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Objective: Generalized periodic discharges are a repeated and generalized electroencephalography (EEG) pattern that can be seen in the context of altered mental status. This article describes a series of five individuals with generalized periodic discharges who demonstrated signs and symptoms of catatonia, a treatable neuropsychiatric condition., Methods: Inpatients with a clinical diagnosis of catatonia, determined with the Bush-Francis Catatonia Rating Scale (BFCRS), and EEG recordings with generalized periodic discharges were analyzed in a retrospective case series., Results: Five patients with catatonia and generalized periodic discharges on EEG were evaluated from among 106 patients with catatonia and contemporaneous EEG measurements. Four of these patients showed an improvement in catatonia severity when treated with benzodiazepines, with an average reduction of 6.75 points on the BFCRS., Conclusions: Among patients with generalized periodic discharges, catatonia should be considered, in the appropriate clinical context. Patients with generalized periodic discharges and catatonia may benefit from treatment with empiric trials of benzodiazepines., Competing Interests: Dr. Luccarelli has received funding from Harvard Medical School Dupont Warren Fellowship and Livingston Awards, and he holds equity in Revival Therapeutics. Dr. Smith has received support from Axial and Roche for clinical trial work. Dr. Fricchione has served as a consultant for Revival Therapeutics; he has received royalties from Adya Health; and he has received honoraria or royalties from American Psychiatric Association Publishing, Belvoir Press, Johns Hopkins University Press, and the University of Chicago Press. Dr. Westover is a cofounder of Beacon Biosignals.

Objectives: This study aimed to evaluate whether a measure of subjective cognitive decline (SCD), the Patient-Reported Outcomes Measurement Information System (PROMIS) Applied Cognition-Abilities questionnaire, was associated with postoperative delirium. It was hypothesized that delirium during the surgical hospitalization would be associated with a decrease in subjective cognition up to 6 months after cardiac surgery., Design: This was a secondary analysis of data from the Minimizing Intensive Care Unit Neurological Dysfunction with Dexmedetomidine-induced Sleep randomized, placebo-controlled, parallel-arm superiority trial., Setting: Data from patients recruited between March 2017 and February 2022 at a tertiary medical center in Boston, Massachusetts were analyzed in February 2023., Participants: Data from 337 patients aged 60 years or older who underwent cardiac surgery with cardiopulmonary bypass were included., Interventions: Patients were assessed preoperatively and postoperatively at 30, 90, and 180 days using the subjective PROMIS Applied Cognition-Abilities and telephonic Montreal Cognitive Assessment., Measurement and Main Results: Postoperative delirium occurred within 3 days in 39 participants (11.6%). After adjusting for baseline function, participants who developed postoperative delirium self-reported worse cognitive function (mean difference [MD] -2.64 [95% CI -5.25, -0.04]; p = 0.047) up to 180 days after surgery, as compared with nondelirious patients. This finding was consistent with those obtained from objective t-MoCA assessments (MD -0.77 [95% CI -1.49, -0.04]; p = 0.04)., Conclusions: In this cohort of older patients undergoing cardiac surgery, in-hospital delirium was associated with SCD up to 180 days after surgery. This finding suggested that measures of SCD may enable population-level insights into the burden of cognitive decline associated with postoperative delirium., Competing Interests: Declaration of Competing Interest A.M. reports receiving funding from Roche Diagnostics and the University of Chicago for statistical consulting projects related to biomarkers in preeclampsia. T.T.H. reports receiving personal fees from Anesthesiology and Headache. O.A. is listed as an inventor on brain monitoring patents assigned to Massachusetts General Hospital. No other disclosures were reported., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objectives: Patients hospitalized with stroke develop delirium at higher rates than general hospitalized patients. While several medications are associated with existing delirium, it is unknown whether early medication exposures are associated with subsequent delirium in patients with stroke. Additionally, it is unknown whether delirium identification is associated with changes in the prescription of these medications., Materials and Methods: We conducted a retrospective cohort study of patients admitted to a comprehensive stroke center, who were assessed for delirium by trained nursing staff during clinical care. We analyzed exposures to multiple medication classes in the first 48 h of admission, and compared them between patients who developed delirium >48 hours after admission and those who never developed delirium. Statistical analysis was performed using univariate testing. Multivariable logistic regression was used further to evaluate the significance of univariately significant medications, while controlling for clinical confounders., Results: 1671 unique patients were included in the cohort, of whom 464 (27.8%) developed delirium >48 hours after admission. Delirium was associated with prior exposure to antipsychotics, sedatives, opiates, and antimicrobials. Antipsychotics, sedatives, and antimicrobials remained significantly associated with delirium even after accounting for several clinical covariates. Usage of these medications decreased in the 48 hours following delirium identification, except for atypical antipsychotics, whose use increased. Other medication classes such as steroids, benzodiazepines, and sleep aids were not initially associated with subsequent delirium, but prescription patterns still changed after delirium identification., Conclusions: Early exposure to multiple medication classes is associated with the subsequent development of delirium in patients with stroke. Additionally, prescription patterns changed following delirium identification, suggesting that some of the associated medication classes may represent modifiable targets for future delirium prevention strategies, although future study is needed., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: M. Brandon Westover reports financial support was provided by Glenn Foundation for Medical Research. M. Brandon Westover reports was provided by American Federation for Aging Research. M. Brandon Westover reports financial support was provided by American Academy of Sleep Medicine. M. Brandon Westover reports financial support was provided by National Institutes of Health. M. Brandon Westover reports financial support was provided by National Science Foundation. Eyal Y. Kimchi reports financial support was provided by National Institutes of Health. Sophia L. Ryan reports administrative support and statistical analysis were provided by Harvard University Harvard Catalyst. M. Brandon Westover reports a relationship with Beacon Biosignals, Inc. that includes: equity or stocks. co-author Rachel Renwick previously employed at UCB, after completion of their work on this study., (Copyright © 2023. Published by Elsevier Inc.)

Objective: This study aims to identify blood biomarkers of postoperative delirium., Background: Phosphorylated tau at threonine 217 (Tau-PT217) and 181 (Tau-PT181) are new Alzheimer disease biomarkers. Postoperative delirium is associated with Alzheimer disease. We assessed associations between Tau-PT217 or Tau-PT181 and postoperative delirium., Methods: Of 491 patients (65 years old or older) who had a knee replacement, hip replacement, or laminectomy, 139 participants were eligible and included in the analysis. Presence and severity of postoperative delirium were assessed in the patients. Preoperative plasma concentrations of Tau-PT217 and Tau-PT181 were determined by a newly established Nanoneedle technology., Results: Of 139 participants (73±6 years old, 55% female), 18 (13%) developed postoperative delirium. Participants who developed postoperative delirium had higher preoperative plasma concentrations of Tau-PT217 and Tau-PT181 than participants who did not. Preoperative plasma concentrations of Tau-PT217 or Tau-PT181 were independently associated with postoperative delirium after adjusting for age, education, and preoperative Mini-Mental State score [odds ratio (OR) per unit change in the biomarker: 2.05, 95% confidence interval (CI):1.61-2.62, P <0.001 for Tau-PT217; and OR: 4.12; 95% CI: 2.55--6.67, P <0.001 for Tau-PT181]. The areas under the receiver operating curve for predicting delirium were 0.969 (Tau-PT217) and 0.885 (Tau-PT181). The preoperative plasma concentrations of Tau-PT217 or Tau-PT181 were also associated with delirium severity [beta coefficient (β) per unit change in the biomarker: 0.14; 95% CI: 0.09-0.19, P <0.001 for Tau-PT217; and β: 0.41; 95% CI: 0.12-0.70, P =0.006 for Tau-PT181)., Conclusions: Preoperative plasma concentrations of Tau-PT217 and Tau-PT181 were associated with postoperative delirium, with Tau-PT217 being a stronger indicator of postoperative delirium than Tau-PT181., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Using observational data and variation in hospital admissions across days of the week, we examined the association between ED boarding time and development of delirium within 72 hours of admission among patients aged 65+ years admitted to an inpatient neurology ward. We exploited a natural experiment created by potentially exogenous variation in boarding time across days of the week because of competition for the neurology floor beds. Using proportional hazard models adjusting for socio-demographic and clinical characteristics in a propensity score, we examined the time to delirium onset among 858 patients: 2/3 were admitted for stroke, with the remaining admitted for another acute neurologic event. Among all patients, 81.2% had at least one delirium risk factor in addition to age. All eligible patients received delirium prevention protocols upon admission to the floor and received at least one delirium screening event. While the clinical and social-demographic characteristics of admitted patients were comparable across days of the week, patients with ED arrival on Sunday or Tuesday were more likely to have had delayed floor admission (waiting time greater than 13 hours) and delirium (adjusted HR = 1.54, 95%CI:1.37-1.75). Delayed initiation of delirium prevention protocol appeared to be associated with greater risk of delirium within the initial 72 hours of a hospital admission.

Purpose of Review: Two years of coronavirus disease 2019 (COVID-19) pandemic highlighted that excessive sedation in the ICU leading to coma and other adverse outcomes remains pervasive. There is a need to improve monitoring and management of sedation in mechanically ventilated patients. Remote technologies that are based on automated analysis of electroencephalogram (EEG) could enhance standard care and alert clinicians real-time when severe EEG suppression or other abnormal brain states are detected., Recent Findings: High rates of drug-induced coma as well as delirium were found in several large cohorts of mechanically ventilated patients with COVID-19 pneumonia. In patients with acute respiratory distress syndrome, high doses of sedatives comparable to general anesthesia have been commonly administered without defined EEG endpoints. Continuous limited-channel EEG can reveal pathologic brain states such as burst suppression, that cannot be diagnosed by neurological examination alone. Recent studies documented that machine learning-based analysis of continuous EEG signal is feasible and that this approach can identify burst suppression as well as delirium with high specificity., Summary: Preventing oversedation in the ICU remains a challenge. Continuous monitoring of EEG activity, automated EEG analysis, and generation of alerts to clinicians may reduce drug-induced coma and potentially improve patient outcomes., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

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., Competing Interests: Drs. Kimchi’s and Westover’s institutions received funding from the National Institutes of Health (NIH). Drs. Kimchi and Westover received support for article research from the NIH. Dr. Westover received funding from Beacon Biosignals. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Background: We investigated the effect of delirium burden in mechanically ventilated patients, beginning in the ICU and continuing throughout hospitalization, on functional neurologic outcomes up to 2.5 years following critical illness., Methods: Prospective cohort study of enrolling 178 consecutive mechanically ventilated adult medical and surgical ICU patients between October 2013 and May 2016. Altogether, patients were assessed daily for delirium 2941days using the Confusion Assessment Method for the ICU (CAM-ICU). Hospitalization delirium burden (DB) was quantified as number of hospital days with delirium divided by total days at risk. Survival status up to 2.5 years and neurologic outcomes using the Glasgow Outcome Scale were recorded at discharge 3, 6, and 12 months post-discharge., Results: Of 178 patients, 19 (10.7%) were excluded from outcome analyses due to persistent coma. Among the remaining 159, 123 (77.4%) experienced delirium. DB was independently associated with >4-fold increased mortality at 2.5 years following ICU admission (adjusted hazard ratio [aHR], 4.77; 95% CI, 2.10-10.83; P < .001), and worse neurologic outcome at discharge (adjusted odds ratio [aOR], 0.02; 0.01-0.09; P < .001), 3 (aOR, 0.11; 0.04-0.31; P < .001), 6 (aOR, 0.10; 0.04-0.29; P < .001), and 12 months (aOR, 0.19; 0.07-0.52; P = .001). DB in the ICU alone was not associated with mortality (HR, 1.79; 0.93-3.44; P = .082) and predicted neurologic outcome less strongly than entire hospital stay DB. Similarly, the number of delirium days in the ICU and for whole hospitalization were not associated with mortality (HR, 1.00; 0.93-1.08; P = .917 and HR, 0.98; 0.94-1.03, P = .535) nor with neurological outcomes, except for the association between ICU delirium days and neurological outcome at discharge (OR, 0.90; 0.81-0.99, P = .038)., Conclusions: Delirium burden throughout hospitalization independently predicts long term neurologic outcomes and death up to 2.5 years after critical illness, and is more predictive than delirium burden in the ICU alone and number of delirium days., Competing Interests: The authors have declared that no competing interests exist.

Background: Intraoperative burst-suppression is associated with postoperative delirium. Whether this association is causal remains unclear. Therefore, the authors investigated whether burst-suppression during cardiopulmonary bypass (CPB) mediates the effects of known delirium risk factors on postoperative delirium., Methods: This was a retrospective cohort observational substudy of the Minimizing ICU [intensive care unit] Neurological Dysfunction with Dexmedetomidine-induced Sleep (MINDDS) trial. The authors analyzed data from patients more than 60 yr old undergoing cardiac surgery (n = 159). Univariate and multivariable regression analyses were performed to assess for associations and enable causal inference. Delirium risk factors were evaluated using the abbreviated Montreal Cognitive Assessment and Patient-Reported Outcomes Measurement Information System questionnaires for applied cognition, physical function, global health, sleep, and pain. The authors also analyzed electroencephalogram data (n = 141)., Results: The incidence of delirium in patients with CPB burst-suppression was 25% (15 of 60) compared with 6% (5 of 81) in patients without CPB burst-suppression. In univariate analyses, age (odds ratio, 1.08 [95% CI, 1.03 to 1.14]; P = 0.002), lowest CPB temperature (odds ratio, 0.79 [0.66 to 0.94]; P = 0.010), alpha power (odds ratio, 0.65 [0.54 to 0.80]; P < 0.001), and physical function (odds ratio, 0.95 [0.91 to 0.98]; P = 0.007) were associated with CPB burst-suppression. In separate univariate analyses, age (odds ratio, 1.09 [1.02 to 1.16]; P = 0.009), abbreviated Montreal Cognitive Assessment (odds ratio, 0.80 [0.66 to 0.97]; P = 0.024), alpha power (odds ratio, 0.75 [0.59 to 0.96]; P = 0.025), and CPB burst-suppression (odds ratio, 3.79 [1.5 to 9.6]; P = 0.005) were associated with delirium. However, only physical function (odds ratio, 0.96 [0.91 to 0.99]; P = 0.044), lowest CPB temperature (odds ratio, 0.73 [0.58 to 0.88]; P = 0.003), and electroencephalogram alpha power (odds ratio, 0.61 [0.47 to 0.76]; P < 0.001) were retained as predictors in the burst-suppression multivariable model. Burst-suppression (odds ratio, 4.1 [1.5 to 13.7]; P = 0.012) and age (odds ratio, 1.07 [0.99 to 1.15]; P = 0.090) were retained as predictors in the delirium multivariable model. Delirium was associated with decreased electroencephalogram power from 6.8 to 24.4 Hertz., Conclusions: The inference from the present study is that CPB burst-suppression mediates the effects of physical function, lowest CPB temperature, and electroencephalogram alpha power on delirium.

Objective: To determine which findings on routine clinical EEGs correlate with delirium severity across various presentations and to determine whether EEG findings independently predict important clinical outcomes., Methods: We prospectively studied a cohort of nonintubated inpatients undergoing EEG for evaluation of altered mental status. Patients were assessed for delirium within 1 hour of EEG with the 3-Minute Diagnostic Interview for Confusion Assessment Method (3D-CAM) and 3D-CAM severity score. EEGs were interpreted clinically by neurophysiologists, and reports were reviewed to identify features such as theta or delta slowing and triphasic waves. Generalized linear models were used to quantify associations among EEG findings, delirium, and clinical outcomes, including length of stay, Glasgow Outcome Scale scores, and mortality., Results: We evaluated 200 patients (median age 60 years, IQR 48.5-72 years); 121 (60.5%) met delirium criteria. The EEG finding most strongly associated with delirium presence was a composite of generalized theta or delta slowing (odds ratio 10.3, 95% confidence interval 5.3-20.1). The prevalence of slowing correlated not only with overall delirium severity ( R = 0.907) but also with the severity of each feature assessed by CAM-based delirium algorithms. Slowing was common in delirium even with normal arousal. EEG slowing was associated with longer hospitalizations, worse functional outcomes, and increased mortality, even after adjustment for delirium presence or severity.2 = 0.907) but also with the severity of each feature assessed by CAM-based delirium algorithms. Slowing was common in delirium even with normal arousal. EEG slowing was associated with longer hospitalizations, worse functional outcomes, and increased mortality, even after adjustment for delirium presence or severity., Conclusions: Generalized slowing on routine clinical EEG strongly correlates with delirium and may be a valuable biomarker for delirium severity. In addition, generalized EEG slowing should trigger elevated concern for the prognosis of patients with altered mental status., (© 2019 American Academy of Neurology.)

Objectives: Basic science and clinical studies suggest that sleep disturbance may be a modifiable risk factor for postoperative delirium. We aimed to assess the association between preoperative sleep disturbance and postoperative delirium., Data Sources: We searched PubMed, Embase, CINAHL, Web of Science, and Cochrane from inception until May 31, 2017., Study Selection: We performed a systematic search of the literature for all studies that reported on sleep disruption and postoperative delirium excluding cross-sectional studies, case reports, and studies not reported in English language., Data Extraction: Two authors independently performed study selection and data extraction. We calculated pooled effects estimates with a random-effects model constructed in Stata and evaluated the risk of bias by formal testing (Stata Corp V.14, College Station, TX), DATA SYNTHESIS:: We included 12 studies, from 1,238 citations that met our inclusion criteria. The pooled odds ratio for the association between sleep disturbance and postoperative delirium was 5.24 (95% CI, 3.61-7.60; p < 0.001 and I = 0.0%; p = 0.76). The pooled risk ratio for the association between sleep disturbance and postoperative delirium in prospective studies (n = 6) was 2.90 (95% CI, 2.28-3.69; p < 0.001 and I = 0.0%; p = 0.89). The odds ratio associated with obstructive sleep apnea and unspecified types of sleep disorder were 4.75 (95% CI, 2.65-8.54; p < 0.001 and I = 0.0%; p = 0.85) and 5.60 (95% CI, 3.46-9.07; p < 0.001 and I = 0.0%; p = 0.41), respectively. We performed Begg's and Egger's tests for publication bias and confirmed a null result for publication bias (p = 0.371 and 0.103, respectively)., Conclusions: Preexisting sleep disturbances are likely associated with postoperative delirium. Whether system-level initiatives targeting patients with preoperative sleep disturbance may help reduce the prevalence, morbidity, and healthcare costs associated with postoperative delirium remains to be determined.

Introduction: Delirium, which is prevalent in postcardiac surgical patients, is an acute brain dysfunction characterised by disturbances in attention, awareness and cognition not explained by a pre-existing neurocognitive disorder. The pathophysiology of delirium remains poorly understood. However, basic science and clinical studies suggest that sleep disturbance may be a modifiable risk factor for the development of delirium. Dexmedetomidine is a α-2A adrenergic receptor agonist medication that patterns the activity of various arousal nuclei similar to sleep. A single night-time loading dose of dexmedetomidine promotes non-rapid eye movement sleep stages N2 and N3 sleep. This trial hypothesises dexmedetomidine-induced sleep as pre-emptive therapy for postoperative delirium., Methods and Analysis: The MINDDS (Minimizing ICU Neurological Dysfunction with Dexmedetomidine-induced Sleep) trial is a 370-patient block-randomised, placebo-controlled, double-blinded, single-site, parallel-arm superiority trial. Patients over 60 years old, undergoing cardiac surgery with planned cardiopulmonary bypass, will be randomised to receive a sleep-inducing dose of dexmedetomidine or placebo. The primary outcome is the incidence of delirium on postoperative day 1, assessed with the Confusion Assessment Method by staff blinded to the treatment assignment. To ensure that the study is appropriately powered for the primary outcome measure, patients will be recruited and randomised into the study until 370 patients receive the study intervention on postoperative day 0. Secondary outcomes will be evaluated by in-person assessments and medical record review for in-hospital end points, and by telephone interview for 30-day, 90-day and 180-day end points. All trial outcomes will be evaluated using an intention-to-treat analysis plan. Hypothesis testing will be performed using a two-sided significance level (type I error) of α=0.05. Sensitivity analyses using the actual treatment received will be performed and compared with the intention-to-treat analysis results. Additional sensitivity analyses will assess the potential impact of missing data due to loss of follow-up., Ethics and Dissemination: The Partners Human Research Committee approved the MINDDS trial. Recruitment began in March 2017. Dissemination plans include presentations at scientific conferences, scientific publications and popular media., Trial Registration Number: NCT02856594., Competing Interests: Competing interests: OA and ENB have a provisional patent application describing the use of alpha-2 agonists for promoting N3 sleep., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)