Inouye, Sharon K.

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.

Objective To develop an individualized method for detecting cognitive adverse events (CAEs) in the context of an ongoing trial of electroconvulsive therapy for refractory agitation and aggression for advanced dementia (ECT-AD study). Methods Literature search aimed at identifying (a) cognitive measures appropriate for patients with advanced dementia, (b) functional scales to use as a proxy for cognitive status in patients with floor effects on baseline cognitive testing, and (c) statistical approaches for defining a CAE, to develop CAEs monitoring plan specifically for the ECT-AD study. Results Using the Severe Impairment Battery-8 (SIB-8), baseline floor effects are defined as a score of ≤5/16. For patients without floor effects, a decline of ≥6 points is considered a CAE. For patients with floor effects, a decline of ≥30 points from baseline on the Barthel Index is considered a CAE. These values were derived using the standard deviation index (SDI) approach to measuring reliable change. Conclusions The proposed plan accounts for practical and statistical challenges in detecting CAEs in patients with advanced dementia. While this protocol was developed in the context of the ECT-AD study, the general approach can potentially be applied to other interventional neuropsychiatric studies that carry the risk of CAEs in patients with advanced dementia.

AbstractBackgroundDelirium and dementia are common causes of cognitive impairment in older adults and frequently co‐exist. Delirium is associated with poor clinical outcomes when comorbid with dementia. Identifying delirium superimposed on dementia (DSD) is clinically challenging given the overlap in symptoms, including inattention, cognitive impairment, and altered level of consciousness, especially in advanced stages of dementia. Recognition of delirium is also critical in ADRD (Alzheimer’s Disease and Related Dementias) clinical trials for both validity and safety reasons. The ECT‐AD study is one such trial investigating the safety and efficacy of electroconvulsive therapy (ECT) for treatment‐refractory agitation and aggression in individuals with advanced ADRD. Herein we review the Confusion Assessment Method (CAM) for identifying delirium in the ECT‐AD study.MethodInclusion criteria for ECT‐AD are hospitalized individuals diagnosed with ADRD (ages 55–89, MMSE ≤ 15) and refractory agitation/aggression, as measured by the Cohen‐Mansfield Agitation Inventory (CMAI). Procedures for detecting baseline and treatment‐emergent delirium involve a 3‐step approach conducted by raters trained in the CAM, which assesses inattention, disorganized thinking, altered levels of consciousness, and fluctuating mental status. Step 1 involves gathering information from nurse informants regarding the patient’s mental status over the past 24 hours. Step 2 involves collecting observational data through informal patient interaction (e.g., brief conversation). Step 3 is an objective assessment of cognitive status using the Severe Impairment Battery – 8 Item (SIB‐8), while also making qualitative observations about delirium features (e.g., level of consciousness). The rater then codes the CAM and determines delirium status based on these 3 steps.ResultOf our 6 consented subjects, 1 experienced delirium detected by the CAM during the Randomization Phase. The subject received three positive CAMs on consecutive treatment days, citing change in mental status, inability to arouse, restlessness, psychomotor agitation, and swearing. ECT/S‐ECT was held each treatment day and the subject was withdrawn from the Randomization Phase.ConclusionIdentifying DSD is challenging due to overlapping symptoms and the fluctuating nature of delirium. The CAM may be useful in this regard by using a multi‐step approach that incorporates observations from reliable informants, direct patient interactions, and structured cognitive assessments.