| Literature DB >> 29643935 |
Takakazu Oka1,2, Tokusei Tanahashi2, Nobuyuki Sudo2, Battuvshin Lkhagvasuren2, Yu Yamada1.
Abstract
BACKGROUND: In a previous randomized controlled trial, we found that sitting isometric yoga improves fatigue in patients with chronic fatigue syndrome (CFS) who are resistant to conventional therapy. The aim of this study was to investigate possible mechanisms behind this finding, focusing on the short-term fatigue-relieving effect, by comparing autonomic nervous function and blood biomarkers before and after a session of isometric yoga.Entities:
Keywords: Chronic fatigue syndrome; Cytokine; DHEA-S; Heart rate variability; Isometric yoga; Myalgic encephalomyelitis; Treatment
Year: 2018 PMID: 29643935 PMCID: PMC5891891 DOI: 10.1186/s13030-018-0123-2
Source DB: PubMed Journal: Biopsychosoc Med ISSN: 1751-0759
Fig. 1Experimental procedures
Fig. 2Sitting isometric yoga program. The 20-min sitting isometric yoga program consisted of three parts. (1) Patients practiced being aware of their spontaneous breathing for 1 min to facilitate interoceptive and proprioceptive awareness. (2) Patients slowly practiced six isometric postures, taking 3–10 s each (5 s in average), in association with exhalation with/without sounds, using 50% maximal physical strength. (3) Patients practiced abdominal breathing for 1 min
Changes in POMS scores, autonomic function indices, and blood biomarkers following a sitting isometric yoga session
n: Sample size
Values are mean ± standard deviation
Pre: Mean values before yoga sessions
Post: Mean values after yoga sessions
∆: The mean difference between Pre and Post values, i.e. Post value – Pre value
P value: Paired t-test or Wilcoxon signed-rank test between Pre and Post values
95% CI: 95% Confidence interval (Lower bound – Upper bound)
C: Correlations
*: Correlation between ∆ F and ∆ plasma/serum components, P < 0.05
#: Correlation between ∆ V and ∆ plasma/serum components, P < 0.05
n.s.: not significant
Highlighted in gray: The probability of normal distribution is violated by Kolmogorov-Smirnov test
Fig. 3Correlations between ∆ Fatigue score and ∆ plasma TGF-β1 (a) and ∆ plasma BDNF (b). Each trend line indicates a linear relationship between two respective variables
Fig. 4Correlations between ∆ Vigor score and ∆ plasma HVA; n = 15; a trendline indicates a linear relationship between two respective variables; mg/D, milligram per day (a). Normal P-P plot of the standardized residuals (b). Dependent variable: ∆ Vigor. Independent variable: ∆ HVA