Clinical characteristics of participants according to the red blood cell distribution width.

<p>Clinical characteristics of participants according to the red blood cell distribution width.</p

Relationship between red blood cell distribution width and leukoaraiosis.

<p>A) Boxplot for RDW according to the Fazekas scale. In each boxplot, the lower and upper ends of the box represent the 25^th and 75^th percentiles (interquartile range, IQR) and the line inside the box represents the median. An asterisk indicates the mean value. The ends of the vertical lines represent the lowest and the highest value within the range from 25^th percentile– 1.5 x IQR to 75^th percentile + 1.5 x IQR. B) Regression spline curve of estimated probability for severe degree of leukoaraiosis according to the level of RDW. The black lines and gray shadows represent the estimated probability and the 95% confidence intervals for the presence of severe degree of leukoaraiosis (Fazekas scale ≥2) at the RDW level, based on the generalized additive model with splines. Adjustments were made on the variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150308#pone.0150308.t003" target="_blank">Table 3</a>. The x-axis is limited from the 5^th to the 95^th percentile of RDW to avoid overfitting by rare extremes. RDW indicates red blood cell distribution width.</p

Results of univariate logistic regression for the severity of leukoaraiosis.

<p>Results of univariate logistic regression for the severity of leukoaraiosis.</p

Red blood cell distribution on the presence of severe degree of leukoaraiosis.

<p>Red blood cell distribution on the presence of severe degree of leukoaraiosis.</p

Subgroup analysis for the effect of RDW on severe-degree of leukoaraiosis.

<p>Subgroup analysis for the effect of RDW on severe-degree of leukoaraiosis.</p

Determinants of quality of life in patients with fibromyalgia: A structural equation modeling approach

<div><p>Objective</p><p>Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM).</p><p>Methods</p><p>HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software.</p><p>Results</p><p>Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ² = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI.</p><p>Conclusions</p><p>In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL.</p></div

Significant pathways of the final model.

<p>FIQ: Fibromyalgia Impact Questionnaire, BDI: Beck Depression Inventory, STAI: State-Trait Anxiety Inventory, PCS: physical component summary, MCS: mental component summary.</p

Regression weights between structural parameters.

<p>Regression weights between structural parameters.</p

Total, direct, and indirect effects of independent variables on dependent variables.

<p>Total, direct, and indirect effects of independent variables on dependent variables.</p