Absolute frequencies of people with zero, one, or more than one autoimmune diseases.

<p>Absolute frequencies of people with zero, one, or more than one autoimmune diseases.</p

Co-morbidity of autoimmune diseases: number of observed and expected people with zero, one and more than one autoimmune disease.

<p>Co-morbidity of autoimmune diseases: number of observed and expected people with zero, one and more than one autoimmune disease.</p

Prevalence of autoimmune diseases according to gender.

<p>Prevalence of autoimmune diseases according to gender.</p

Prevalence of each autoimmune disease per 100000 people.

<p>Prevalence of each autoimmune disease per 100000 people.</p

Demographic and clinical characteristics of subjects.

<p>Demographic and clinical characteristics of subjects.</p

OPLS-DA score plots in the predictive (<i>x</i>-axis) and orthogonal (<i>y</i>-axis) components of ¹H NMR spectral data of urine samples.

<p><b>A) “Pain <i>vs</i>. C” model. B) “NP <i>vs</i>. C” model. C) “NC <i>vs</i>. C” model. D) “NP <i>vs</i>. NC” model.</b> Separation of classes is maximized along the predictive component, while the orthogonal component accounts for intra-class variability. Ellipse indicates the confidence region. Pain: neuropathic and nociceptive pain samples—inverted grey triangles; C: matched control samples—green circles; NP: neuropathic pain samples—red squares; NC nociceptive pain samples—blue triangles. Details of OPLS-DA models performance are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150476#pone.0150476.s003" target="_blank">S1 Table</a>.</p

Results of samples classification for the different two-classes discriminant models.

<p>Results of samples classification for the different two-classes discriminant models.</p