IDEAS home Printed from https://ideas.repec.org/a/wly/nuhsci/v17y2015i4p533-538.html
   My bibliography  Save this article

Gait velocity and walking distance to predict community walking after stroke

Author

Listed:
  • SeungHeon An
  • YunBok Lee
  • HyeonHui Shin
  • GyuChang Lee

Abstract

Gait speed and walking distance were evaluated as predictors for levels of community walking after stroke. In this study, 103 stroke survivors were identified as limited (n = 67) or independent community walkers (n = 36). Ten meter and six min walk tests were used to measure gait speed and walking distance, respectively. The discriminative properties of gait speed and walking distance for community walking were investigated using receiver operating characteristic curves. Cut‐off values of 0.87 m/s for community walking gait speed for walking distance had positive predictive values of 65% and 55%, respectively. The negative predictive value ranged from 89% for gait speed to 79% for walking distance. Gait speed and walking distance showed significant differences between limited and independent community walking. Gait speed was more significantly related to community walking than walking distance. The results of this study suggest that gait speed is a better predictor for community walking than walking distance in moderately affected post‐stroke survivors.

Suggested Citation

  • SeungHeon An & YunBok Lee & HyeonHui Shin & GyuChang Lee, 2015. "Gait velocity and walking distance to predict community walking after stroke," Nursing & Health Sciences, John Wiley & Sons, vol. 17(4), pages 533-538, December.
    • Handle: RePEc:wly:nuhsci:v:17:y:2015:i:4:p:533-538
    DOI: 10.1111/nhs.12234
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/nhs.12234
    Download Restriction: no
    File URL: https://libkey.io/10.1111/nhs.12234?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fayaz Khan & Sami Abusharha & Aljowhara Alfuraidy & Khadeeja Nimatallah & Raghad Almalki & Rafa’a Basaffar & Mawada Mirdad & Mohamed Faisal Chevidikunnan & Reem Basuodan, 2022. "Prediction of Factors Affecting Mobility in Patients with Stroke and Finding the Mediation Effect of Balance on Mobility: A Cross-Sectional Study," IJERPH, MDPI, vol. 19(24), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:nuhsci:v:17:y:2015:i:4:p:533-538. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1442-2018 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.