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Spatiotemporal Gait Parameters That Predict the Tinetti Performance-Oriented Mobility Assessment in People With Stroke

  • Jeong, Yeon-gyu (Dept. of Physical Therapy, Dongguk University Ilsan Hospital) ;
  • Kim, Jeong-soo (Dept. of Physical Therapy, Seoul Rehabilitation Hospital)
  • Received : 2015.09.11
  • Accepted : 2015.10.15
  • Published : 2015.11.19

Abstract

The purpose of this study was to find which spatiotemporal gait parameters gained from stroke patients could be predictive factors for the gait part of Tinetti Performance-Oriented Mobility Assessment (POMA-G). Two hundred forty-six stroke patients were recruited for this study. They participated in two assessments, the POMA-G and computerized spatiotemporal gait analysis. To analyze the relationship between the POMA-G and spatiotemporal parameters, we used Pearson's correlation coefficients. In addition, multiple linear regression analyses (stepwise method) were used to predict the spatiotemporal gait parameters that correlated most with the POMA-G. The results show that the gait velocity (r=.67, p<.01), cadence (r=.66, p<.01), step length of the affected side (r=.49, p<.01), step length of the non-affected side (r=.53, p<.01), swing percentage of the non-affected side (r=.47, p<.01), and single support percentage of the affected side (r=.53, p<.01) as well as the double support percentage of the non-affected side (r=-.42, p<.01) and the step-length asymmetry (r=-.64, p<.01) correlated with POMA-G. The gait velocity, step-length asymmetry, cadence, and single support percentage of the affected side explained 67%, 2%, 2%, and 1% of the variance in the POMA-G, respectively. In conclusion, gait velocity would be the most predictive factor for the POMA-G.

Keywords

References

  1. Canbek J, Fulk G, Nof L, et al. Test-retest reliability and construct validity of the tinetti performance-oriented mobility assessment in people with stroke. J Neuro Phys Ther. 2013;37(1):14-19. http://dx.doi.org/10.1097/NPT.0b013e318283ffcc
  2. Coutts F. Gait analysis in the therapeutic environment. Man Ther. 1999;4(1):2-10. https://doi.org/10.1016/S1356-689X(99)80003-4
  3. Daly JJ, Roenigk K, Holcomb J, et al. A randomized controlled trial of functional neuromuscular stimulation in chronic stroke subjects. Stroke. 2006;37(1):172-178. https://doi.org/10.1161/01.STR.0000195129.95220.77
  4. Dewar ME, Judge G. Temporal asymmetry as a gait quality indicator. Med Biol Eng Comput. 1980;18(5):689-693. https://doi.org/10.1007/BF02443147
  5. Dickstein R. Rehabilitation of gait speed after stroke: A critical review of intervention approaches. Neurorehabil Neural Repair. 2008;22(6):649-660. http://dx.doi.org/10.1177/1545968308315997
  6. Faber MJ, Bosscher RJ, van Wieringen PC. Clinimetric properties of the performance-oriented mobility assessment. Phys Ther. 2006;86(7):944-954.
  7. Kegelmeyer DA, Kloos AD, Thomas KM, et al. Reliability and validity of the tinetti mobility test for individuals with parkinson disease. Phys Ther. 2007;87(10):1369-1378. https://doi.org/10.2522/ptj.20070007
  8. Lin PY, Yang YR, Cheng SJ, et al. The relation between ankle impairments and gait velocity and symmetry in people with stroke. Arch Phys Med Rehabil. 2006;87(4):562-568. https://doi.org/10.1016/j.apmr.2005.12.042
  9. McDonough AL, Batavia M, Chen FC, et al. The validity and reliability of the gaitrite system's measurements: A preliminary evaluation. Arch Phys Med Rehabil. 2001;82(3):419-425. https://doi.org/10.1053/apmr.2001.19778
  10. McGinley JL, Goldie PA, Greenwood KM, et al. Accuracy and reliability of observational gait analysis data: Judgments of push-off in gait after stroke. Phys Ther. 2003;83(2):146-160.
  11. Menz HB, Latt MD, Tiedemann A, et al. Reliability of the gaitrite walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait Posture. 2004;20(1):20-25. https://doi.org/10.1016/S0966-6362(03)00068-7
  12. Patterson KK, Parafianowicz I, Danells CJ, et al. Gait asymmetry in community-ambulating stroke survivors. Arch Phys Med Rehabil. 2008;89(2):304-310. http://dx.doi.org/10.1016/j.apmr.2007.08.142
  13. Rinaldi LA, Monaco V. Spatio-temporal parameters and intralimb coordination patterns describing hemiparetic locomotion at controlled speed. J Neuroeng Rehabil. 2013;10(1):53. http://dx.doi.org/10.1186/1743-0003-10-53
  14. Roth EJ, Merbitz C, Mroczek K, et al. Hemiplegic gait: Relationships between walking speed and other temporal parameters. Am J Phys Med Rehabil. 1997;76(2):128-133. https://doi.org/10.1097/00002060-199703000-00008
  15. Schmid A, Duncan PW, Studenski S, et al. Improvements in speed-based gait classifications are meaningful. Stroke. 2007;38(7):2096-2100. https://doi.org/10.1161/STROKEAHA.106.475921
  16. Stokic DS, Horn TS, Ramshur JM, et al. Agreement between temporospatial gait parameters of an electronic walkway and a motion capture system in healthy and chronic stroke populations. Am J Phys Med Rehabil. 2009;88(6):437-444. http://dx.doi.org/10.1097/PHM.0b013e3181a5b1ec
  17. Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc. 1986;34(2):119-126. https://doi.org/10.1111/j.1532-5415.1986.tb05480.x
  18. Toro B, Nester CJ, Farren PC. The status of gait assessment among physiotherapists in the united kingdom. Am J Phys Med Rehabil. 2003;84(12):1878-1884. https://doi.org/10.1016/S0003-9993(03)00482-9