Summary of clinical and biochemical variables.

<p>Summary of clinical and biochemical variables.</p

Plasma BPA concentration.

<p>Healthy subjects (n = 10); patients on online hemodiafiltration (HDF) (n = 58) and patients on conventional hemodialysis (HD) who were later enrolled in the present study (n = 18) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193288#pone.0193288.ref007" target="_blank">7</a>]. Data expressed as mean±SD. For HD and OL-HDF, values correspond to baseline predialysis values in the switch studies. At this point, patients had been on HD or OL-HDF for >6 months. * p<0.05; ** p = 0.017.</p

Study design: Timing of plasma sampling for BPA assessment.

<p>Baseline pre-dialysis plasma sampling took place after >6 months OL-HDF and prior to the first session with the switch dialyzer. Baseline post-dialysis sampling was obtained immediately after the first session with the switch dialyzer. Sampling was repeated pre- and post-dialysis after 3 months on the switch dialyzer.</p

Plasma BPA concentration in patients on OL-HDF with polynephron (PN) or polysulfone (PS) membranes.

<p>Pre- and post-dialysis measurements are shown for the first (baseline) and the last (3-month) session after the switch. Prior to the baseline pre-dialysis sample, patients had been on OL-HDF with the opposite membrane for >6 months. Thus, baseline pre-dialysis values represent values corresponding to >6 months OL-HDF with the opposite membrane and were used as baseline values for the switch study, while baseline post-dialysis values were already obtained after the first session with the switch membrane. Data expressed as mean±SD. ** p<0.01. Pre- and Post- refers to pre-dialysis and post-dialysis (OL-HDF) session.</p

Univariate logistic regression models for predicting mortality.

<p>Higher baseline age, lower baseline serum albumin and a decreasing ΔiPTH (ΔiPTH<0 pg/ml) within the first year are predictors of mortality.</p

Multivariable regression model for mortality prediction considering ΔiPTH within the first year as a binary variable (decrease/increase) or as quartiles.

<p>Multivariable regression model for mortality prediction considering ΔiPTH within the first year as a binary variable (decrease/increase) or as quartiles.</p

Baseline quantitative variables in patients with or without a decrease in ΔiPTH during the first year.

<p>Data expressed as Mean ±SD.</p

Demographic and clinical characteristics of the study population.

<p>Data expressed as mean SD, median (interquartile range) or %.</p

Patient flowchart.

<p>Patient flowchart.</p

Changes in iPTH (ΔiPTH,pg/ml) during the first 12 months and mortality at 24 months.

<p>(A) Comparison of ΔiPTH within the first 12 months between survivors and deceased patients at 24 months. The mean ΔiPTH was higher in survivors than in deceased patients. <b><i>* P <0</i>.<i>05</i></b>. (B) Graphic representation of mortality according to quartiles of ΔiPTH in the first year: Q1 ΔiPTH <0 pg/ml; Q2 0–100 pg/ml; Q3 101–300 pg/ml; Q4 >301 pg/ml. <b><i>* P <0</i>.<i>05 *** p <0</i>.<i>001 vs Q1</i></b>.</p