AIMC Topic: Endarterectomy, Carotid

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Predicting Intraoperative Burst Suppression Using Preoperative EEG and Patient Characteristics.

International journal of neural systems Apr 16, 2025
Burst suppression (BS) is an electroencephalogram (EEG) pattern observed in patients undergoing general anesthesia. The occurrence of BS is associated with adverse outcomes such as postoperative delirium, extended recovery time, and increased postope...
Male Middle Aged Aged Aged, 80 and over Humans Electroencephalography Endarterectomy, Carotid Intraoperative Neurophysiological Monitoring Machine Learning Anesthesia, General Female
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Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery Nov 22, 2024
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...
Male Middle Aged Aged Aged, 80 and over Intraoperative Neurophysiological Monitoring Treatment Outcome Risk Assessment Case-Control Studies Retrospective Studies Female Reproducibility of Results Risk Factors Machine Learning Decision Support Techniques Humans Endarterectomy, Carotid Carotid Stenosis Predictive Value of Tests Neurologic Examination Wakefulness
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Advancing Vascular Surgery: The Role Of Artificial Intelligence And Machine Learning In Managing Carotid Stenosis.

Portuguese journal of cardiac thoracic and vascular surgery Oct 12, 2024
INTRODUCTION: Cardiovascular diseases affect 17.7 million people annually, worldwide. Carotid degenerative disease, commonly described as atherosclerotic plaque accumulation, significantly contributes to this, posing a risk for cerebrovascular events...
Machine Learning Risk Assessment Carotid Stenosis Endarterectomy, Carotid Humans Artificial Intelligence
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A Machine Learning Approach for Predicting Early Phase Postoperative Hypertension in Patients Undergoing Carotid Endarterectomy.

Annals of vascular surgery Jul 10, 2020
BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EPOH) requiring the administration of intravenous vasodilators after carotid endarterectomy (CEA).
Cerebrovascular Disorders Databases, Factual Adult Administration, Intravenous Time Factors Male Vasodilator Agents Retrospective Studies Machine Learning Hypertension Aged Cerebrovascular Circulation Decision Support Techniques Female Middle Aged Aged, 80 and over Humans Blood Pressure Risk Factors Risk Assessment Antihypertensive Agents Carotid Stenosis Treatment Outcome Endarterectomy, Carotid Predictive Value of Tests
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