Fong, Tamara G.

Importance Treatment for cognitive dysfunction due to postacute sequelae of long COVID (ie, symptoms of fatigue, malaise, weakness, confusion that persist beyond 12 weeks after an initial COVID infection) remains a significant unmet need. Objective To test evidence-based rehabilitation strategies for improving cognitive symptoms in persons with long COVID. Design, Setting, and Participants This was a 5-arm, multicenter, randomized clinical trial of 3 remotely delivered interventions conducted between August 17, 2023, and June 10, 2024. The study took place at 22 trial sites and included the screening of individuals with cognitive long COVID. Interventions Participants were randomized to 1 of 5 arms: adaptive computerized cognitive training (BrainHQ [Posit Science]), cognitive-behavioral rehabilitation involving both group and individual counseling sessions (PASC-Cognitive Recovery [PASC-CoRE]) paired with BrainHQ, and transcranial direct current stimulation (tDCS) paired with BrainHQ. Two comparator arms were included as follows: unstructured computer puzzles and games (active comparator) and sham tDCS paired with BrainHQ. The interventions occurred 5 times per week over 10 weeks. Main Outcomes and Measures Cognitive and behavioral in-person assessments were performed at baseline, midintervention, at the end of intervention, and 3 months after the end of the intervention. The primary outcome measure was the modified Everyday Cognition Scale 2 (ECog2) completed at the end of the intervention compared to the baseline visit based on participant self-report looking back over the prior 7 days. Results A total of 378 individuals were screened, from which there were 328 participants (median [IQR] age, 48.0 [37.0-58.0] years; 241 female [73.5%]; race: 15 Asian [4.6%], 47 Black [14.3%], and 235 White [71.6%]; ethnicity: 52 Hispanic [15.9%]). None of the 3 active interventions demonstrated benefits on the modified ECog2 in the intention-to-treat population by the end of the intervention period. The adjusted differences in mean change were 0.0 (95% CI, −0.2 to 0.2) for BrainHQ vs active comparator, 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs active comparator, 0.0 (95% CI, −0.2 to 0.2) for tDCS-active + BrainHQ vs tDCS-sham + BrainHQ, and 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs BrainHQ alone. Secondary participant-reported outcomes and neuropsychological tests showed no differential benefits for any treatment arm. All 5 arms demonstrated some improvements over time on the modified ECog2 and on secondary outcomes. There were no serious adverse events attributable to the interventions. Conclusions and Relevance This phase 2 randomized clinical trial failed to demonstrate differential benefits for online cognitive training, a structured cognitive rehabilitation program, and tDCS for cognitive long COVID. Trial Registration ClinicalTrials.gov Identifier: NCT05965739 .

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.