Do clinical assessments, steady-state or daily-life gait characteristics predict falls in ambulatory chronic stroke survivors?

Michiel Punt, Sjoerd M. Bruijn, Harriet Wittink, Ingrid G. van de Port, Jaap H. Van Dieën

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Objective: This exploratory study investigated to what extent gait characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. Design: Prospective study. Subjects: Chronic fall-prone and non-fall-prone stroke survivors. Methods: Steady-state gait characteristics were collected from 40 participants while walking on a treadmill with motion capture of spatio-temporal, variability, and stability measures. An accelerometer was used to collect daily-life gait characteristics during 7 days. Six physical and psychological assessments were administered. Fall events were determined using a "fall calendar" and monthly phone calls over a 6-month period. After data reduction through principal component analysis, the predictive capacity of each method was determined by logistic regression. Results: Thirty-eight percent of the participants were classified as fallers. Laboratory-based and daily- life gait characteristics predicted falls acceptably well, with an area under the curve of, 0.73 and 0.72, respectively, while fall predictions from clinical assessments were limited (0.64). Conclusion: Independent of the type of gait assessment, qualitative gait characteristics are better fall predictors than clinical assessments. Clinicians should therefore consider gait analyses as an alternative for identifying fall-prone stroke survivors.

Original languageEnglish
Pages (from-to)402-409
Number of pages8
JournalJournal of Rehabilitation Medicine
Volume49
Issue number5
DOIs
Publication statusPublished - 2017

Fingerprint

Gait
Stroke
Principal Component Analysis
Walking
Area Under Curve
Logistic Models
Prospective Studies
Psychology

Keywords

  • Accelerometry
  • Cerebrovascular accident
  • Fall prediction
  • Gait
  • Prospective falls
  • Stroke

Cite this

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title = "Do clinical assessments, steady-state or daily-life gait characteristics predict falls in ambulatory chronic stroke survivors?",
abstract = "Objective: This exploratory study investigated to what extent gait characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. Design: Prospective study. Subjects: Chronic fall-prone and non-fall-prone stroke survivors. Methods: Steady-state gait characteristics were collected from 40 participants while walking on a treadmill with motion capture of spatio-temporal, variability, and stability measures. An accelerometer was used to collect daily-life gait characteristics during 7 days. Six physical and psychological assessments were administered. Fall events were determined using a {"}fall calendar{"} and monthly phone calls over a 6-month period. After data reduction through principal component analysis, the predictive capacity of each method was determined by logistic regression. Results: Thirty-eight percent of the participants were classified as fallers. Laboratory-based and daily- life gait characteristics predicted falls acceptably well, with an area under the curve of, 0.73 and 0.72, respectively, while fall predictions from clinical assessments were limited (0.64). Conclusion: Independent of the type of gait assessment, qualitative gait characteristics are better fall predictors than clinical assessments. Clinicians should therefore consider gait analyses as an alternative for identifying fall-prone stroke survivors.",
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Do clinical assessments, steady-state or daily-life gait characteristics predict falls in ambulatory chronic stroke survivors? / Punt, Michiel; Bruijn, Sjoerd M.; Wittink, Harriet; van de Port, Ingrid G.; Van Dieën, Jaap H.

In: Journal of Rehabilitation Medicine, Vol. 49, No. 5, 2017, p. 402-409.

Research output: Contribution to JournalArticleAcademicpeer-review

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