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Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index

BACKGROUND: Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in...

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Detalles Bibliográficos
Autores principales: Lai, Zhi-Chao, Liu, Bao, Chen, Yu, Ni, Leng, Liu, Chang-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4733740/
https://www.ncbi.nlm.nih.gov/pubmed/26063363
http://dx.doi.org/10.4103/0366-6999.158317
Descripción
Sumario:BACKGROUND: Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in blood pressure (BP) after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. METHODS: Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI) was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR]) were compared for predicting CHS occurrence. RESULTS: Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%). The area under the curve (AUC) of receiver operating characteristic: AUC(VBI)= 0.981, 95% confidence interval [CI] 0.949–0.995; AUC(VR)= 0.935, 95% CI 0.890–0.966, P = 0.02. CONCLUSIONS: The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.