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The Journal of Cardiovascular Surgery 2015 June;56(3):417-22

Copyright © 2015 EDIZIONI MINERVA MEDICA

language: English

Cross-flow determination by transcranial Doppler predicts clamping ischemia in patients undergoing carotid endarterectomy

Attigah N. 1, Demirel S. 1, Ringleb P. 2, Hinz U. 3, Hyhlik-Dürr A. 1, Böckler D. 1

1 Department of Vascular and Endovascular Surgery, University of Heidelberg, Heidelberg, Germany;
2 Department of Neurology, University of Heidelberg, Heidelberg, Germany
3 Unit of Documentation and Biostatistics, Department of Surgery, University of Heidelberg, Heidelberg, Germany


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AIM: Aim of the paper was to assess the reliability of preoperative cross-flow determination by transcranial Doppler measurement (TCD) to detect clamping ischemia in patients undergoing carotid endarterectomy with selective shunting.
METHODS: Retrospective one-to-one matched-pair analysis of 72 patients undergoing carotid endarterectomy with preoperative TCD scanning. Matching criteria were gender, degree of contralateral stenosis and the type of stenosis (asymptomatic or symptomatic).
RESULTS: Patients in need for a secondary shunt insertion had significantly less cross-flow in preoperative TCD measurement (N.=14; 38.89%) compared to the control group (N.=32; 88.89%: P=0.0001%). The sensitivity of the cross-flow determination to predict clamping ischemia was 88.9%, the specificity 61.1%. The risk of developing a clamping ischemia in the absence of a cross-flow was 12 fold higher (OR: 12.6; 95% CI: 3.7-43.3). The existence of circulatory impairment of the MCA was associated with the presence of a collateral flow in the ACoA (OR 3.21; P=0.0531; likelihood ratio test 0.0481). Other factors like renal insufficiency, the degree of stenosis or the stump pressure showed no association with a cross-flow of the ACoA in a multivariate model.
CONCLUSION: TCD scanning is highly reliable to detect cross-flow prior to carotid surgery and thus helpful to identify patients at risk for clamping ischemia and need for shunting.

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nicolas.attigah@med.uni-heidelberg.de