Matching Clinical Profiles with Interventions to Optimize Daily Stepping in People with Stroke

Kiersten M McCartney; Ryan T Pohlig; Allison E Miller; Elizabeth D Thompson; Darcy S Reisman

doi:10.1093/ptj/pzaf070

Matching Clinical Profiles with Interventions to Optimize Daily Stepping in People with Stroke

Phys Ther. 2025 May 13:pzaf070. doi: 10.1093/ptj/pzaf070. Online ahead of print.

Authors

Kiersten M McCartney^{1

2}, Ryan T Pohlig³, Allison E Miller⁴, Elizabeth D Thompson¹, Darcy S Reisman^{1

2}

Affiliations

¹ University of Delaware, Department of Physical Therapy, Newark, DE, United States.
² University of Delaware, Biomechanics and Movement Science Program, Newark, DE, United States.
³ University of Delaware, Biostatistics Core, Newark, DE, United States.
⁴ Washington University School of Medicine in St. Louis, Program of Physical Therapy, St. Louis, MO, United States.

PMID: 40360175
DOI: 10.1093/ptj/pzaf070

Abstract

Importance: Individualizing interventions is imperative to optimize step-activity in people with chronic stroke.

Objective: The objective was to group individuals with chronic stroke into clinical profiles based on baseline characteristics and examine if these profiles preferentially benefitted from a specific intervention to improve daily step-activity.

Design: This is a secondary analysis of a randomized control trial.

Setting: The parent study occurred at 4 outpatient rehabilitation clinics.

Participants: Participants had strokes ≥6 months prior to enrollment, were 21 to 85 years old, had walking speeds of 0.3 to1.0 m/s, and took <8000 steps-per-day.

Interventions: Participants were randomized to high-intensity treadmill training (FAST), a step-activity behavioral intervention (SAM), or a combined intervention (FAST+SAM).

Main outcome(s): The primary outcome was the interaction of latent class (clinical profile) and intervention group (FAST, SAM, FAST+SAM) on a change in steps-per-day. Key clinical characteristics to identify the latent classes included walking speed, walking endurance, balance self-efficacy, cognition, and area deprivation.

Results: Of the 190 participants with complete pre- and post-intervention data (mean [SD] age, 64 [12] years; 93 females [48.9%]), 3 distinct profiles of people with chronic stroke were identified. Class 1 had the lowest walking capacity (speed and endurance), lowest balance self-efficacy, and highest area deprivation, and the greatest change in step-activity when enrolled in SAM (mean = 1624, 95% CI = 426 to 2821) or FAST+SAM (mean = 1150, 95% CI = 723 to 1577]). Class 2 had walking capacity, baseline steps-per-day, and self-efficacy values between Class 1 and 3, and had the greatest change in step-activity when enrolled in SAM (mean = 2002, 95% CI = 1193 to 2811). Class 3 had the highest walking capacity, highest self-efficacy, and lowest area deprivation and the greatest change in step-activity when enrolled in FAST+SAM (mean = 1532, 95% CI = 915 to 2150).

Conclusions: People with chronic stroke require different interventions to optimize changes in step-activity.

Relevance: Clinicians can use clinically relevant measures to personalize intervention selection to augment step-activity in people with chronic stroke.

Keywords: Stroke; High-intensity gait; Physical activity; Step-activity monitoring; Walking.