Randomized Study to Evaluate Strategies to Address Cognitive Fog in Long-COVID-19 Patients
Phase: PHASE4
Conditions: Cognitive Impairment, Long COVID
Sponsor: Eva Szigethy

Project Title: Randomized Study to Evaluate Strategies to Address Cognitive Fog in Long-COVID Patients 
NCT 05597722 
5/7/24 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Applicant’s first name: Eva 
Applicant’s Last name: Szigethy  
Applicant’s Professional Title: Professor of Psychiatry Pediatrics and Medicine 
Applicant’s Business Unit/Facility: 
List of additional investigators: Dr. Alison Morris (Pulmonology &Critical Care), Dr. Bryan McVerry 
(Pulmonology & Critical Care), Dr. Michael Collins (Sports Medicine Concussion Program) 
Name of person endorsing the project:  Dr. Donald Yealy 
Project Title: Randomized Study to Evaluate Strategies to Address Cognitive Fog in Long-COVID Patients 
Project Summary  
The multi-disciplinary UPMC Post-COVID Recovery clinic serves the clinical needs of Long-COVID 
patients, those with persistent symptoms after initial infection recovery. Using an IRB-approved 
research registry collecting biomarkers, clinical data, imaging results and patient-reported outcomes 
(PROs), this group defines burden of long-COVID and guides personalized medicine strategies.  
 
To date, phenotyping of 148 Long-COVID patients show 86% with new onset cognitive fog (using 
validated criteria) and 48% with depression (PHQ8 criteria). Cognitive fog was the most common 
complaint endorsed by patients during their clinic evaluations. Additionally, a subgroup of patients 
requesting a behavioral evaluation, who were in the prime of their adult productivity, reported that 
“cognitive fog” was the main symptom impacting their functioning, work performance, and life 
satisfaction; making it a critical domain to target clinically.  The specific cognitive deficits reported as 
part of this “fog” varied across patients.   
 
In a pilot study, we prescribed 90 of these depressed patients a coached digital cognitive behavioral 
therapy (dCBT) app developed by UPMC called RxWell, as part of care. Half of the patients (N = 45) 
downloaded the app and the 75% who completed techniques showed improvement in depression over 
3 months (large effect size of change with PHQ8 (delta 6; p=0.001; Cohen’s d=1.1; mean age 46)).  
 
We posit rapid, accurate, and scalable assessment of cognitive impairment and implementation of the 
right interventions targeting specific deficits is a better fuller recovery path for these patients. This 
proposal evaluates the utility of computer-based evaluation of COVID-related cognitive fog and the 
relative efficacy of two intervention strategies to treat moderate cognitive impairment using a 
randomized trial which will inform the design of a future adaptive trial.  We plan to study 120 post-
COVID patients seen in the Long-COVID clinic over the next 12 months with moderate or severe 
cognitive fog to assess the type and severity of neurocognitive impairment using computerized 
neuropsychological testing (BrainCheck). We will randomize to either 1) dCBT with coaching (RxWell) 
versus 2) stimulant medication (amphetamine/dextroamphetamine), as part of the study embedded 
in clinical care, to provide data to inform design of future larger phase adaptive trials.   BrainCheck is 

an FDA-approved technology to provide rapid, mobile cognitive assessment with venture investment 
and partnership with UPMC Enterprises. RxWell is a mobile app, developed and housed at UPMC Health 
Plan, with health coaches employed by UPMC. Both technology solutions improve access in an era of 
shortage of neuropsychologists and mental health providers. Stimulants have documented safety and 
effectiveness in helping neurocognitive deficits in conditions with similar deficit such as ADHD, post-
concussion, and other inflammatory medical conditions. 
We will evaluate effects of treatments on cognitive impairment (primary aim) and emotional distress 
(depression), satisfaction with life, work disability and health care utilization (secondary outcomes) over 
3 months.  Findings will provide inform and guide the design for the next phase adaptive clinical trial. 
These results will be generalizable to treating other common neuroinflammatory cognitive deficits such 
as that which follows ICU admission for sepsis or respiratory failure or following chemotherapy.  
Select the item(s) that best support(s) your research 
✓ Promotes research with new approaches and innovations in care. 
✓ Incorporates the concept of comparative effectiveness and/or embedded and adaptive designs, 
which allows researchers to rapidly test multiple treatment approaches more efficiently than 
traditional clinical trials and with quicker, more applicable results. 
✓ Supports a current UPMC focused initiative, including (but not limited to) those with aggressive 
approaches to cancer, gastrointestinal, heart disease and neuroscience. 
Problem statement: (COVID-19 threatened the health of millions of Americans and others across the 
globe. After acute illness, prolonged effects called Long-COVID extract much from sufferers; data driven 
methods to address and manage these symptoms are lacking. Cognitive fog and emotional distress are 
common longer-term consequences after COVID-19. In our clinic, 80% of Long-COVID patients report 
persistent cognitive fog and 46% of these have at least moderate depressive severity. Both inflammatory 
and non-inflammatory factors may cause the cognitive and depressive symptoms.  
We propose two efficient solutions that advance the treatment of reversible cognitive impairment 
secondary to COVID, which may apply to other medical conditions.  Our two interventions approach the 
problem from different perspectives- one targeting cognitive fog associated with depression, the other 
the cognitive fog directly. For depression with cognitive fog, a digital cognitive behavioral solution with 
health coaches offers cognitive rehabilitation strategies. For cognitive fog without depression, a 
stimulant medication known to reduce cognitive impairment in other chronic medical conditions will be 
used. Preliminary findings from this project will provide the necessary data to write a competitive 
federally supported proposal to fund a larger-scale adaptive design study. This next phase proposal will 
also incorporate learnings from this preliminary study to personalize intervention strategies to target 
specific cognitive domains of impairment. We will seek both federal funding and internal funding (UPMC 
Enterprises) for this next larger phase. 
Summary of Project 
Design Summary: Randomized trial of dCBT versus stimulant to treat cognitive impairment +/- 
depression in adults with Long-COVID.   
Aim 1:  Test efficacy of two interventions for improving cognitive impairment (primary outcome) and 
emotional distress (depression), life satisfaction, work disability, and medical utilization (secondary 

outcomes). Assess effect of demographic and COVID symptom characterization variables on treatment 
efficacy.  
Hypothesis: Stimulant therapy will outperform dCBT for patients with cognitive impairment alone and 
dCBT will outperform stimulant for cognitive impairment and depression.   
Aim 2: Define the important response characteristics in these patients to inform design of a larger 
adaptive clinical trial evaluating treatment options for COVID-related cognitive impairment.    
Methodology: Participants with confirmed Long-COVID cognitive impairment assigned with a 1:1 
allocation to either arm using a permuted block design stratified by depression severity. Participants will 
complete computerized neurocognitive assessments and other study measures at baseline, 1.5 (interim) 
and 3 months after randomization.  
Inclusion: Patients with Long-COVID between ages of 21-65; moderate cognitive impairment (MOCA<18) 
present for at least 3 months; access to a smartphone.  
Exclusion: No history of dementia, psychosis, mania, addiction or current conditions requiring 
immediate hospitalization. No history of stimulant failure. No current cardiac condition 
 
Interventions: 
1. RxWell is a mobile application that consists of CBT techniques1 and a health coach who provides 
in-app guidance and risk mitigation. Coaches will receive training to provide cognitive 
rehabilitation tips. Usage will be tracked.  
 
2. Standardized dosing of amphetamine/dextroamphetamine monitored monthly with response-
based titration to maximum dose of 20 mg bid2 with side effects tracked. To date, patients with 
post-COVID fog have tolerated stimulants well.    
 Clinical flow and recruitment rates for registry study make 12-month recruitment completion feasible. 
Primary outcome: Cognitive impairment 
Measures: 
Montreal Cognitive Assessment (MOCA) (10 minutes3) A validated screening tool for detection of 
mild cognitive impairment.  
BrainCheck Neurocognitive Assessment (15 minutes): FDA-approved validated automated remote 
neurocognitive assessments in multiple domains4. 
ImPACT (20 minutes) is an FDA-approved computerized neurocognitive concussion assessment tool5.  
Secondary outcomes: depression (PHQ8), satisfaction with life (SWLS), disability (Sheenan Disability 
Scale), and health care utilization (ED and outpatient visits).  
Statistical Analysis: 

Aim 1: Intent-to-treat analyses stratified by depression severity. We evaluate three-month outcomes 
using linear regression models with assigned intervention depression severity and the corresponding 
baseline score as independent variables. Longitudinal linear mixed effects regression models with time, 
intervention, depression severity and corresponding baseline scores will assess treatment effects at 1.5 
and 3 months and with interactions between intervention and time-points tested.  Multivariable models 
include prespecified demographic and COVID symptom characteristics as covariates.  
Aim 2: We will build a seamless Phase 2 to Phase 3 design with defined decision rules to determine 
whether interventions, including dCBT and stimulant, will “graduate” to the Phase 3 adaptive clinical 
trial. Bayesian analyses of accumulated data (including data from Aim 1) are performed on a 
prespecified schedule until stopping criteria are met. For a comparison of interventions, we may 
conclude superiority, inferiority or futility which can depend on pre-defined stratification variables.  We 
anticipate that a response adaptive randomization (RAR) will be applied in Phase 3 such that the 
proportion of participants who receive each intervention will be determined based on the predicted 
probability that the intervention is optimal considering all accrued outcome data. Findings from Aim 1 
will be used in simulations to estimate sample size requirements and to evaluate the operating 
characteristics of the adaptive clinical trial.  
References 
1. Szigethy et al., Clinical and Translational Gastroenterology, 12(12), DOI: 
10.14309/ctg.0000000000000436 
2. Gardner et al., Phys Sportsmed. Feb;45(1):1-10,2017 
3.  Smith et al., Can J Psychiatry May;52(5):329-32,2007.  
4. Ye et al., medRxiv 2020.06.01.20119289. 
5.  Maerlender et al., Clinical neuropsychologist, 24(8):1309–1325,2010.