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. 2009;32(3):97-102.
doi: 10.1519/00139143-200932030-00003.

The relationship between fatigue, aerobic fitness, and motor control in people with chronic stroke: a pilot study

Benjamin Y Tseng  1 , Patricia Kluding
Affiliations

The relationship between fatigue, aerobic fitness, and motor control in people with chronic stroke: a pilot study

Benjamin Y Tseng et al. J Geriatr Phys Ther. 2009.

Abstract

Background: Fatigue is a commonly neglected issue despite the high incidence rate reported in people post-stroke.

Objective: To explore the relationship between fatigue, aerobic fitness, and motor control in people with chronic stroke.

Methods: Nine people post-stroke participated in this cross-sectional study (7 females, mean age = 56.8 (11.8) years, range 47-73, time post-stroke = 47.6 (51.2) months, range 11-140). Participants performed a six-minute-walk exercise in order to induce fatigue, followed immediately by a Fatigue Index (FI) scale to report fatigue at the moment. The distance walked (6MWD) was documented. On a separate visit, aerobic fitness was characterized by VO(2Peak) using a cycle-ergometer. In addition, Fugl-Meyer (FM) test was administered to assess motor control of the hemiparetic side. Pearson Product Correlation Coefficient and multiple linear regression were used to analyze the relationships between FI, VO(2Peak) and FM.

Results: VO(2Peak) showed significant positive correlations with FM (r = .779, p = .013) and 6MWD (r = .726, p = .027). Fatigue index displayed significant negative correlations with VO(2Peak) (r = -.739, p = .023) and FM (r = -.873, p = .002), but not with 6MWD (r = -.620, p = .075). Using stepwise multiple regression, we found that that FM was an independent predictor of FI (p = .002) and explained 76.2% of variance in FI (R2 = .762).

Conclusion: Our data suggests that motor control capability may be a good predictor of fatigue in people post-stroke. Fatigue is a complex phenomenon; a quantifiable measure that is sensitive to multiple components is needed in order to distinguish the nature of fatigue and its contributing factors.

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Figures

Figure 1
Figure 1
Experimental procedures.
Figure 2
Figure 2
Scatterplot illustrating the correlation between Fatigue (FI) and Aerobic Fitness (VO2Peak). FI = Fatigue Index VO2Peak – Peak oxygen uptake
Figure 3
Figure 3
Scatterplot illustrating the correlation between Fatigue (FI) and Motor Control (FM). FI – Fatigue Index score FM – Fugl-Meyer score
Figure 4
Figure 4
Scatterplot illustrating the correlation between Aerobic Fitness (VO2Peak) and Motor Control (FM). VO2Peak – Peak oxygen uptake FM – Fugl-Meyer score
Figure 5
Figure 5
Scatterplot illustrating the correlation between Six-Minute-Walk distance (6MWD) and Aerobic Fitness (VO2Peak). 6MWD – Six-Minute-Walk distance VO2Peak – Peak oxygen uptake
Figure 6
Figure 6
Scatterplot illustrating the correlation between Six-Minute-Walk distance (6MWD) and Fatigue (FI). 6MWD – Six-Minute-Walk distance FI – Fatigue Index score
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