Investigating how electroencephalogram measures associate with delirium: A systematic review

Neurophysiological patterns reflecting vulnerability to delirium subtypes: a resting-state EEG and event-related potential study

Delirium is a common and acute neurocognitive disorder in older adults associated with increased risk of dementia and death. Understanding the interaction between brain vulnerability and acute stressors is key to delirium pathophysiology, but the neurophysiology of delirium vulnerability is not well defined. This study aimed to identify pre-operative resting-state EEG and event-related potential markers of incident delirium and its subtypes in older adults undergoing elective cardiac procedures. This prospective observational study included 58 older participants (mean age = 75.6 years, SD = 7.1; 46 male/12 female); COVID-19 restrictions limited recruitment. Baseline assessments were conducted in the weeks before elective cardiac procedures and included a 4-min resting-state EEG recording (2-min eyes open and 2-min eyes closed), a 5-min frequency auditory oddball paradigm recording, and cognitive and depression examinations. Periodic peak power, peak frequency and bandwidth measures, and aperiodic offsets and exponents were derived from resting-state EEG data. Event-related potentials were measured as mean component amplitudes (first positive component, first negative component, early third positive component, and mismatch negativity) following standard and deviant auditory stimuli. Incident delirium occurred in 21 participants: 10 hypoactive, 6 mixed, and 5 hyperactive. Incident hyperactive delirium was associated with higher pre-operative eyes open (P = 0.045, d = 1.0) and closed (P = 0.036, d = 1.0) aperiodic offsets. Incident mixed delirium was associated with significantly larger pre-operative first positive component amplitudes to deviants (P = 0.037, d = 1.0) and larger third positive component amplitudes to standards (P = 0.025, d = 1.0) and deviants (P = 0.041, d = 0.9). Other statistically non-significant but moderate-to-large effects were observed in relation to all subtypes. We report evidence of neurophysiological markers of delirium risk weeks prior to elective cardiac procedures in older adults. Despite being underpowered due to COVID-19-related recruitment impacts, these findings indicate pre-operative dysfunction in neural excitation/inhibition balance associated with different delirium subtypes and warrant further investigation on a larger scale.

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study

OBJECTIVES

To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs).

DESIGN

Prospective cross-sectional study.

SETTING

Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals.

PARTICIPANTS

494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious.

MEASUREMENTS

DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets.

METHODS

Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus.

RESULTS

DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity.

CONCLUSIONS

DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

Electroencephalography as a tool for assessing delirium in hospitalized patients: A single-center tertiary hospital experience

Background

Delirium is a prevalent yet underdiagnosed disorder characterized by acute cognitive impairment. Various screening tools are available, including the Confusion Assessment Method (CAM) and 4 A's test (4AT). However, the results of these assessments may vary among raters. Therefore, we investigated the objective use of electroencephalography (EEG) in delirium and its clinical associations and predictive value.

Method

This cross-sectional observational study was conducted at Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan, Malaysia, from April 2021 to April 2023. This study included patients aged ≥18 years with a preliminary diagnosis of delirium. Demographic and clinical data were collected along with EEG recordings evaluated by certified neurologists to classify abnormalities and compare the associated factors between patients with delirium with or without EEG abnormalities.

Results

One hundred and twenty patients were recruited, with 80.0% displaying EEG abnormalities, mostly generalized slowing (moderate to severe) and primarily generalized slowing (mild to severe), and were characterized by theta activity. Age was significantly associated with EEG abnormalities, with patients aged 75 and older demonstrating the highest incidence (88.2%). The CAM scores were strongly correlated with EEG abnormalities (r = 0.639, P < 0.001) and was a predictor of EEG abnormalities (P < 0.012), indicating that EEG can complement clinical assessments for delirium. The Richmond Agitation and Sedation Scale (RASS) scores (r = -0.452, P < 0.001) and Barthel index (BI) (r = -0.582, P < 0.001) were negatively correlated with EEG abnormalities. Additionally, a longer hospitalization duration was associated with EEG abnormalities (r = 0.250, P = 0.006) and emerged as a predictor of such changes (P = 0.030).

Conclusion

EEG abnormalities are prevalent in patients with delirium, particularly in elderly patients. CAM scores and the duration of hospitalization are valuable predictors of EEG abnormalities. EEG can be an objective tool for enhancing delirium diagnosis and prognosis, thereby facilitating timely interventions.

Electroencephalographic Measures of Delirium in the Perioperative Setting: A Systematic Review

Postoperative delirium (POD) is frequent in older adults and is associated with adverse cognitive and functional outcomes. In the last several decades, there has been an increased interest in exploring tools that easily allow the early recognition of patients at risk of developing POD. The electroencephalogram (EEG) is a widely available tool used to understand delirium pathophysiology, and its use in the perioperative setting has grown exponentially, particularly to predict and detect POD. We performed a systematic review to investigate the use of EEG in the pre-, intra-, and postoperative settings. We identified 371 studies, and 56 met the inclusion criteria. A range of techniques was used to obtain EEG data, from limited 1-4 channel setups to complex 256-channel systems. Power spectra were often measured preoperatively, yet the outcomes were inconsistent. During surgery, the emphasis was primarily on burst suppression (BS) metrics and power spectra, with a link between the frequency and timing of BS, and POD. The EEG patterns observed in POD aligned with those noted in delirium in different contexts, suggesting a reduction in EEG activity. Further research is required to investigate preoperative EEG indicators that may predict susceptibility to delirium.

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.

Prevalence of clinical electroencephalography findings in stroke patients with delirium

OBJECTIVE

Delirium is an acute cognitive disorder associated with multiple electroencephalographic (EEG) abnormalities in non-neurological patients, though specific EEG characteristics in patients with stroke remain unclear. We aimed to compare the prevalence of EEG abnormalities in stroke patients during delirium episodes with periods that did not correspond to delirium.

METHODS

We retrospectively analyzed clinical EEG reports for stroke patients who received daily delirium assessments as part of a prospective study. We compared the prevalence of EEG features corresponding to patient-days with vs. without delirium, including focal and generalized slowing, and focal and generalized epileptiform abnormalities (EAs).

RESULTS

Among 58 patients who received EEGs, there were 192 days of both EEG and delirium monitoring (88% [n = 169] corresponding to delirium). Generalized slowing was significantly more prevalent on days with vs. without delirium (96% vs. 57%, p = 0.03), as were bilateral or generalized EAs (38% vs. 13%, p = 0.03). In contrast, focal slowing (53% vs. 74%, p = 0.11) and focal EAs were less prevalent on days with delirium (38% vs. 48%, p = 0.37), though these differences were not statistically significant.

CONCLUSIONS

We found a higher prevalence of generalized but not focal EEG abnormalities in stroke patients with delirium.

SIGNIFICANCE

These findings may reinforce the diffuse nature of delirium-associated encephalopathy, even in patients with discrete structural lesions.

Effect of prolonged sedation with dexmedetomidine, midazolam, propofol, and sevoflurane on sleep homeostasis in rats

BACKGROUND

Sleep disruption is a common occurrence during medical care and is detrimental to patient recovery. Long-term sedation in the critical care setting is a modifiable factor that affects sleep, but the impact of different sedative-hypnotics on sleep homeostasis is not clear.

METHODS

We conducted a systematic comparison of the effects of prolonged sedation (8 h) with i.v. and inhalational agents on sleep homeostasis. Adult Sprague-Dawley rats (n=10) received dexmedetomidine or midazolam on separate days. Another group (n=9) received propofol or sevoflurane on separate days. A third group (n=12) received coadministration of dexmedetomidine and sevoflurane. Wakefulness (wake), slow-wave sleep (SWS), and rapid eye movement (REM) sleep were quantified during the 48-h post-sedation period, during which we also assessed wake-associated neural dynamics using two electroencephalographic measures: theta-high gamma phase-amplitude coupling and high gamma weighted phase-lag index.

RESULTS

Dexmedetomidine-, midazolam-, or propofol-induced sedation increased wake and decreased SWS and REM sleep (P<0.0001) during the 48-h post-sedation period. Sevoflurane produced no change in SWS, decreased wake for 3 h, and increased REM sleep for 6 h (P<0.02) post-sedation. Coadministration of dexmedetomidine and sevoflurane induced no change in wake (P>0.05), increased SWS for 3 h, and decreased REM sleep for 9 h (P<0.02) post-sedation. Dexmedetomidine, midazolam, and coadministration of dexmedetomidine with sevoflurane reduced wake-associated phase-amplitude coupling (P≤0.01). All sedatives except sevoflurane decreased wake-associated high gamma weighted phase-lag index (P<0.01).

CONCLUSIONS

In contrast to i.v. drugs, prolonged sevoflurane sedation produced minimal changes in sleep homeostasis and neural dynamics. Further studies are warranted to assess inhalational agents for long-term sedation and sleep homeostasis.

Differential effects of sevoflurane and desflurane on frontal intraoperative electroencephalogram dynamics associated with postoperative delirium

STUDY OBJECTIVE

Intraoperative electroencephalogram (EEG) patterns associated with postoperative delirium (POD) development have been studied, but the differences in EEG recordings between sevoflurane- and desflurane-induced anesthesia have not been clarified. We aimed to distinguish the EEG characteristics of sevoflurane and desflurane in relation to POD development.

DESIGN AND PATIENTS

We collected frontal four-channel EEG data during the maintenance of anesthesia from 148 elderly patients who received sevoflurane (n = 77) or desflurane (n = 71); 30 patients were diagnosed with delirium postoperatively. The patients were divided into four subgroups based on anesthetics and delirium status: sevoflurane delirium (n = 17), sevoflurane non-delirium (n = 60), desflurane delirium (n = 13), and desflurane non-delirium (n = 58). We compared spectral power, coherence, and pairwise phase consistency (PPC) between sevoflurane and desflurane, and between non-delirium and delirium groups for each anesthetic.

MAIN RESULTS

In patients without POD, the sevoflurane non-delirium group exhibited higher EEG spectral power across 8.5-35 Hz (99.5% CI bootstrap analysis) and higher PPC from alpha to gamma bands (p < 0.005) compared to the desflurane non-delirium group. Conversely, in patients with POD, no significant EEG differences were observed between the sevoflurane and desflurane delirium groups. For the sevoflurane-induced patients, the sevoflurane delirium group had significantly lower power within 7.5-31.5 Hz (99.5% CI bootstrap analysis), reduced coherence over 8.9-23.8 Hz (99.5% CI bootstrap analysis), and lower PPC values in the alpha band (p < 0.005) compared with the sevoflurane non-delirium group. For the desflurane-induced patients, there were no significant differences in the EEG patterns between delirium and non-delirium groups.

CONCLUSIONS

In normal patients without POD, sevoflurane demonstrates a higher power spectrum and prefrontal connectivity than desflurane. Furthermore, reduced frontal alpha power, coherence, and connectivity of intraoperative EEG could be associated with an increased risk of POD. These intraoperative EEG characteristics associated with POD are more noticeable in sevoflurane-induced anesthesia than in desflurane-induced anesthesia.

Acute encephalopathy in the ICU: a practical approach

PURPOSE OF REVIEW

Acute encephalopathy (AE) - which frequently develops in critically ill patients with and without primary brain injury - is defined as an acute process that evolves rapidly and leads to changes in baseline cognitive status, ranging from delirium to coma. The diagnosis, monitoring, and management of AE is challenging. Here, we discuss advances in definitions, diagnostic approaches, therapeutic options, and implications to outcomes of the clinical spectrum of AE in ICU patients without primary brain injury.

RECENT FINDINGS

Understanding and definitions of delirium and coma have evolved. Delirium is a neurocognitive disorder involving impairment of attention and cognition, usually fluctuating, and developing over hours to days. Coma is a state of unresponsiveness, with absence of command following, intelligible speech, or visual pursuit, with no imaging or neurophysiological evidence of cognitive motor dissociation. The CAM-ICU(-7) and the ICDSC are validated, guideline-recommended tools for clinical delirium assessment, with identification of clinical subtypes and stratification of severity. In comatose patients, the roles of continuous EEG monitoring and neuroimaging have grown for the early detection of secondary brain injury and treatment of reversible causes.

SUMMARY

Evidence-based pharmacologic treatments for delirium are limited. Dexmedetomidine is effective for mechanically ventilated patients with delirium, while haloperidol has minimal effect of delirium but may have other benefits. Specific treatments for coma in nonprimary brain injury are still lacking.

Delirium is associated with loss of feedback cortical connectivity

INTRODUCTION

Post-operative delirium (POD) is associated with increased morbidity and mortality but is bereft of treatments, largely due to our limited understanding of the underlying pathophysiology. We hypothesized that delirium reflects a disturbance in cortical connectivity that leads to altered predictions of the sensory environment.

METHODS

High-density electroencephalogram recordings during an oddball auditory roving paradigm were collected from 131 patients. Dynamic causal modeling (DCM) analysis facilitated inference about the neuronal connectivity and inhibition-excitation dynamics underlying auditory-evoked responses.

RESULTS

Mismatch negativity amplitudes were smaller in patients with POD. DCM showed that delirium was associated with decreased left-sided superior temporal gyrus (l-STG) to auditory cortex feedback connectivity. Feedback connectivity also negatively correlated with delirium severity and systemic inflammation. Increased inhibition of l-STG, with consequent decreases in feed-forward and feed-back connectivity, occurred for oddball tones during delirium.

DISCUSSION

Delirium is associated with decreased feedback cortical connectivity, possibly resulting from increased intrinsic inhibitory tone.

HIGHLIGHTS

Mismatch negativity amplitude was reduced in patients with delirium. Patients with postoperative delirium had increased feedforward connectivity before surgery. Feedback connectivity was diminished from left-side superior temporal gyrus to left primary auditory sensory area during delirium. Feedback connectivity inversely correlated with inflammation and delirium severity.

Dementia and Postoperative Delirium in Surgical Hip Fracture Patients: Unveiling Contrasting Risk Factors and Implications

Postoperative delirium is a serious complication, particularly in older adults with hip fractures. Using the 2019 American College of Surgeons National Surgical Quality Improvement Program data file, we performed multiple regression analyses to compare risk factors for postoperative delirium in hip fracture patients with and without dementia. Preoperative delirium and mobility aid use were common risk factors in both groups. However, differential effects were observed for other factors. Pathological fracture increased delirium risk in patients with dementia but had a protective effect in those without dementia. In patients with dementia, American Society of Anesthesiology score IV/V was identified as a risk factor, whereas advanced age, severe chronic obstructive pulmonary disease, weight loss, sepsis, elevated international normalized ratio, and serum creatinine level were additional risk factors in patients without dementia. These findings enhance our understanding of the complex relationship among dementia, hip fractures, and postoperative delirium. Identifying specific risk factors for each group can inform tailored interventions and preventive strategies. Further research is needed to validate and expand these findings, ultimately improving care and outcomes. [Journal of Gerontological Nursing, 49(12), 25-30.].

Electroencephalogram measured functional connectivity for delirium detection: a systematic review

Objective

Delirium is an acute alteration of consciousness marked by confusion, inattention, and changes in cognition. Some speculate that delirium may be a disorder of functional connectivity, but the requirement to lay still may limit measurement with existing functional imaging modalities in this population. Electroencephalography (EEG) may allow for a more feasible approach to the study of potential connectivity disturbances in delirium. We conducted a systematic review to investigate whether there are EEG-measurable differences in brain functional connectivity in the resting state associated with delirium.

Methods

Medline, PubMed, PsychInfo, Embase and CINAHL were searched for relevant articles containing original data studying EEG functional connectivity measures in delirium.

Results

The search yielded 1,516 records. Following strict inclusion criteria, four studies were included in the review. The studies used a variety of EEG measures including phase lag index, coherence, entropy, shortest path length, minimum spanning tree, and network clustering coefficients to study functional connectivity between scalp electrodes. Across connectivity measures, delirium was associated with decreased brain functional connectivity. All four studies found decreased alpha band connectivity for patients with delirium. None of the studies directly compared the different motor subtypes of delirium.

Significance

This systematic review provides converging evidence for disturbances in oscillatory-based functional connectivity in delirium.

Predicting postoperative delirium after cardiovascular surgeries from preoperative portable electroencephalography oscillations

Introduction

Postoperative delirium (POD) is common and life-threatening, however, with intensive interventions, a potentially preventable clinical syndrome. Although electroencephalography (EEG) is a promising biomarker of delirium, standard 20-leads EEG holds difficulties for screening usage in clinical practice.

Objective

We aimed to develop an accurate algorithm to predict POD using EEG data obtained from portable device.

Methods

We recruited 128 patients who underwent scheduled cardiovascular surgery. Cognitive function assessments were conducted, and portable EEG recordings were obtained prior to surgery.

Results

Among the patients, 47 (36.7%) patients with POD were identified and they did not significantly differ from patients without POD in sex ratio, age, cognitive function, or treatment duration of intensive care unit. However, significant differences were observed in the preoperative EEG power spectrum densities at various frequencies, especially gamma activity, between patients with and without POD. POD was successfully predicted using preoperative EEG data with a machine learning algorithm, yielding accuracy of 86% and area under the receiver operating characteristic curve of 0.93.

Discussion

This study provides new insights into the objective and biological vulnerability to delirium. The developed algorithm can be applied in general hospitals without advanced equipment and expertise, thereby enabling the reduction of POD occurrences with intensive interventions for high-risk patients.

Precision-based approaches to delirium in critical illness: A narrative review

Delirium occurs in critical illness and is associated with poor clinical outcomes, having a longstanding impact on survivors. Understanding the complexity of delirium in critical illness and its deleterious outcome has expanded since early reports. Delirium is a culmination of predisposing and precipitating risk factors that result in a transition to delirium. Known risks range from advanced age, frailty, medication exposure or withdrawal, sedation depth, and sepsis. Because of its multifactorial nature, different clinical phenotypes, and potential neurobiological causes, a precise approach to reducing delirium in critical illness requires a broad understanding of its complexity. Refinement in the categorization of delirium subtypes or phenotypes (i.e., psychomotor classifications) requires attention. Recent advances in the association of clinical phenotypes with clinical outcomes expand our understanding and highlight potentially modifiable targets. Several delirium biomarkers in critical care have been examined, with disrupted functional connectivity being precise in detecting delirium. Recent advances reinforce delirium as an acute, and partially modifiable, brain dysfunction, and place emphasis on the importance of mechanistic pathways including cholinergic activity and glucose metabolism. Pharmacologic agents have been assessed in randomized controlled prevention and treatment trials, with a disappointing lack of efficacy. Antipsychotics remain widely used after "negative" trials, yet may have a role in specific subtypes. However, antipsychotics do not appear to improve clinical outcomes. Alpha-2 agonists perhaps hold greater potential for current use and future investigation. The role of thiamine appears promising, yet requires evidence. Looking forward, clinical pharmacists should prioritize the mitigation of predisposing and precipitating risk factors as able. Future research is needed within individual delirium psychomotor subtypes and clinical phenotypes to identify modifiable targets that hold the potential to improve not only delirium duration and severity, but long-term outcomes including cognitive impairment.

A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients

As of 2022, individuals age 65 and older represent approximately 10% of the global population [1], and older adults make up more than one third of anesthesia and surgical cases in developed countries [2, 3]. With approximately > 234 million major surgical procedures performed annually worldwide [4], this suggests that > 70 million surgeries are performed on older adults across the globe each year. The most common postoperative complications seen in these older surgical patients are perioperative neurocognitive disorders including postoperative delirium, which are associated with an increased risk for mortality [5], greater economic burden [6, 7], and greater risk for developing long-term cognitive decline [8] such as Alzheimer's disease and/or related dementias (ADRD). Thus, anesthesia, surgery, and postoperative hospitalization have been viewed as a biological "stress test" for the aging brain, in which postoperative delirium indicates a failed stress test and consequent risk for later cognitive decline (see Fig. 3). Further, it has been hypothesized that interventions that prevent postoperative delirium might reduce the risk of long-term cognitive decline. Recent advances suggest that rather than waiting for the development of postoperative delirium to indicate whether a patient "passed" or "failed" this stress test, the status of the brain can be monitored in real-time via electroencephalography (EEG) in the perioperative period. Beyond the traditional intraoperative use of EEG monitoring for anesthetic titration, perioperative EEG may be a viable tool for identifying waveforms indicative of reduced brain integrity and potential risk for postoperative delirium and long-term cognitive decline. In principle, research incorporating routine perioperative EEG monitoring may provide insight into neuronal patterns of dysfunction associated with risk of postoperative delirium, long-term cognitive decline, or even specific types of aging-related neurodegenerative disease pathology. This research would accelerate our understanding of which waveforms or neuronal patterns necessitate diagnostic workup and intervention in the perioperative period, which could potentially reduce postoperative delirium and/or dementia risk. Thus, here we present recommendations for the use of perioperative EEG as a "predictor" of delirium and perioperative cognitive decline in older surgical patients.

How is depth of anaesthesia assessed in experimental pigs? A scoping review

BACKGROUND

Despite the large number of pigs involved in translational studies, no gold standard depth of anaesthesia indicators are available. We undertook a scoping review to investigate and summarize the evidence that sustains or contradicts the use of depth of anaesthesia indicators in this species.

METHODS

Medline, Embase and CAB abstract were searched up to September 22nd 2022. No limits were set for time, language and study type. Only original articles of in vivo studies using pigs or minipigs undergoing general anaesthesia were included. The depth of anaesthesia indicators reported in the selected papers were divided in two categories: A, indicators purposely investigated as method to assess depth of anaesthesia; B, indicators reported but not investigated as method to assess depth of anaesthesia.

RESULTS

Out of 13792 papers found, 105 were included after the screening process. Category A: 17 depth of anaesthesia indicators were found in 19 papers. Studies were conducted using inhalant anaesthetics as the main anaesthetic agent in the majority of the cases (13/19 = 68.4%), while 3/19 (15.8%) used propofol. The most investigated depth of anaesthesia indicators were bispectral index (8/19 = 42.1%) and spectral edge frequency 95% (5/19 = 26.3%). Contrasting results about the specific usefulness of each depth of anaesthesia indicators were reported. Category B: 23 depth of anaesthesia indicators were found in 92 papers. The most reported depth of anaesthesia indicators were: motor response following a stimulus (37/92 = 40.2%), depth of anaesthesia scores (21/92 = 23.3%), bispectral index (16/92 = 17.8%) and spectral edge frequency 95% (9/92 = 9.8%).

CONCLUSION

Results highlight the lack of scientifically valid and reliable indicators to ensure adequate depth of anaesthesia in pigs.

Postoperative Delirium Severity and Recovery Correlate With Electroencephalogram Spectral Features

BACKGROUND

Delirium is an acute syndrome characterized by inattention, disorganized thinking, and an altered level of consciousness. A reliable biomarker for tracking delirium does not exist, but oscillations in the electroencephalogram (EEG) could address this need. We evaluated whether the frequencies of EEG oscillations are associated with delirium onset, severity, and recovery in the postoperative period.

METHODS

Twenty-six adults enrolled in the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES; ClinicalTrials.gov NCT02241655) study underwent major surgery requiring general anesthesia, and provided longitudinal postoperative EEG recordings for this prespecified substudy. The presence and severity of delirium were evaluated with the confusion assessment method (CAM) or the CAM-intensive care unit. EEG data obtained during awake eyes-open and eyes-closed states yielded relative power in the delta (1-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) bands. Discriminability for delirium presence was evaluated with c-statistics. To account for correlation among repeated measures within patients, mixed-effects models were generated to assess relationships between: (1) delirium severity and EEG relative power (ordinal), and (2) EEG relative power and time (linear). Slopes of ordinal and linear mixed-effects models are reported as the change in delirium severity score/change in EEG relative power, and the change in EEG relative power/time (days), respectively. Bonferroni correction was applied to confidence intervals (CIs) to account for multiple comparisons.

RESULTS

Occipital alpha relative power during eyes-closed states offered moderate discriminability (c-statistic, 0.75; 98% CI, 0.58-0.87), varying inversely with delirium severity (slope, -0.67; 98% CI, -1.36 to -0.01; P = .01) and with severity of inattention (slope, -1.44; 98% CI, -2.30 to -0.58; P = .002). Occipital theta relative power during eyes-open states correlated directly with severity of delirium (slope, 1.28; 98% CI, 0.12-2.44; P = .007), inattention (slope, 2.00; 98% CI, 0.48-3.54; P = .01), and disorganized thinking (slope, 3.15; 98% CI, 0.66-5.65; P = .01). Corresponding frontal EEG measures recapitulated these relationships to varying degrees. Severity of altered level of consciousness correlated with frontal theta relative power during eyes-open states (slope, 11.52; 98% CI, 6.33-16.71; P < .001). Frontal theta relative power during eyes-open states correlated inversely with time (slope, -0.05; 98% CI, -0.12 to -0.04; P = .002).

CONCLUSIONS

Presence, severity, and core features of postoperative delirium covary with spectral features of the EEG. The cost and accessibility of EEG facilitate the translation of these findings to future mechanistic and interventional trials.

The Association between Electroencephalography with Auditory Steady-State Response and Postoperative Delirium

Delirium is a disorder of consciousness and a risk factor for cognitive dysfunction and poor prognosis. We hypothesized that preoperative gamma activities would be linked to postoperative delirium. We enrolled 71 subjects for elective surgery and recorded auditory steady-state response (ASSR) by electroencephalography (EEG) before the surgery and examined postoperative delirium with DSM-5. The EEG data were analyzed for baseline power, and ASSR evoked power (EP) and phase-locking factor (PLF) within the gamma range. Postoperative delirium was found in 18 patients (delirium group) but not in 53 patients (non-delirium group). There were no significant differences in the 40-Hz EP or PLF between the two groups. The baseline gamma activity negatively correlated with the 40-Hz PLF in the non-delirium group (ρ = −0.444, p < 0.01). The correlation between baseline gamma activity and 40-Hz EP was not significant in either the delirium or non-delirium group. In all patients, both preoperative PLF and EP had no significant correlations with the Delirium Rating Scale Revised-98 and the Memorial Delirium Assessment Measure at the post-operation, respectively. The disruption of the neurophysiological relationship between baseline gamma activity before sound stimuli and the PLF of the 40-Hz ASSR may be one of the potential neurophysiological indicators associated with postoperative delirium.

Delusions and Hallucinations Are Associated With Greater Severity of Delirium

BACKGROUND

The 3 core domains of delirium (cognitive, higher level thinking, circadian) do not include the less common noncore psychotic symptoms. However, psychosis might inform about perturbations of neural circuitry, outcomes, or suggest tailored clinical management.

OBJECTIVE

We assessed for the first time the relationships between psychosis and other characteristics of delirium in patients without confounders for delirium phenotype, such as dementia or antipsychotics treatment.

METHODS

Cross-sectional analysis of 366 adults with delirium per the Delirium Rating Scale Revised-98, whose items distinguish hallucinations and delusions from other types of misperceptions and abnormal thought content, assessed during the preceding 24 hours to capture symptom severity fluctuation. The relationship of psychosis with other delirium characteristics was assessed using bivariate comparisons and analysis of variance as appropriate for groups with no psychosis and any psychosis (hallucinations and/or delusions), and subgroups with only hallucinations, only delusions, or both. A discriminant logistic model assessed variables associated with presence of any psychotic features versus none.

RESULTS

Delirium with any psychotic features occurred in 44.5% (163 of 366). Of the 366, 119 (32.5%) had only hallucinations (Hall), 14 (3.8%) had only delusions (Del), and 30 (8.2%) had both (Both). In the psychotic group (n = 163), 73.0% were Hall, 8.6% Del, and 18.4% Both. All psychotic patient groupings had significantly greater delirium severity on the Delirium Rating Scale Revised-98. Delusions and hallucinations were discordant for occurring together. The discriminant model found increased odds of having psychosis as 3 symptom severities increased (visuospatial ability, thought process, and sleep-wake cycle) where these each represented a delirium core domain. The noncore symptom of lability of affect had high odds ratio for psychosis, while motor retardation reduced odds of psychosis in this model.

CONCLUSIONS

Consistent with prior reports, psychosis occurred in less than half of delirious patients with delusions being infrequent, and an association with affective lability was found. We are the first to report that psychotic features are a marker for more severe delirium affecting all core domains. Given that previous functional magnetic resonance imaging research found a correlation between neural network dysconnectivity with greater severity of delirium, psychotic symptoms might be a clinical marker for greater underlying cerebral cortical neural circuitry dysfunction.

How do predisposing factors differ between delirium motor subtypes? A systematic review and meta-analysis

BACKGROUND

Delirium is a common neurocognitive disorder in hospitalised older adults with vast negative consequences. The predominant method of subtyping delirium is by motor activity profile into hypoactive, hyperactive and mixed groups.

OBJECTIVE

This systematic review and meta-analysis investigated how predisposing factors differ between delirium motor subtypes.

METHODS

Databases (Medline, PsycINFO, Embase) were systematically searched for studies reporting predisposing factors (prior to delirium) for delirium motor subtypes. A total of 61 studies met inclusion criteria (N = 14,407, mean age 73.63 years). Random-effects meta-analyses synthesised differences between delirium motor subtypes relative to 22 factors.

RESULTS

Hypoactive cases were older, had poorer cognition and higher physical risk scores than hyperactive cases and were more likely to be women, living in care homes, taking more medications, with worse functional performance and history of cerebrovascular disease than all remaining subtypes. Hyperactive cases were younger than hypoactive and mixed subtypes and were more likely to be men, with better cognition and lower physical risk scores than all other subtypes. Those with no motor subtype (unable to be classified) were more likely to be women and have better functional performance. Effect sizes were small.

CONCLUSIONS

Important differences in those who develop motor subtypes of delirium were shown prior to delirium occurrence. We provide robust quantitative evidence for a common clinical assumption that indices of frailty (institutional living, cognitive and functional impairment) are seen more in hypoactive patients. Motor subtypes should be measured across delirium research. Motor subtyping has great potential to improve the clinical risk assessment and management of delirium.

The inter-relationship between delirium and dementia: the importance of delirium prevention

Delirium and dementia are two frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship. Delirium is an acute confusional state characterized by inattention, cognitive dysfunction and an altered level of consciousness, whereas dementia is an insidious, chronic and progressive loss of a previously acquired cognitive ability. People with dementia have a higher risk of developing delirium than the general population, and the occurrence of delirium is an independent risk factor for subsequent development of dementia. Furthermore, delirium in individuals with dementia can accelerate the trajectory of the underlying cognitive decline. Delirium prevention strategies can reduce the incidence of delirium and associated adverse outcomes, including falls and functional decline. Therefore, delirium might represent a modifiable risk factor for dementia, and interventions that prevent or minimize delirium might also reduce or prevent long-term cognitive impairment. Additionally, understanding the pathophysiology of delirium and the connection between delirium and dementia might ultimately lead to additional treatments for both conditions. In this Review, we explore mechanisms that might be common to both delirium and dementia by reviewing evidence on shared biomarkers, and we discuss the importance of delirium recognition and prevention in people with dementia.

In this Review, Fong and Inouye explore mechanisms that might be common to both delirium and dementia. They present delirium as a possible modifiable risk factor for dementia and discuss the importance of delirium prevention strategies in reducing this risk.

Delirium and dementia are frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship.

Delirium prevention strategies have been shown to reduce not only the incidence of delirium but also the incidence of adverse outcomes associated with delirium such as falls and functional decline.

Adverse outcomes associated with delirium, such as the onset of dementia symptoms in individuals with preclinical dementia, and/or the acceleration of cognitive decline in individuals with dementia might also be delayed by the implementation of delirium prevention strategies.

Evidence regarding the association of systemic inflammatory and neuroinflammatory biomarkers with delirium is variable, possibly as a result of co-occurring dementia pathology or disruption of the blood–brain barrier.

Alzheimer disease pathology, even prior to the onset of symptoms, might have an effect on delirium risk, with potential mechanisms including neuroinflammation and gene–protein interactions with the APOE ε4 allele.

Novel strategies, including proteomics, multi-omics, neuroimaging, transcranial magnetic stimulation and EEG, are beginning to reveal how changes in cerebral blood flow, spectral power and connectivity can be associated with delirium; further work is needed to expand these findings to patients with delirium superimposed upon dementia.

Feasibility and potential of a bedside mini-EEG for diagnosing delirium superimposed on dementia

OBJECTIVE

Delirium superimposed on dementia (DSD) is difficult to diagnose because symptoms of delirium might be interpreted as symptoms of dementia. To improve diagnostic accuracy, we investigated the potential of a brief point-of-care EEG measurement.

METHODS

Thirty older patients were included, all with Major Neurocognitive Disorder (i.e. dementia) according to DSM-5 criteria. EEG was registered at right prefrontal and right temporal site, with eyes either open or closed for three minutes, simultaneously with the Discomfort Scale for Dementia of Alzheimer Type. The Confusion Assessment Method for the Intensive Care Unit was administered to determine the presence of symptoms of a delirium at the time of EEG administration. Video registrations were reviewed independently by two delirium experts.

RESULTS

Higher activities of delta and theta1, and lower activities of theta2, alpha, and beta activity, were found in DSD when compared to dementia only. The ratio of delta and theta power during eyes-open conditions had the highest accuracy (AUC = 0.80 [0.63-0.94]; p <.001) to distinguish DSD from dementia alone. All subjects were on benzodiazepines and half on clozapine, thus the effects of psychotropics on EEG cannot be fully excluded.

CONCLUSIONS

A brief point-of-care EEG at two sites of the head has the potential to aid in the detection of DSD.

SIGNIFICANCE

The diagnostic accuracy of EEG in recognizing or excluding delirium in patients who already have dementia is of large potential given the lack of proper diagnostic tools.

A Cross-Sectional Survey on the Clinical Management of Emergence Delirium in Adults: Knowledge, Attitudes, and Practice in Mainland China

Background: Emergence delirium (ED) occurs immediately after emergence from general anesthesia, which may have adverse consequences. This cross-sectional survey assessed Chinese physicians’ and nurses’ knowledge of, attitudes towards, and practice regarding ED in adults. Methods: Electronic questionnaires were sent to 93 major academic hospitals across mainland China and both attending anesthesiologists and anesthesia nurses were recommended to complete them. Results: A total of 243 anesthesiologists and 213 anesthesia nurses participated in the survey. Most of the participants considered it a very important issue; however, less than one-third of them routinely assessed ED. In terms of screening tools, anesthesiologists preferred the Confusion Assessment Method, while anesthesia nurses reported using multiple screening tools. Divergence also appeared with regard to the necessity of monitoring the depth of anesthesia. Anesthesiologists considered it only necessary in high-risk patients, while the nurses considered that it should be carried out routinely. No unified treatment strategy nor medication was reported for ED treatment during the recovery period. Conclusions: This study illustrated that there are high awareness levels among both Chinese anesthesiologists and anesthesia nurses regarding the importance of ED. However, a specific practice in terms of routine delirium assessment, anesthesia depth monitoring, and a standardized treatment algorithm needs to be implemented to improve ED management.

Using Electroencephalogram Biosignal Changes for Delirium Detection in Intensive Care Units

ABSTRACT

BACKGROUND: Biosignal data acquired during quantitative electroencephalography (QEEG) research may ultimately be used to develop algorithms for more accurate detection of delirium. This study investigates the biosignal changes during delirium states by using the QEEG data of patients in a medical intensive care unit. METHODS: This observational study was conducted between September 2018 and December 2019 at a tertiary hospital in South Korea. Delirium was measured using the Korean version of Confusion Assessment Method for the Intensive Care Unit in intensive care unit patients. Quantitative EEG measurements were recorded for 20 minutes in a natural state without external treatment or stimuli, and QEEG data measured in the centroparietal and parietal regions with eyes open were selected for analysis. Power spectrum analysis with a 5-minute epoch was conducted on the selected 65 cases. RESULTS: QEEG changes in the presence of delirium indicated that alpha, beta, gamma, and spectral edge frequency 50% waves showed significantly lower absolute power spectra than the corresponding findings in the absence of delirium. Brain-mapping results showed that these brain waves were inactivated in delirious states. CONCLUSION: QEEG assessments can potentially detect the changes in the centroparietal and parietal regions of delirium patients. QEEG changes, including lower power spectra of alpha, beta, and gamma waves, and spectral edge frequency 50%, can be successfully used to distinguish delirium from the absence of delirium.

Electroencephalography in delirium assessment: a scoping review

BACKGROUND

Delirium is a common disorder affecting around 31% of patients in the intensive care unit (ICU). Delirium assessment scores such as the Confusion Assessment Method (CAM) are time-consuming, they cannot differentiate between different types of delirium and their etiologies, and they may have low sensitivities in the clinical setting. While today, electroencephalography (EEG) is increasingly being applied to delirious patients in the ICU, a lack of clear cut EEG signs, leads to inconsistent assessments.

METHODS

We therefore conducted a scoping review on EEG findings in delirium. One thousand two hundred thirty-six articles identified through database search on PubMed and Embase were reviewed. Finally, 33 original articles were included in the synthesis.

RESULTS

EEG seems to offer manifold possibilities in diagnosing delirium. All 33 studies showed a certain degree of qualitative or quantitative EEG alterations in delirium. Thus, normal routine (rEEG) and continuous EEG (cEEG) make presence of delirium very unlikely. All 33 studies used different research protocols to at least some extent. These include differences in time points, duration, conditions, and recording methods of EEG, as well as different patient populations, and diagnostic methods for delirium. Thus, a quantitative synthesis and common recommendations are so far elusive.

CONCLUSION

Future studies should compare the different methods of EEG recording and evaluation to identify robust parameters for everyday use. Evidence for quantitative bi-electrode delirium detection based on increased relative delta power and decreased beta power is growing and should be further pursued. Additionally, EEG studies on the evolution of a delirium including patient outcomes are needed.

DelIrium VULnerability in GEriatrics (DIVULGE) study: a protocol for a prospective observational study of electroencephalogram associations with incident postoperative delirium

INTRODUCTION

Delirium is a neurocognitive disorder common in older adults in acute care settings. Those who develop delirium are at an increased risk of dementia, cognitive decline and death. Electroencephalography (EEG) during delirium in older adults is characterised by slowing and reduced functional connectivity, but markers of vulnerability are poorly described. We aim to identify EEG spectral power and event-related potential (ERP) markers of incident delirium in older adults to understand neural mechanisms of delirium vulnerability. Characterising delirium vulnerability will provide substantial theoretical advances and outcomes have the potential to be translated into delirium risk assessment tools.

METHODS AND ANALYSIS

We will record EEG in 90 participants over 65 years of age prior to elective coronary artery bypass grafting (CABG) or transcatheter aortic valve implantation (TAVI). We will record 4-minutes of resting state (eyes open and eyes closed) and a 5-minute frequency auditory oddball paradigm. Outcome measures will include frequency band power, 1/f offset and slope, and ERP amplitude measures. Participants will undergo cognitive and EEG testing before their elective procedures and daily postoperative delirium assessments. Group allocation will be done retrospectively by linking preoperative EEG data according to postoperative delirium status (presence, severity, duration and subtype).

ETHICS AND DISSEMINATION

This study is approved by the Human Research Ethics Committee of the Royal Adelaide Hospital, Central Adelaide Local Health Network and the University of South Australia Human Ethics Committee. Findings will be disseminated through peer-reviewed journal articles and presentations at national and international conferences.

TRIAL REGISTRATION NUMBER

ACTRN12618001114235 and ACTRN12618000799257.

The neuropsychological profile of delirium vulnerability: A systematic review and meta-analysis

Delirium is a common neurocognitive disorder in hospitalised older adults with substantial negative consequences. Impaired global cognition is a well-established delirium risk factor. However, poor performance on attention tests and higher intra-subject variability may be more sensitive delirium risk factors, given the disorder is characterised by a fluctuating course and attentional deficits. We systematically searched databases (Embase, PsycINFO, MEDLINE) and 44 studies satisfied inclusion criteria. Random-effects meta-analysis models showed poor performance in all cognitive domains except perception was significantly associated with incident delirium. Largest effects were for orientation (g=-1.20) and construction and motor performance (g=-0.60). These effects were no longer significant in the subgroup without pre-existing cognitive impairment, where executive functions and verbal functions and language skills were associated with incident delirium. A small, non-significant association between intra-subject variability and incident delirium was found (g=0.42). Cognitive domain specific tests may be quicker and more sensitive predictors of incident delirium. This pattern of neuropsychological findings supports the proposition that vulnerability for delirium manifests as a dysfunction of whole-brain information integration.

Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S)

OBJECTIVES

Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a tool that can help close this diagnostic gap: the Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

DESIGN

Retrospective cohort study.

SETTING

Single-center tertiary academic medical center.

PATIENTS

Three-hundred seventy-three adult patients undergoing electroencephalography to evaluate altered mental status between August 2015 and December 2019.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We developed the E-CAM-S based on a learning-to-rank machine learning model of forehead electroencephalography signals. Clinical delirium severity was assessed using the Confusion Assessment Method Severity (CAM-S). We compared associations of E-CAM-S and CAM-S with hospital length of stay and inhospital mortality. E-CAM-S correlated with clinical CAM-S (R = 0.67; p < 0.0001). For the overall cohort, E-CAM-S and CAM-S were similar in their strength of association with hospital length of stay (correlation = 0.31 vs 0.41, respectively; p = 0.082) and inhospital mortality (area under the curve = 0.77 vs 0.81; p = 0.310). Even when restricted to noncomatose patients, E-CAM-S remained statistically similar to CAM-S in its association with length of stay (correlation = 0.37 vs 0.42, respectively; p = 0.188) and inhospital mortality (area under the curve = 0.83 vs 0.74; p = 0.112). In addition to previously appreciated spectral features, the machine learning framework identified variability in multiple measures over time as important features in electroencephalography-based prediction of delirium severity.

CONCLUSIONS

The E-CAM-S is an automated, physiologic measure of delirium severity that predicts clinical outcomes with a level of performance comparable to conventional interview-based clinical assessment.

Retrospective delirium ascertainment from case notes: a retrospective cohort study

OBJECTIVES

This study sets out to ascertain if recognition of delirium impacts on patient outcomes.

DESIGN

Retrospective cohort study.

SETTING

Unscheduled admissions to acute care trust/secondary care UK hospitals.

PARTICIPANTS

Six hundred and fifty-six older adults aged ≥65 years admitted on 14 September 2018.

MEASUREMENTS

Delirium was ascertained retrospectively from case notes using medical notes. Documented delirium was classified as recognised delirium and retrospectively ascertained delirium was classified as unrecognised delirium.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcome measure: inpatient mortality.

SECONDARY OUTCOME MEASURES

length of stay, discharge destination.

RESULTS

Delirium was present in 21.1% (132/626) of patients at any point during admission. The presence of delirium was associated with increased mortality (HR 2.65, CI 1.40 to 5.01). Recognition of delirium did not significantly impact on outcomes.

CONCLUSIONS

Delirium is associated with adverse outcomes in hospitalised older adults. However, there is insufficient evidence that recognition of delirium affects outcomes. However, delirium recognition presents an opportunity to discuss a person's overall prognosis and discuss this with the patient and their family. Further research is needed to assess the pathophysiology of delirium to enable development of targeted interventions towards improved outcomes in patients with delirium.

Current Challenges in the Recognition and Management of Delirium Superimposed on Dementia

Delirium occurring in a patient with preexisting dementia is referred to as delirium superimposed on dementia (DSD). DSD commonly occurs in older hospitalized patients and is associated with worse outcomes, including higher rates of mortality and institutionalization, compared to inpatients with delirium or dementia alone. This narrative review summarizes the screening, diagnosis, management, and pathophysiology of DSD and concludes by highlighting opportunities for future research. Studies were identified via Medline and PsycINFO keyword search, and handsearching reference lists. Conceptually, DSD could be considered an "acute exacerbation" of dementia precipitated by a noxious insult akin to an acute exacerbation of heart failure or acute on chronic renal failure. However, unlike other organ systems, there are no established biomarkers for delirium, so DSD is diagnosed and monitored clinically. Because cognitive dysfunction is common to both delirium and dementia, the diagnosis of DSD can be challenging. Inattention, altered levels of arousal, and motor dysfunction may help distinguish DSD from dementia alone. An informant history suggestive of an acute change in cognition or alertness should be investigated and managed as delirium until proven otherwise. The key management principles include prevention, identifying and treating the underlying precipitant(s), implementing multicomponent interventions to create an ideal environment for brain recovery, preventing complications, managing distress, and monitoring for resolution. Informing and involving family members or caregivers throughout the patient journey are essential because there is significant prognostic uncertainty, including the risk of persistent cognitive and functional decline following DSD and relapse. Furthermore, informal carers can provide significant assistance in management. Emerging evidence demonstrates that increased exposure to delirium is associated with neuronal injury and worse cognitive outcomes although the mechanisms through which this occurs remain unclear. Given the clinical overlap between delirium and dementia, studying shared pathophysiological pathways may uncover diagnostic tests and is an essential step in therapeutic innovation.

Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using larger sample size and performed topological data analysis to improve the BSEEG method. Data from 274 subjects included in the previous study were analyzed as a 1st cohort. Subjects were enrolled at the University of Iowa Hospitals and Clinics (UIHC) between January 30, 2016, and October 30, 2017. A second cohort with 265 subjects was recruited between January 16, 2019, and August 19, 2019. The BSEEG score was calculated as a power ratio between low frequency to high frequency using our newly developed algorithm. Additionally, Topological data analysis (TDA) score was calculated by applying TDA to our EEG data. The BSEEG score and TDA score were compared between those patients with delirium and without delirium. Among the 274 subjects from the first cohort, 102 were categorized as delirious. Among the 206 subjects from the second cohort, 42 were categorized as delirious. The areas under the curve (AUCs) based on BSEEG score were 0.72 (1st cohort, Fp1-A1), 0.76 (1st cohort, Fp2-A2), and 0.67 (2nd cohort). AUCs from TDA were much higher at 0.82 (1st cohort, Fp1-A1), 0.84 (1st cohort, Fp2-A2), and 0.78 (2nd cohort). When sensitivity was set to be 0.80, the TDA drastically improved specificity to 0.66 (1st cohort, Fp1-A1), 0.72 (1st cohort, Fp2-A2), and 0.62 (2nd cohort), compared to 0.48 (1st cohort, Fp1-A1), 0.54 (1st cohort, Fp2-A2), and 0.46 (2nd cohort) with BSEEG. BSEEG has the potential to detect delirium, and TDA is helpful to improve the performance.