Perioperative Neurocognitive Disorders and Putative Biomarkers

Contributed by Phillipe E. Vlisides, MD, Department of Anesthesiology, University of Michigan Medicine, Ann Arbor, MI


Perioperative neurocognitive disorders represent a major public health issue, particularly among aging surgical populations. In fact, the American Society of Anesthesiologists has launched a Brain Health Initiative with the aim of protecting and preserving brain health in older surgical patients.1

Unfortunately, the neurobiological processes underlying perioperative neurocognitive disorders remain incompletely understood. This incomplete pathophysiologic understanding tempers development of novel, evidence-based prevention efforts and therapeutic strategies.

The objective of our study was to test candidate neurophysiological and cerebrovascular biomarkers for their associations with postoperative cognitive outcomes. The neurophysiological biomarkers included preoperative posterior electroencephalographic (EEG) alpha (8 – 12 Hz) oscillatory power, which correlates with neurocognitive recovery after anesthesia and may reflect organization of cortical dynamics for supporting cognition.2

We also tested baseline preoperative frontal-parietal cortical connectivity, as altered connectivity between frontal and parietal cortices has been implicated in postoperative delirium.3 Lastly, as a marker of underlying cerebrovascular disease, we simultaneously tested baseline cerebral oximetry values via near-infrared spectroscopy.4

Study Design

This was a prospective observational study design, with all operations conducted at Michigan Medicine (Ann Arbor, MI USA). Adults ≥18 years of age presenting for major non-cardiac surgery were recruited (n=64). This broad age range enabled neurophysiologic comparisons across the lifespan. A whole-scalp, 16-channel electroencephalography (EEG) system was placed in the preoperative holding unit along with near-infrared spectroscopy cerebral oximetry sensors. This approach allowed simultaneous monitoring of EEG waveforms and cerebral oximetry.

The primary outcome was the National Institutes of Health Cognition Toolbox score, derived as the average of three separate tests: the Flanker Inhibitory Control and Attention Test, List Sorting Working Memory Test, and Pattern Comparison Processing Speed Test. These tests assess attention, working memory, and processing speed, which are all relevant to delirium and related neurocognitive disorders. Delirium was a secondary outcome, as assessed via 3-minute Diagnostic Confusion Assessment Method (3D-CAM). Patient-centered surveys were conducted three months after discharge via paper mail.


Median age of the cohort (n=64) was 59 (interquartile range 48-66) years old, with 36 (56%) males and 28 (44%) females. Participants were predominantly white (n=58, 91%), non-Hispanic, and presented for colorectal, gastrointestinal, hepatobiliary, pancreatic, and urological surgery.

Preoperative baseline attention and processing speed scores were approximately one standard deviation below the U.S. population mean (adjusted for age, sex, race, ethnicity, and level of education). Relative to baseline, mean scores for both working memory and attention were significantly reduced on the first postoperative day but returned to baseline by the second postoperative day. In total, 9/59 (15%) participants from the final cohort experienced at least one episode of delirium.

No significant association was detected between any of the preoperative baseline EEG- or oximetry-based measures and postoperative cognitive outcomes, including both NIH Toolbox scores and delirium. Intraoperatively, EEG cortical connectivity patterns dynamically shifted between states of alpha-dominant frontal-parietal connectivity vs. theta- (4 – 8 Hz) dominant frontal-parietal connectivity. The occurrence of theta-dominant connectivity intraoperatively was associated with postoperative delirium.

No significant associations were observed between EEG- or oximetry-based measures and 3-month patient-centered outcomes. Lastly, a post-hoc analysis was undertaken to identify deficits in cognitive domains during states of delirium (based on positive 3D-CAM screens and contemporaneous NIH Toolbox testing). Based on NIH Toolbox scores, patients who screened positive for delirium demonstrated concurrent reductions in working memory and cognitive processing speed scores.

Conclusions and Future Directions

In summary, neither perioperative cortical connectivity patterns nor baseline cerebral oximetry values were associated with the occurrence of postoperative delirium or postoperative cognitive trajectory. However, intraoperative shifts towards relatively slow-wave cortical connectivity states may reflect an underlying neurocognitive vulnerability that predisposes to delirium.

Given the fluctuating nature of cortical dynamics, a brief snapshot of cortical connectivity patterns may be insufficient to identify the neurophysiologic underpinnings that support cognition. Future studies aiming to identify EEG-based correlates of perioperative neurocognitive disorders may need to include prolonged recording periods, such that comprehensive spatiotemporal shifts in neurophysiologic patterns can be identified and tested.

Lastly, our post-hoc analysis revealed deficits in working memory and processing speed during states of delirium, as identified via 3D-CAM. While these findings should be considered as hypothesis-generating, it is notable that the cognitive functions identified are closely associated with attentional processing,5,6 and inattention is a hallmark feature of delirium. As such, the associations between delirium and working memory and processing speed should be further tested in future prospective studies.


  1. Fleisher LA: Brain Health Initiative: a new ASA patient safety initiative. ASA Monitor 2016; 80: 10-11.
  2. Blain-Moraes S, Tarnal V, Vanini G, et al. Network efficiency and posterior alpha patterns are markers of recovery from general anesthesia: a high-density electroencephalography study in healthy volunteers. Front Hum Neurosci. 2017; 11:328. doi: 10.3389/fnhum.2017.00328
  3. Tanabe S, Mohanty R, Lindroth H, et al. Cohort study into the neural correlates of postoperative delirium: the role of connectivity and slow-wave activity. Br J Anaesth. 2020; 125(1):55-66. doi: 10.1016/j.bja.2020.02.027
  4. Iadecola C, Duering M, Hachinski V, et al. Vascular cognitive impairment and dementia: JACC Scientific Expert Panel. J Am Coll Cardiol. 2019; 73(25):3326-3344. doi: 10.1016/j.jacc.2019.04.034
  5. Lilienthal L, Tamez E, Shelton JT, Myerson J, Hale S. Dual n-back training increases the capacity of the focus of attention. Psychon Bull Rev. 2013; 20:135-41. doi: 10.3758/s13423-012-0335-6
  6. Lu H, Chan SSM, Lam LCW. ‘Two-level’ measurements of processing speed as cognitive markers in the differential diagnosis of dsm-5 mild neurocognitive disorders (NCD). Sci Rep. 2017; 7:521. doi: 10.1038/s41598-017-00624-8

Suggested Citation

Vlisides, Phillipe. Perioperative Neurocognitive Disorders and Putative Biomarkers; March, 2024, Available at: (accessed today’s date)

Posted in Delirium Research, NIDUS Resources.

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