Prediction of Post-Operative Delirium in Older Adults from Preoperative Cognition and Alpha Power from Resting-State EEG.

Postoperative Delirium (POD) is the most common complication following surgery among older adults, and has been consistently associated with increased mortality and morbidity, cognitive decline, and loss of independence, as well as markedly increased health-care costs. The development of new tools to identify individuals at high risk for POD could guide clinical decision-making and enable targeted interventions to potentially decrease delirium incidence and POD-related complications. In this study, we used machine learning techniques to evaluate whether baseline (pre-operative) cognitive function and resting-state electroencephalography could be used to identify patients at risk for POD. Pre-operative resting-state EEGs and the Montreal Cognitive Assessment (MoCA) were collected from 85 patients (age = 73 ± 6.4 years) undergoing elective surgery, 12 of whom subsequently developed POD. The model with the highest f1-score for predicting delirium, a linear-discriminant analysis (LDA) model incorporating MoCA scores and occipital alpha-band EEG features, was subsequently validated in an independent, prospective cohort of 51 older adults (age ≥ 60) undergoing elective surgery, 6 of whom developed POD. The LDA-based model, with a total of 7 features, was able to predict POD with area under the receiver operating characteristic curve, specificity and accuracy all >90%, and sensitivity > 80%, in the validation cohort. Notably, models incorporating both resting-state EEG and MoCA scores outperformed those including either EEG or MoCA alone. While requiring prospective validation in larger cohorts, these results suggest that prediction of POD with high accuracy may be feasible in clinical settings using simple and widely available clinical tools.

Integrated Multi-Omics Analysis of Cerebrospinal Fluid in Postoperative Delirium.

Preoperative risk biomarkers for delirium may aid in identifying high-risk patients and developing intervention therapies, which would minimize the health and economic burden of postoperative delirium. Previous studies have typically used single omics approaches to identify such biomarkers. Preoperative cerebrospinal fluid (CSF) from the Healthier Postoperative Recovery study of adults ≥ 63 years old undergoing elective major orthopedic surgery was used in a matched pair delirium case-no delirium control design. We performed metabolomics and lipidomics, which were combined with our previously reported proteomics results on the same samples. Differential expression, clustering, classification, and systems biology analyses were applied to individual and combined omics datasets. Probabilistic graph models were used to identify an integrated multi-omics interaction network, which included clusters of heterogeneous omics interactions among lipids, metabolites, and proteins. The combined multi-omics signature of 25 molecules attained an AUC of 0.96 [95% CI: 0.85-1.00], showing improvement over individual omics-based classification. We conclude that multi-omics integration of preoperative CSF identifies potential risk markers for delirium and generates new insights into the complex pathways associated with delirium. With future validation, this hypotheses-generating study may serve to build robust biomarkers for delirium and improve our understanding of its pathophysiology.

Why Do We (and Still Do!) Need the National Institute on Aging-50 Years of Innovation.

This Viewpoint discusses the role and benefits of the National Institute on Aging.

Assessing Delirium Severity in Dementia: Item Development and Psychometric Validation for a Delirium Severity Instrument.

PURPOSE: Despite the importance of measuring delirium severity in patients with Alzheimer's disease and related dementias (ADRD), no validated instrument currently exists. Our goal was to generate items for use in such an instrument. METHOD: An interdisciplinary expert panel developed items to assess seven domains and 21 subdomains of delirium severity. Nursing experts provided input on items. RESULTS: Experts achieved consensus on 21 items, including best respondents for each item, and appropriate look-back periods. Nursing experts emphasized the need for educating nursing staff and obtaining information from caregivers. CONCLUSION: Careful, nuanced identification of distinguishing features is key for generating items for measuring delirium severity in persons with ADRD. Once developed, engaging nurses will be essential to facilitate adoption and relevance of the tool. [Journal of Gerontological Nursing, 50(9), 24-30.].

Electroencephalography-Guided Anesthesia and Delirium in Older Adults After Cardiac Surgery: The ENGAGES-Canada Randomized Clinical Trial.

Importance: Intraoperative electroencephalogram (EEG) waveform suppression, suggesting excessive general anesthesia, has been associated with postoperative delirium. Objective: To assess whether EEG-guided anesthesia decreases the incidence of delirium after cardiac surgery. Design, Setting, and Participants: Randomized, parallel-group clinical trial of 1140 adults 60 years or older undergoing cardiac surgery at 4 Canadian hospitals. Recruitment was from December 2016 to February 2022, with follow-up until February 2023. Interventions: Patients were randomized in a 1:1 ratio (stratified by hospital) to receive EEG-guided anesthesia (n = 567) or usual care (n = 573). Patients and those assessing outcomes were blinded to group assignment. Main Outcomes and Measures: The primary outcome was delirium during postoperative days 1 through 5. Intraoperative measures included anesthetic concentration and EEG suppression time. Secondary outcomes included intensive care and hospital length of stay. Serious adverse events included intraoperative awareness, medical complications, and 30-day mortality. Results: Of 1140 randomized patients (median [IQR] age, 70 [65-75] years; 282 [24.7%] women), 1131 (99.2%) were assessed for the primary outcome. Delirium during postoperative days 1 to 5 occurred in 102 of 562 patients (18.15%) in the EEG-guided group and 103 of 569 patients (18.10%) in the usual care group (difference, 0.05% [95% CI, -4.57% to 4.67%]). In the EEG-guided group compared with the usual care group, the median volatile anesthetic minimum alveolar concentration was 0.14 (95% CI, 0.15 to 0.13) lower (0.66 vs 0.80) and there was a 7.7-minute (95% CI, 10.6 to 4.7) decrease in the median total time spent with EEG suppression (4.0 vs 11.7 min). There were no significant differences between groups in median length of intensive care unit (difference, 0 days [95% CI, -0.31 to 0.31]) or hospital stay (difference, 0 days [95% CI, -0.94 to 0.94]). No patients reported intraoperative awareness. Medical complications occurred in 64 of 567 patients (11.3%) in the EEG-guided group and 73 of 573 (12.7%) in the usual care group. Thirty-day mortality occurred in 8 of 567 patients (1.4%) in the EEG-guided group and 13 of 573 (2.3%) in the usual care group. Conclusions and Relevance: Among older adults undergoing cardiac surgery, EEG-guided anesthetic administration to minimize EEG suppression, compared with usual care, did not decrease the incidence of postoperative delirium. This finding does not support EEG-guided anesthesia for this indication. Trial Registration: ClinicalTrials.gov Identifier: NCT02692300.

Relationship between cortical brain atrophy, delirium, and long-term cognitive decline in older surgical patients.

In older patients, delirium after surgery is associated with long-term cognitive decline (LTCD). The neural substrates of this association are unclear. Neurodegenerative changes associated with dementia are possible contributors. We investigated the relationship between brain atrophy rates in Alzheimer's disease (AD) and cognitive aging signature regions from magnetic resonance imaging before and one year after surgery, LTCD assessed by the general cognitive performance (GCP) score over 6 years post-operatively, and delirium in 117 elective surgery patients without dementia (mean age = 76). The annual change in cortical thickness was 0.2(1.7) % (AD-signature p = 0.09) and 0.4(1.7) % (aging-signature p = 0.01). Greater atrophy was associated with LTCD (AD-signature: beta(CI) = 0.24(0.06-0.42) points of GCP/mm of cortical thickness; p < 0.01, aging-signature: beta(CI) = 0.55(0.07-1.03); p = 0.03). Atrophy rates were not significantly different between participants with and without delirium. We found an interaction with delirium severity in the association between atrophy and LTCD (AD-signature: beta(CI) = 0.04(0.00-0.08), p = 0.04; aging-signature: beta(CI) = 0.08(0.03-0.12), p < 0.01). The rate of cortical atrophy and severity of delirium are independent, synergistic factors determining postoperative cognitive decline in the elderly.

Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.

BACKGROUND: Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. OBJECTIVE: To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. METHODS: We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. RESULTS: Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium. CONCLUSIONS: Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.

The Delphi Delirium Management Algorithms. A practical tool for clinicians, the result of a modified Delphi expert consensus approach.

Delirium is common in hospitalised patients, and there is currently no specific treatment. Identifying and treating underlying somatic causes of delirium is the first priority once delirium is diagnosed. Several international guidelines provide clinicians with an evidence-based approach to screening, diagnosis and symptomatic treatment. However, current guidelines do not offer a structured approach to identification of underlying causes. A panel of 37 internationally recognised delirium experts from diverse medical backgrounds worked together in a modified Delphi approach via an online platform. Consensus was reached after five voting rounds. The final product of this project is a set of three delirium management algorithms (the Delirium Delphi Algorithms), one for ward patients, one for patients after cardiac surgery and one for patients in the intensive care unit.

Trajectories of Postoperative Depressive Symptoms in Older Patients Undergoing Major Surgery.

This cohort study examines the trajectories of postoperative depressive symptoms in older patients undergoing major surgery and the differences in patient characteristics between the trajectory groups.

Biomarkers of neurodegeneration and neural injury as potential predictors for delirium.

OBJECTIVES: Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS: In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aß)42 , Aß40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS: Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aß40 and Aß42 . CONCLUSIONS: These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

Optimizing delirium care in the era of Age-Friendly Health System.

Delirium is a significant geriatric condition associated with adverse clinical and economic outcomes. The cause of delirium is usually multifactorial, and person-centered multicomponent approaches for proper delirium management are required. In 2017, the John A. Hartford Foundation and the Institute for Healthcare Improvement (IHI) launched a national initiative, Age-Friendly Health System (AFHS), promoting the use of a framework called 4Ms (what matters, medication, mentation, and mobility). The 4Ms framework's primary goal is to provide comprehensive and practical person-centered care for older adults and it aligns with the core concepts of optimal delirium management. In this special article, we demonstrate how a traditional delirium prevention and management model can be assessed from the perspective of AFHS. An example is the crosswalk with the Hospital Elder Life Program (HELP) Core Interventions and the 4MS, which demonstrates alignment in delirium management. We also introduce useful tools to create an AFHS environment in delirium management. Although much has been written about delirium management, there is a need to identify the critical steps in advancing the overall delirium care in the context of the AFHS. In this article, we suggest future directions, including the need for more prospective and comprehensive research to assess the impact of AFHS on delirium care, the need for more innovative and sustainable education platforms, fundamental changes in the healthcare payment system for proper adoption of AFHS in any healthcare setting, and application of AFHS in the community for continuity of care for older adults with delirium.

Social determinants of health and incident postoperative delirium: Exploring key relationships in the SAGES study.

BACKGROUND: Examining the associations of social determinants of health (SDOH) with postoperative delirium in older adults will broaden our understanding of this potentially devastating condition. We explored the association between SDOH factors and incident postoperative delirium. METHODS: A retrospective study of a prospective cohort of patients enrolled from June 18, 2010, to August 8, 2013, across two academic medical centers in Boston, Massachusetts. Overall, 560 older adults age ≥70 years undergoing major elective non-cardiac surgery were included in this analysis. Exposure variables included income, lack of private insurance, and neighborhood disadvantage. Our main outcome was incident postoperative delirium, measured using the Confusion Assessment Method long form. RESULTS: Older age (odds ratio, OR: 1.01, 95% confidence interval, CI: 1.00, 1.02), income <20,000 a year (OR: 1.12, 95% CI: 1.00, 1.26), lack of private insurance (OR: 1.19, 95% CI: 1.04, 1.38), higher depressive symptomatology (OR: 1.02, 95% CI: 1.01, 1.04), and the Area Deprivation Index (OR: 1.02, 95% CI: 1.01, 1.04) were significantly associated with increased risk of postoperative delirium in bivariable analyses. In a multivariable model, explaining 27% of the variance in postoperative delirium, significant independent variables were older age (OR 1.01, 95% CI 1.00, 1.02), lack of private insurance (OR 1.18, 95% CI 1.02, 1.36), and depressive symptoms (OR 1.02, 95% CI 1.00, 1.03). Household income was no longer a significant independent predictor of delirium in the multivariable model (OR:1.02, 95% CI: 0.90, 1.15). The type of medical insurance significantly mediated the association between household income and incident delirium. CONCLUSIONS: Lack of private insurance, a social determinant of health reflecting socioeconomic status, emerged as a novel and important independent risk factor for delirium. Future efforts should consider targeting SDOH factors to prevent postoperative delirium in older adults.