The Gupta Perioperative Risk for Myocardial Infarct or Cardiac Arrest (MICA) Calculator as an Intraoperative Neurologic Deficit Predictor in Carotid Endarterectomy

Gupta围手术期心肌梗死或心脏骤停风险(MICA)计算器作为颈动脉内膜剥脱术中神经功能缺损的预测指标

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Abstract

BACKGROUND: Patients undergoing carotid endarterectomy (CEA) may experiment intraoperative neurologic deficits (IND) during carotid cross-clamping. This work aimed to assess the impact of the Gupta Perioperative Myocardial Infarct or Cardiac Arrest (MICA) risk calculator in the IND. METHODS: From January 2012 to April 2021, patients undergoing CEA with regional anaesthesia for carotid stenosis with IND and consecutively control operated patients without IND were selected. A regressive predictive model was created, and a receiver operating characteristic (ROC) curve was applied for comparison. A multivariable dependence analysis was conducted using a classification and regression tree (CRT) algorithm. RESULTS: A total of 97 out of 194 included patients developed IND. Obesity showed aOR = 4.01 (95% CI: 1.66-9.67) and MICA score aOR = 1.21 (1.03-1.43). Higher contralateral stenosis showed aOR = 1.29 (1.08-1.53). The AUROC curve was 0.656. The CRT algorithm differentiated obese patients with a MICA score ≥ 8. Regarding non-obese patients, the model identified the presence of contralateral stenosis ≥ 55% with a MICA ≥ 10. CONCLUSION: MICA score might play an additional role in stratifying patients for IND in CEA. Obesity was determined as the best discrimination factor, followed by a score ≥ 8. A higher ipsilateral stenosis degree is suggested to have a part in avoiding procedure-related IND. Larger studies might validate the benefit of MICA score regarding the risk of IND.

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