Role of Intraoperative Neurophysiological Monitoring in Preventing Stroke After Cardiac Surgery

Neuroprotective Strategies in Coronary Artery Disease Interventions

Neuroprotective strategies in coronary artery interventions are essential due to the rising number of high-risk patients undergoing procedures like coronary artery bypass grafting (CABG), totally endoscopic coronary artery bypass (TECAB), and hybrid revascularization. In this review article, we summarize the neurological complications associated with coronary artery disease intervention and the risk mitigation strategies. CABG carries significant risks, including ischemic stroke, encephalopathy, seizures, and peripheral nerve injuries. Risk factors include advanced age, hypertension, diabetes, and atherosclerosis. Off-pump CABG minimizes stroke risk by avoiding aortic manipulation and CPB. TECAB and hybrid revascularization have fewer reported neurological complications but still pose risks of stroke and cranial nerve injuries. Pharmacological neuroprotection includes agents such as barbiturates, volatile anesthetics, lidocaine, NMDA receptor antagonists, magnesium, nimodipine, corticosteroids, and aprotinin. Deep hypothermic circulatory arrest (DHCA) is reserved for complex aortic cases requiring a bloodless surgical field. Intraoperative strategies involve cerebral perfusion monitoring, embolic protection devices, and therapeutic hypothermia. Preoperative optimization targets risk factors, arrhythmia prevention, and antiplatelet therapy management. Postoperatively, timely antiplatelet administration, glucose control, hemodynamic stabilization, and cognitive monitoring are critical. Comprehensive neuroprotective approaches, spanning pre- to postoperative phases, aim to reduce neurological complications and enhance outcomes in coronary interventions.

Intraoperative neuromonitoring as an independent predictor for postoperative delirium in ICU following aneurysm clipping

Objectives

This study aims to evaluate the diagnostic accuracy of significant intraoperative neurophysiological monitoring (IONM) changes as an independent predictor of postoperative delirium (POD) in patients undergoing aneurysm clipping.

Methods

IONM and clinical data from 273 patients who underwent craniotomy for aneurysm clipping from 2019 until 2021 were retrospectively reviewed. Significant IONM changes and POD were respectively evaluated based on visual review of data and clinical documentation. POD was assessed multiple times in the ICU using the Intensive Care Delirium Screening Checklist (ICDSC).

Results

Of the 273 patients undergoing craniotomy with IONM, 83 had POD (30.4 %). Significant IONM changes were noted in 42 patients, of which 19 patients had POD (45.2 %). In contrast, 231 patients had no IONM changes during surgery, of which 64 (27.7 %) patients had POD. Multivariable analysis showed that significant IONM changes were associated with POD, OR: 2.09 (95 % CI 1.01-4.43, p-value: 0.046). Additionally, somatosensory evoked potentials (SSEP) changes were significantly associated with POD (p-value: 0.044).

Conclusion

Significant IONM changes are associated with an increased risk of POD in patients undergoing craniotomy for aneurysm clipping. Our findings offer a strong basis for future research and analysis of EEG and SSEP monitoring to detect and possibly prevent POD.

Intraoperative neurophysiologic monitoring during cardiac surgery: an observational cohort study

OBJECTIVE

To evaluate the impact of intraoperative neuromonitoring (IONM) on stroke and operative mortality after coronary and/or valvular operations.

METHODS

This was an observational study of coronary and/or valvular heart operations from 2010 to 2021. Baseline characteristics and postoperative outcomes were compared by the use or non-use of IONM, which included both electroencephalography and somatosensory-evoked potentials. Propensity-score matching was employed to assess the association of IONM usage with operative mortality and stroke.

RESULTS

A total of 19 299 patients underwent a cardiac operation, of which 589 (3.1%) had IONM. Patients with IONM were more likely to have had baseline cerebrovascular disease (60% vs 22%). Patients with IONM had increased operative mortality (5.3% vs 2.5%) and stroke (4.9% vs 1.9%). Moreover, stroke and mortality were highly correlated, with 14% of strokes resulting in death, while only 2% of non-strokes resulted in death (p<0.001). The unadjusted Kaplan-Meier survival estimate was significantly lower among the group with IONM (p<0.001, log-rank). After propensity matching, however, there was no difference in operative mortality or stroke across each group: 3.6% vs 5.3% for mortality and 3.7% vs 5.4% for stroke. In the propensity-matched cohort, the Kaplan-Meier survival estimates were not significantly different across each group (p=0.419, log-rank).

CONCLUSIONS

Adjusting for baseline risk, there was no significant difference in adverse outcomes across each group. IONM may serve as a biomarker of cerebral ischaemia, and empirical adjustments based on changes may provide benefits for neurologic outcomes in high-risk patients. The efficacy of IONM during cardiac surgery should be prospectively validated.

Risk factors and operative risk of large vessel occlusion and stroke during cardiac surgery

OBJECTIVE

Perioperative Large Vessel Occlusions (LVOs) occurring during and following surgery are of immense clinical importance. As such, we aim to present risk factors and test if the Society of Thoracic Surgery (STS) mortality and stroke risk scores can be used to assess operative risk.

METHODS

Using data containing 7 index cardiac operations at a single tertiary referral center from 2010 to 2022, logistic and multivariate regression analysis was performed to identify factors that correlate to higher operative LVO and stroke rate. Odds ratios and confidence intervals were also obtained to test if the STS-Predicted Risk of Mortality (PROM) and -Predicted Risk of Stroke (PROS) scores were positively correlated to operative LVO and stroke rate.

RESULTS

Multivariate modeling showed primary risk factors for an operative LVO were diabetes (OR: 1.727 [95 % CI: 1.060-2.815]), intracranial or extracranial carotid stenosis (OR: 3.661 [95 % CI: 2.126-6.305]), and heart failure as defined by NYHA class (Class 4, OR: 3.951 [95 % CI: 2.092-7.461]; compared to Class 1). As the STS-PROM increased, the relative rate of LVO occurrence increased (very high risk, OR: 6.576 [95 % CI: 2.92-14.812], high risk, OR: 2.667 [1.125-6.322], medium risk, OR: 2.858 [1.594-5.125]; all compared to low risk). STS-PROS quartiles showed a similar relation with LVO risk (quartile 4, OR: 7.768 [95 % CI: 2.740-22.027], quartile 3, OR: 5.249 [1.800-15.306], quartile 2, OR:2.980 [0.960-9.248]; all compared to quartile 1).

CONCLUSIONS

Patients with diabetes, carotid disease and heart failure are at high risk for operative LVO. Both STS-PROM and -PROS can be useful metrics for preoperative measuring of LVO risks.

Surgical Coronary Revascularization in Patients With Underlying Atrial Fibrillation: State-of-the-Art Review

The number of individuals referred for coronary artery bypass grafting (CABG) with preoperative atrial fibrillation (AF) is reported to be 8% to 20%. Atrial fibrillation is a known marker of high-risk patients as it was repeatedly found to negatively influence survival. Therefore, when performing surgical revascularization, consideration should be given to the concomitant treatment of the arrhythmia, the clinical consequences of the arrhythmia itself, and the selection of adequate surgical techniques. This state-of-the-art review aimed to provide a comprehensive analysis of the current understanding of, advancements in, and optimal strategies for CABG in patients with underlying AF. The following topics are considered: stroke prevention, prophylaxis and occurrence of postoperative AF, the role of surgical ablation and left atrial appendage occlusion, and an on-pump vs off-pump strategy. Multiple acute complications can occur in patients with preexisting AF undergoing CABG, each of which can have a significant effect on patient outcomes. Long-term results in these patients and the future perspectives of this scientific area were also addressed. Preoperative arrhythmia should always be considered for surgical ablation because such an approach improves prognosis without increasing perioperative risk. While planning a revascularization strategy, it should be noted that although off-pump coronary artery bypass provides better short-term outcomes, conventional on-pump approach may be beneficial at long-term follow-up. By collecting the current evidence, addressing knowledge gaps, and offering practical recommendations, this state-of-the-art review serves as a valuable resource for clinicians involved in the management of patients with AF undergoing CABG, ultimately contributing to improved outcomes and enhanced patient care.

Role of Intraoperative Neuromonitoring to Predict Postoperative Delirium in Cardiovascular Surgery

OBJECTIVE

Postoperative delirium (POD) can occur in up to 50% of older patients undergoing cardiovascular surgery, resulting in hospitalization and significant morbidity and mortality. This study aimed to determine whether intraoperative neurophysiologic monitoring (IONM) modalities can be used to predict delirium in patients undergoing cardiovascular surgery.

DESIGN

Adult patients undergoing cardiovascular surgery with IONM between 2019 and 2021 were reviewed retrospectively. Delirium was assessed multiple times using the Intensive Care Delirium Screening Checklist (ICDSC). Patients with an ICDSC score ≥4 were considered to have POD. Significant IONM changes were evaluated based on a visual review of electroencephalography (EEG) and somatosensory evoked potentials data and documentation of significant changes during surgery.

SETTING

University of Pittsburgh Medical Center hospitals.

PARTICIPANTS

Patients 18 years old and older undergoing cardiovascular surgery with IONM monitoring.

MEASUREMENTS AND MAIN RESULTS

Of the 578 patients undergoing cardiovascular surgery with IONM, 126 had POD (21.8%). Significant IONM changes were noted in 134 patients, of whom 49 patients had delirium (36.6%). In contrast, 444 patients had no IONM changes during surgery, of whom 77 (17.3%) patients had POD. Upon multivariate analysis, IONM changes were associated with POD (odds ratio 2.12; 95% CI 1.31-3.44; p < 0.001). Additionally, baseline EEG abnormalities were associated with POD (p = 0.002).

CONCLUSION

Significant IONM changes are associated with an increased risk of POD in patients undergoing cardiovascular surgery. These findings offer a basis for future research and analysis of EEG and somatosensory evoked potential monitoring to predict, detect, and prevent POD.

Reliable and fast automatic artifact rejection of Long-Term EEG recordings based on Isolation Forest

Long-term electroencephalogram (Long-Term EEG) has the capacity to monitor over a long period, making it a valuable tool in medical institutions. However, due to the large volume of patient data, selecting clean data segments from raw Long-Term EEG for further analysis is an extremely time-consuming and labor-intensive task. Furthermore, the various actions of patients during recording make it difficult to use algorithms to denoise part of the EEG data, and thus lead to the rejection of these data. Therefore, tools for the quick rejection of heavily corrupted epochs in Long-Term EEG records are highly beneficial. In this paper, a new reliable and fast automatic artifact rejection method for Long-Term EEG based on Isolation Forest (IF) is proposed. Specifically, the IF algorithm is repetitively applied to detect outliers in the EEG data, and the boundary of inliers is promptly adjusted by using a statistical indicator to make the algorithm proceed in an iterative manner. The iteration is terminated when the distance metric between clean epochs and artifact-corrupted epochs remains unchanged. Six statistical indicators (i.e., min, max, median, mean, kurtosis, and skewness) are evaluated by setting them as centroid to adjust the boundary during iteration, and the proposed method is compared with several state-of-the-art methods on a retrospectively collected dataset. The experimental results indicate that utilizing the min value of data as the centroid yields the most optimal performance, and the proposed method is highly efficacious and reliable in the automatic artifact rejection of Long-Term EEG, as it significantly improves the overall data quality. Furthermore, the proposed method surpasses compared methods on most data segments with poor data quality, demonstrating its superior capacity to enhance the data quality of the heavily corrupted data. Besides, owing to the linear time complexity of IF, the proposed method is much faster than other methods, thus providing an advantage when dealing with extensive datasets.