Neurophysiologic predictors of individual risk for post‐operative delirium after elective surgery

Abstract

Background Post‐surgical delirium is associated with increased morbidity, lasting cognitive decline, and loss of functional independence. Within a conceptual framework that delirium is triggered by stressors when vulnerabilities exist in cerebral connectivity and plasticity, we previously suggested that neurophysiologic measures might identify individuals at risk for post‐surgical delirium. Here we demonstrate the feasibility of the approach and provide preliminary experimental evidence of the predictive value of such neurophysiologic measures for the risk of delirium in older persons undergoing elective surgery. Methods Electroencephalography (EEG) and transcranial magnetic stimulation (TMS) were collected from 23 patients prior to elective surgery. Resting‐state EEG spectral power ratio (SPR) served as a measure of integrity of neural circuits. TMS–EEG metrics of plasticity (TMS‐plasticity) were used as indicators of brain capacity to respond to stressors. Presence or absence of delirium was assessed using the confusion assessment method (CAM). We included individuals with no baseline clinically relevant cognitive impairment (MoCA scores ≥21) in order to focus on subclinical neurophysiological measures. Results In patients with no baseline cognitive impairment (N = 20, age = 72 ± 6), 3 developed post‐surgical delirium (MoCA = 24 ± 2.6) and 17 did not (controls; MoCA = 25 ± 2.4). Patients who developed delirium had pre‐surgical resting‐state EEG power ratios outside the 95% confidence interval of controls, and 2/3 had TMS‐plasticity measures outside the 95% CI of controls. Conclusions Consistent with our proposed conceptual framework, this pilot study suggests that non‐invasive and scalable neurophysiologic measures can identify individuals at risk of post‐operative delirium. Specifically, abnormalities in resting‐state EEG spectral power or TMS‐plasticity may indicate sub‐clinical risk for post‐surgery delirium. Extension and confirmation of these findings in a larger sample is needed to assess the clinical utility of the proposed neurophysiologic markers, and to identify specific connectivity and plasticity targets for therapeutic interventions that might minimize the risk of delirium.

Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex

“…The choice of amplitude quantification method also influenced reliability: peak-to-peak was more reliable than the mean of the absolute value (Fig 3K-N), although both had moderate reliability. Our metric for absolute amplitude, the mean of the absolute values within a time window, is equivalent to the common area-under-the-curve (AUC) metrics of TEP amplitude (7,35,67), except with a normalization for window length. Our method for peak-to-peak calculation, similar to that used in (68), differs from some other approaches that rely on temporal peak detection (e.g.…”

Relationship of Postoperative Serum Neuro-Specific Enolase Levels with Postoperative Delirium Occurring after Microvascular Depression Surgery in Older Patients

“…Several previous studies have suggested predictive indicators of postoperative delirium. Ross et al discovered that abnormalities in resting-state EEG spectral power or TMS plasticity may indicate a subclinical risk for post-surgery delirium [43]. Lin et al collected 740 patients, 83 of whom developed postoperative delirium, and examined preoperative biochemical markers of cerebrospinal fluid, suggesting that the preoperative α-syn protein level in cerebrospinal fluid can be a predictor of postoperative delirium [44].…”

Measuring Consciousness in the Intensive Care Unit

“…Additional applications in future clinical trials include the use of TMS-EEG to predict individualized responses to therapies [69], and to measure subclinical therapeutic responses [70]. It may also be possible for TMS-EEG to predict a patient's risk of delirium [71,72], a common ICU complication.…”