordingly, including information about pupil status improves the predictive performance of prognostic scores for in-hospital mortality in patients with aSAH. HHPA and sHHP allow simple, early and detailed prognosis assessment while predictive performance remained strong in an external validation cohort suggesting adequate generalizability and low interrater variability.
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1 University Medical Center Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany (GRID:grid.13648.38) (ISNI:0000 0001 2180 3484); Stanford University School of Medicine, Institute for Stem Cell Biology and Regenerative Medicine, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
2 University Medical Center Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany (GRID:grid.13648.38) (ISNI:0000 0001 2180 3484)
3 Charité-Universitätsmedizin Berlin, Department of Neurosurgery, Berlin, Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662)
4 University Medical Center Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany (GRID:grid.13648.38) (ISNI:0000 0001 2180 3484); University Medical Center Regensburg, Department of Neurosurgery, Regensburg, Germany (GRID:grid.411941.8) (ISNI:0000 0000 9194 7179)