Near-infrared Spectroscopy As a Predictor of Cerebral Ischaemia During Carotid Endarterectomy in Awake Patients

Objectives: The aim of our study was to evaluate the near-infrared spectroscopy monitoring system to detect cerebral ischaemia, find indications for selective shunting during carotid endarterectomy and compare it with an internal carotid artery stump pressure monitoring technique in patients operated under local anaesthesia.

Methods: During January 2015 and November 2018, 131 patients undergoing carotid endarterectomy under local anaesthesia were prospectively included in the study. Near-infrared spectroscopy as intraoperative monitoring was applied and compared with stump pressure.

Results: Carotid endarterectomy was performed successfully in 106 patients operated under local anaesthesia. Meanwhile, 25 patients developed neurological changes (motor or consciousness impairment, weakness of extremities, cognitive decline) during clamping, and all of them received a shunt. ΔrSO, stump pressure and rSO (-11 ± 8%, 31 ± 6mmHg, 58 ± 11) values were smaller in the group of shunted subjects versus non-shunted group subjects (-2 ± 5%, 61 ± 17 mmHg, 64 ± 8) after 1 min of internal carotid artery clamping ( < 0.05). Statistical analysis showed a sensitivity of 90% (95% CI: 0.85-0.95) and a specificity of 70% (95% CI: 0.62-0.78) for a ≥10% drop in ΔrSO to predict ischaemia symptoms during carotid clamping. Using stump pressure with a cut-off value of ≤40 mmHg for predicting symptoms, the sensitivity was 82% and specificity 54%.

Conclusions: Near-infrared spectroscopy is a suitable non-invasive cerebral oxygenation monitoring method during carotid endarterectomy. A 10% decrease of ΔrSO had a good correlation with clinical cerebral ischaemia signs and matched well with the stump pressure cut-off value of ≤40 mmHg. There is a possibility of near-infrared spectroscopy to replace stump pressure in cerebral oxygenation monitoring during carotid endarterectomy. However, we need larger prospective multicentre studies to identify the optimal threshold for shunt requirement.