Abstract
Objective
To classify patients with stroke into subgroups based on their characteristics at
the moment of discharge from inpatient rehabilitation in order to predict community
ambulation outcome 6 months later.
Design
Prospective cohort study with a baseline measurement at discharge from inpatient care
and final outcome determined after 6 months.
Setting
Community.
Participants
A cohort of patients (N=243) with stroke, referred for outpatient physical therapy,
after completing inpatient rehabilitation in The Netherlands.
Interventions
Not applicable.
Main Outcome Measures
A classification model was developed using Classification And Regression Tree (CART)
analysis. Final outcome was determined using the community ambulation questionnaire.
Potential baseline predictors included patient demographics, stroke characteristics,
use of assistive devices, comfortable gait speed, balance, strength, motivation, falls
efficacy, anxiety, and depression.
Results
The CART model accurately predicted independent community ambulation in 181 of 193
patients with stroke, based on a comfortable gait speed at discharge of 0.5 meters
per second or faster. In contrast, 27 of 50 patients with gait speeds below 0.5 meters
per second were correctly predicted to become noncommunity walkers.
Conclusions
We show that comfortable gait speed is a key factor in the prognosis of community
ambulation outcome. The CART model may support clinicians in organizing community
services at the moment of discharge from inpatient care.
List of abbreviations:
CAQ (Community Ambulation Questionnaire), CART (Classification And Regression Tree), CI (confidence interval)Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Archives of Physical Medicine and RehabilitationAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Interventions for improving community ambulation in individuals with stroke.Cochrane Database Syst Rev. 2015; 3: CD010200
- What is the evidence for physical therapy poststroke? A systematic review and meta-analysis.PLoS One. 2014; 9e87987
- Measurement of community ambulation after stroke: current status and future developments.Stroke. 2005; 36: 1457-1461
- International Classification of Functioning, Disability and Health: ICF.World Health Organization, Geneva, Switzerland2001
- Community ambulation after stroke: how important and obtainable is it and what measures appear predictive?.Arch Phys Med Rehabil. 2004; 85: 234-239
- Participation in community walking following stroke: subjective versus objective measures and the impact of personal factors.Phys Ther. 2011; 91: 1865-1876
- Classification of walking handicap in the stroke population.Stroke. 1995; 26: 982-989
- Community ambulation in patients with chronic stroke: how is it related to gait speed?.J Rehabil Med. 2008; 40: 23-27
- Levels of community ambulation ability in patients with stroke who live in a rural area.Malays J Med Sci. 2016; 23: 56-62
- The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies.Int J Surg. 2014; 12: 1495-1499
- Early prediction of outcome of activities of daily living after stroke: a systematic review.Stroke. 2011; 42: 1482-1488
- Long-term restrictions in participation in stroke survivors under and over 70 years of age.Disabil Rehabil. 2018; 40: 637-645
- Is gait speed or walking distance a better predictor for community walking after stroke?.J Rehabil Med. 2013; 45: 535-540
- Classification of walking ability of household walkers versus community walkers based on K-BBS, gait velocity and upright motor control.Eur J Phys Rehabil Med. 2015; 51: 619-625
- Predicting home and community walking activity poststroke.Stroke. 2017; 48: 406-411
- Gait velocity and walking distance to predict community walking after stroke.Nurs Health Sci. 2015; 17: 533-538
- Factors predicting falls and mobility outcomes in patients with stroke returning home after rehabilitation who are at risk of falling.Arch Phys Med Rehabil. 2017; 98: 2433-2441
- Severity of spatial neglect during acute inpatient rehabilitation predicts community mobility after stroke.PM R. 2014; 6: 716-722
- Fast gait speed and self-perceived balance as valid predictors and discriminators of independent community walking at 6 months post-stroke--a preliminary study.Disabil Rehabil. 2015; 37: 129-134
- Non-motor factors associated with the attainment of community ambulation after stroke.Clin Med Res. 2015; 13: 58-64
- Effects of circuit training as alternative to usual physiotherapy after stroke: randomised controlled trial.BMJ. 2012; 344e2672
- Cost-effectiveness of a structured progressive task-oriented circuit class training programme to enhance walking competency after stroke: the protocol of the FIT-Stroke trial.BMC Neurol. 2009; 9: 43
- Mobility after stroke: reliability of measures of impairment and disability.Int Disabil Stud. 1990; 12: 6-9
- Ordinal and timed balance measurements: reliability and validity in patients with stroke.Clin Rehabil. 1993; 7: 9-13
- Assessing motor impairment after stroke: a pilot reliability study.J Neurol Neurosurg Psychiatry. 1990; 53: 576-579
- Assessing walking speed in clinical research: a systematic review.J Eval Clin Pract. 2008; 14: 552-562
- Falls efficacy as a measure of fear of falling.J Gerontol. 1990; 45: P239-P243
- International experiences with the hospital anxiety and depression scale--a review of validation data and clinical results.J Psychosom Res. 1997; 42: 17-41
- Using multivariate statistics.3rd ed. HarperCollins, New York1996
- Recursive partitioning and applications.2nd ed. Springer, New York2010
- Classification and regression tree analysis in public health: methodological review and comparison with logistic regression.Ann Behav Med. 2003; 26: 172-181
- Improvements in speed-based gait classifications are meaningful.Stroke. 2007; 38: 2096-2100
- Effects of augmented exercise therapy on outcome of gait and gait-related activities in the first 6 months after stroke: a meta-analysis.Stroke. 2011; 42: 3311-3315
- Stroke rehabilitation.Lancet. 2011; 377: 1693-1702
Article info
Publication history
Published online: May 30, 2019
Footnotes
Supported by the CARE4BRAIN project funded by ZonMW (grant no. 60-63000-98-012) and the ARMED4STROKE project funded by WCF/ZonMW (grant no. 858001102). This study was part of the FIT-Stroke trial, registered in the Dutch Trial Register as NTR 1534, financed by ZonMW (grant no. 80-82310-98-08303). The funding sources had no involvement in study design; collection, analysis and interpretation of data; writing of the report; and the decision to submit the article for publication.
Disclosures: none.
Clinical Trial Registration No.: NTR 1534.
Identification
Copyright
© 2019 by the American Congress of Rehabilitation Medicine
