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. 2025 Mar 1;142(3):500-510.
doi: 10.1097/ALN.0000000000005315. Epub 2024 Nov 27.

Intraoperative Frontal Electroencephalogram Alpha Power Is Associated with Postoperative Mortality and Other Adverse Outcomes

Affiliations

Intraoperative Frontal Electroencephalogram Alpha Power Is Associated with Postoperative Mortality and Other Adverse Outcomes

Rory Vu Mather et al. Anesthesiology. .

Abstract

Background: With estimated global postoperative mortality rates at 1% to 4% leading to approximately 3 million to 12 million deaths per year, an urgent need exists for reliable measures of perioperative risk. Existing approaches suffer from poor performance, place a high burden on clinicians to gather data, or do not incorporate intraoperative data. Previous work demonstrated that intraoperative anesthetics induce prefrontal electroencephalogram (EEG) oscillations in the alpha band (8 to 12 Hz) that correlate with postoperative cognitive outcomes.

Methods: The authors analyzed a retrospective cohort of 1,081 patients undergoing surgery with general anesthesia at Massachusetts General Hospital (Boston, Massachusetts) with intraoperative EEG recordings. The association between EEG alpha power and adverse outcomes was characterized using statistical models that were fitted on propensity weighted data. The primary outcome was postoperative mortality, measured from date of surgery to date of death or last follow-up. Secondary outcomes included mortality within prespecified time windows (30 days, 90 days, 180 days, and 1 yr), hospital and postanesthesia care unit lengths of stay, discharge to long-term care, and 30-day hospital readmission.

Results: Alpha power was associated with mortality risk (hazard ratio, 0.92; 95% CI, 0.85 to 0.99; P = 0.039). Within specified time windows, alpha power was associated with 30-day mortality (odds ratio, 0.81; 95% CI, 0.66 to 0.95; P = 0.010), 90-day mortality (odds ratio, 0.68; 95% CI, 0.55 to 0.79; P < 0.001), 180-day mortality (odds ratio, 0.75; 95% CI, 0.66 to 0.83; P < 0.001), and 1-yr mortality (odds ratio, 0.85; 95% CI, 0.79 to 0.91; P < 0.001). Additionally, alpha power was associated with discharge to long-term care (odds ratio, 0.91; 95% CI, 0.86 to 0.96; P < 0.001). We did not find significant associations among alpha power and 30-day readmission and hospital or postanesthesia care unit lengths of stay.

Conclusions: Intraoperative EEG alpha power is independently associated with postoperative mortality and adverse outcomes, suggesting it could represent a broad measure of postoperative physical resilience and provide clinicians with a low-burden, personalized measure of postoperative risk.

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Conflict of interest statement

Dr. Purdon is a cofounder of PASCALL Systems, Inc. (Boston, Massachusetts), a start-up company developing closed-loop physiologic control systems for anesthesiology. The other authors declare no competing interests.

Figures

Fig. 1.
Fig. 1.
Flow diagram of our study population. EEG, electroencephalogram; EHR, electronic health record.
Fig. 2.
Fig. 2.
Distributions of intraoperative anesthetic dosing across our sample population.
Fig. 3.
Fig. 3.
Violin plots of alpha power split by mortality across specified time windows. Each violin plot represents the distribution of alpha power for those who died and survived at 30 days, 3 months, 6 months, and 1 yr after surgery. The black lines represent the median of the distribution. EEG, electroencephalogram.
Fig. 4.
Fig. 4.
Model estimates for primary and secondary outcomes. This forest plot presents the model estimates with CIs for each outcome with electroencephalogram frontal alpha power as the exposure. Hazard ratios (HR) were estimated for time-to-event outcomes (mortality hazards, postanesthesia care unit [PACU] length of stay, and hospital length of stay) and odds ratios (OR) estimated for binary outcomes (mortality within 30 days, 90 days, 180 days, and 1 yr after surgery, discharge to long-term care (LTC), and 30-day hospital readmission). Odds ratios were calculated by exponentiating model coefficients. We computed the HR by exponentiating the coefficients of the Cox proportional hazards models, which are ratios of event occurrence to population baseline rates. Greater hazard rates predict shorter event occurrence times. Secondary outcome CIs were adjusted using the Bonferroni correction for multiple comparisons.

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