Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage

Author:

Bobeff Ernest JanORCID,Bukowiecka-Matusiak MalgorzataORCID,Stawiski Konrad,Wiśniewski KarolORCID,Burzynska-Pedziwiatr IzabelaORCID,Kordzińska Magdalena,Kowalski Konrad,Sendys Przemyslaw,Piotrowski Michał,Szczesna Dorota,Stefańczyk Ludomir,Wozniak Lucyna AlicjaORCID,Jaskólski Dariusz JanORCID

Abstract

Aneurysmal subarachnoid haemorrhages (aSAH) account for 5% of strokes and continues to place a great burden on patients and their families. Cerebral vasospasm (CVS) is one of the main causes of death after aSAH, and is usually diagnosed between day 3 and 14 after bleeding. Its pathogenesis remains poorly understood. To verify whether plasma concentration of amino acids have prognostic value in predicting CVS, we analysed data from 35 patients after aSAH (median age 55 years, IQR 39–62; 20 females, 57.1%), and 37 healthy volunteers (median age 50 years, IQR 38–56; 19 females, 51.4%). Fasting peripheral blood samples were collected on postoperative day one and seven. High performance liquid chromatography-mass spectrometry (HPLC-MS) analysis was performed. The results showed that plasma from patients after aSAH featured a distinctive amino acids concentration which was presented in both principal component analysis and direct comparison. No significant differences were noted between postoperative day one and seven. A total of 18 patients from the study group (51.4%) developed CVS. Hydroxyproline (AUC = 0.7042, 95%CI 0.5259–0.8826, p = 0.0248) and phenylalanine (AUC = 0.6944, 95%CI 0.5119–0.877, p = 0.0368) presented significant CVS prediction potential. Combining the Hunt-Hess Scale and plasma levels of hydroxyproline and phenylalanine provided the model with the best predictive performance and the lowest leave-one-out cross-validation of performance error. Our results suggest that plasma amino acids may improve sensitivity and specificity of Hunt-Hess scale in predicting CVS.

Funder

Ministry of Science and Higher Education

Publisher

MDPI AG

Subject

General Medicine

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