# Evaluating a Comprehensive Multimodal Outpatient Rehabilitation Program to Improve the Functioning of Persons Suffering from Post-acute Sequelae of SARS-CoV-2 infection (PASC): A Randomized Controlled

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2024 · $642,659

## Abstract

About 10-20% of persons who contract SARS CoV-2 will experience persistent post-acute sequelae of SARS-
CoV-2 infection (referred here as PASC). Given that persistent symptoms are heterogeneous with multisystem
involvement, recent consensus recommendations suggest that a holistic rehabilitation program may be
required to manage PASC and restore function. While treatments offered at emerging outpatient COVID
recovery clinics are being informed by previous similar diseases, the need is great for a better understanding of
the unique needs of this growing population and for tested, efficacious rehabilitation programs to address
them. We provide both here. Specifically, our aims are: (1) To quantify the incidence and severity of PASC
across different variants and their effects on health and functioning; (2) To develop and evaluate the
effectiveness of a patient-centered, interdisciplinary, multimodal comprehensive rehabilitation program among
patients with PASC; and (3)To estimate the costs associated with the proposed PASC rehabilitation
intervention and to examine the relationship between intervention’s costs and effectiveness and their
implication for rehabilitation program initiatives. Data from a large and diverse ongoing longitudinal survey of
persons who tested for COVID-19 at the study health system will serve as the sampling frame from which to
identify and enroll PASC patients in the study. The targeted six-week program will be comprised of a core set
of therapies, including individually titrated stretching and flexibility, strengthening of accessory breathing
muscles and diaphragm, resistance and aerobic conditioning, and vestibular rehabilitation, supplemented by
neuropsychological and cognitive remediation tailored to patients’ needs. Using a randomized controlled trial
(RCT) design, the effectiveness of the intervention will be compared to that of usual care augmented by a one-
time in-person assessment and patient education materials. In addition to walking speed, a widely used global
measure of aerobic capacity and endurance, and patient-reported health and functioning (primary outcomes),
we will assess the intervention effectiveness on: (i) cognitive functioning, (ii) pain, (iii) fatigue, (iv) tension,
stress, anxiety, and depression, and (v) self-management of PASC symptoms (secondary outcomes).
Outcomes will be measured at fixed points in time at 8 weeks (shortly after therapy completion) and at 90 day’s
post- study entry to examine sustainability of effects. Our overarching hypothesis is that that higher
intervention costs in the intervention group will be more than offset by greater improvements in outcomes
implying that, overall, persons in the intervention group will receive more cost-effective care than those in usual
care group. Given the dearth of rigorous scientific evidence regarding effective assessment and treatment of
PASC and the unresolved questions concerning access to and value of post-COVID rehabilitation care, the
...

## Key facts

- **NIH application ID:** 10825569
- **Project number:** 5R01HD108312-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** TIMOTHY R DILLINGHAM
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $642,659
- **Award type:** 5
- **Project period:** 2023-04-12 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10825569

## Citation

> US National Institutes of Health, RePORTER application 10825569, Evaluating a Comprehensive Multimodal Outpatient Rehabilitation Program to Improve the Functioning of Persons Suffering from Post-acute Sequelae of SARS-CoV-2 infection (PASC): A Randomized Controlled (5R01HD108312-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10825569. Licensed CC0.

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