<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03770611</url>
  </required_header>
  <id_info>
    <org_study_id>UIMER003</org_study_id>
    <nct_id>NCT03770611</nct_id>
  </id_info>
  <brief_title>Effect of Prebiotics and/or Probiotics on Uremic Toxins and Inflammation Markers in Peritoneal Dialysis Patients</brief_title>
  <official_title>Effect of a Nutritional Supplement of Probiotics and/or Prebiotics vs Placebo on Serum Concentrations of Uremic Toxins and Inflammatory Cytokines in Automated Peritoneal Dialysis Patients.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Unidad de Investigacion Medica en Enfermedades Renales</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Centro Universitario de Tonalá</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Universidad de Colima</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Unidad de Investigacion Medica en Enfermedades Renales</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      End-stage renal disease (ESRD) is a world public health problem, with high morbidity and&#xD;
      mortality. Cardiovascular disease is the main cause of mortality in ESRD; uremic toxin&#xD;
      retention and inflammation are considered non-traditional risk factors, as they have an&#xD;
      active role in atherosclerosis and vascular calcification pathogenesis in dialysis patients.&#xD;
&#xD;
      Uremic toxins may be generated by internal protein metabolism, however, some toxins that&#xD;
      can't be efficiently eliminated by dialysis such as indoxyl sulphate and p-cresyl sulphate&#xD;
      (protein bound toxins), are generated by the microbial metabolism in the large intestine by&#xD;
      proteolytic bacteria, and may diffuse easily through the intestinal lumen, as a leaky gut&#xD;
      characterizes kidney disease.&#xD;
&#xD;
      The gut has been recognized as a potential source of inflammation in ESRD patients;&#xD;
      accumulation of nitrogen compounds, presence of gastrointestinal symptoms, dietary changes&#xD;
      and multiple drugs and supplements use, stimulates microbiota alterations as bacterial&#xD;
      overgrowth and translocation. These phenomena, may active the immune system, promoting local&#xD;
      and systemic inflammation, which in turn has negative effects increasing endothelial&#xD;
      dysfunction, muscle catabolism, insulin and erythropoietin resistance, and decreases&#xD;
      appetite.&#xD;
&#xD;
      Some methods have been proposed to decrease inflammation and uremic toxin accumulation, as&#xD;
      more efficient dialysis and anti-inflammatory drugs; however, some of them have limited&#xD;
      efficacy and high cost. Nutritional treatments focused on modifying intestinal environment,&#xD;
      as pre- and probiotics have promising effects by altering production and absorption of uremic&#xD;
      toxins and decreasing inflammation; nevertheless, there is scarce information regarding its&#xD;
      use and their role in ESRD, particularly in peritoneal dialysis, which is a widely used&#xD;
      therapy in México. Furthermore, there is no clinical study comparing the effectiveness of&#xD;
      prebiotics, probiotics, and symbiotics on serum concentrations of uremic toxins and&#xD;
      inflammation in ESRD patients. It is possible that the administration of a nutritional&#xD;
      supplement of probiotics and/or prebiotics decreases the serum concentrations of uremic&#xD;
      toxins and inflammation markers in ESRD patients on automated peritoneal dialysis compared to&#xD;
      placebo.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Objective:&#xD;
&#xD;
      The aim of the present study is to evaluate and to compare the effect of a nutritional&#xD;
      supplement of probiotics and/or prebiotics on serum concentrations of uremic toxins and&#xD;
      inflammatory markers compared to placebo, in automated peritoneal dialysis patients.&#xD;
&#xD;
      Sample size:&#xD;
&#xD;
      For the sample size calculation a mean differences formula was used, with a 95% confidence&#xD;
      level, a 80% sample power and accuracy of 0.05. As a reference, the study of Salmean YA, 2015&#xD;
      was considered; in this study, the administration of pea fiber + inulin during 12 weeks in&#xD;
      chronic kidney disease patients, significantly decreased (p&lt;0.05) serum concentrations of&#xD;
      p-cresol (5.82 ± 1.72 mg/L) in comparison to placebo (7.25 ± 1.74 mg/L). After substituting&#xD;
      formula values and adding 20% of possible losses during follow-up, the sample size is: 28&#xD;
      patients.&#xD;
&#xD;
      Additionally, sample size calculation was made considering other outcomes. In the study of&#xD;
      Xie LN, 2015, the administration of high-fermentable soluble fiber in ESRD patients on&#xD;
      hemodialysis during 6 weeks, significantly decreased (p&lt;0.05) inflammation markers:&#xD;
      C-reactive protein (CRP), tumour necrosis factor alpha (TNFa) and interleukin 6 (IL-6) (4.8 ±&#xD;
      4.5 pg/mL, 10.1 ± 1.4 pg/mL, 31.8 ± 5.3 mg/L, respectively) compared to control group (9.5 ±&#xD;
      5.6 pg/mL, 13.1 ± 2.4 pg/mL, 51.5 ± 14.6 mg/L). After substituting the formula, sample size&#xD;
      was 19, 7, and 5 for CRP, TNFa and IL-6, respectively.&#xD;
&#xD;
      Thus, the highest value was finally used: 28 patients for intervention group.&#xD;
&#xD;
      Statistical analysis:&#xD;
&#xD;
      Quantitative variables will be shown as mean and standard deviation or median (25-75&#xD;
      percentiles) according to their parametric or non-parametric distribution; Qualitative&#xD;
      variables will be shown as frequency and percentage. Intergroup comparisons will be performed&#xD;
      with χ2 or Fisher test for qualitative variables and one-way ANOVA or Kruskal-Wallis test for&#xD;
      quantitative variables as appropriate. For intra-group comparisons Mc Nemar test will be used&#xD;
      for qualitative variables and paired T-test, Wilcoxon, repeated-measures or Friedman ANOVA&#xD;
      for quantitative variables as appropriate. An intention to treat analysis will be performed.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date type="Anticipated">January 7, 2019</start_date>
  <completion_date type="Anticipated">August 2020</completion_date>
  <primary_completion_date type="Anticipated">December 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Factorial Assignment</intervention_model>
    <intervention_model_description>Parallel assignment, patients in automated peritoneal dialysis will be randomly assigned to one of the four intervention groups: probiotic, prebiotic, symbiotic and placebo</intervention_model_description>
    <primary_purpose>Treatment</primary_purpose>
    <masking>Triple (Participant, Care Provider, Investigator)</masking>
    <masking_description>Patient Blinding: Patients in automated peritoneal dialysis will be blinded to the intervention they will receive. Evaluator Blinding: The principal investigator and the Doctorate program student will be blinded to the intervention that patients will receive (probiotic, prebiotic, symbiotic or placebo).&#xD;
Care providers will be blinded to the intervention groups.</masking_description>
  </study_design_info>
  <primary_outcome>
    <measure>Change of uremic toxins from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Measurement of serum concentrations of the uremic toxins p-cresyl sulphate (mg/dL) and indoxyl sulphate (mg/dL) by means of liquid chromatography.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Change of uremic toxins from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Measurement of serum concentrations of endotoxin (EU/mL) by means of Limulus amebocyte lisate test.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Change in gut microbiota composition from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Determination of fecal bacterial composition by DNA extraction and pyrosequencing analysis.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change in gastrointestinal symptoms from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Measurement of appetite and frequency and severity of gastrointestinal symptoms (nausea, vomiting, bloating, diarrhea, constipation) by means of a gastrointestinal symptoms questionnaire.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change of inflammatory cytokines from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Measurement of serum concentrations of inflammatory cytokines Interleukin-6 (pg/mL), Interleukin-10 (pg/mL) and Tumor Necrosis Factor alpha (pg/mL) by means of ELISA.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Change of inflammatory cytokines from basal to 1 and 3 months</measure>
    <time_frame>Baseline, 1 month and 3 months</time_frame>
    <description>Measurement of serum concentrations of C-Reactive Protein (mg/L) by means of nephelometry.</description>
  </secondary_outcome>
  <number_of_arms>4</number_of_arms>
  <enrollment type="Anticipated">112</enrollment>
  <condition>End Stage Renal Failure on Dialysis</condition>
  <arm_group>
    <arm_group_label>Probiotic</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Subjects receiving probiotic supplementation: 2x108 CFU probiotic bacteria + prebiotic placebo per day during 3 months</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Prebiotic</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Subjects receiving prebiotic supplementation: 20 g of prebiotic fiber + probiotic placebo per day during 3 months</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Symbiotic</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Subjects receiving probiotic and prebiotic supplementation: 2x108 CFU probiotic bacteria + 20 g of prebiotic fiber per day during 3 months</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Placebo</arm_group_label>
    <arm_group_type>Placebo Comparator</arm_group_type>
    <description>Subjects receiving placebo of probiotic and prebiotic per day during 3 months</description>
  </arm_group>
  <intervention>
    <intervention_type>Dietary Supplement</intervention_type>
    <intervention_name>Probiotic</intervention_name>
    <description>The probiotic supplement is composed of the following bacterial strains: Bacillus coagulans, Bacillus subtilis, Bifidobacterium (B) bifidum, B. breve, B. longum, Lactobacillus (L) acidophilus, L. brevis, L. casei, L. helveticus, L. Paracasei, L plantarum, L. rhamnosus, L. salivarus, Lactococcus lactis, Pediococcus acidilactici, Pediococcus parvulus, Weisella confusa, Weisella paramesenteroides</description>
    <arm_group_label>Probiotic</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Dietary Supplement</intervention_type>
    <intervention_name>Prebiotic</intervention_name>
    <description>The prebiotic fiber is Agave inulin</description>
    <arm_group_label>Prebiotic</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Dietary Supplement</intervention_type>
    <intervention_name>Symbiotic</intervention_name>
    <description>The supplement is a combination of the probiotic product + the prebiotic fiber</description>
    <arm_group_label>Symbiotic</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Dietary Supplement</intervention_type>
    <intervention_name>Placebo</intervention_name>
    <description>The supplement is a combination of probiotic placebo and prebiotic fiber placebo. Placebo will consist on maltodextrin for both cases.</description>
    <arm_group_label>Placebo</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  &gt;3 months on automated peritoneal dialysis treatment&#xD;
&#xD;
          -  Signed informed consent&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  ESRD of inflammatory cause (lupus, vasculitis, collagenopathies)&#xD;
&#xD;
          -  Intake of probiotics, prebiotics or fiber in the last 3 months&#xD;
&#xD;
          -  Use of anti-inflammatory drugs or nutritional supplements (immunossuppresants,&#xD;
             pentoxifylline, NSAIDs, omega-3)&#xD;
&#xD;
          -  Treated with antibiotics or sevelamer&#xD;
&#xD;
          -  Treated with research drugs or participants in any clinical trial&#xD;
&#xD;
          -  Peritonitis or active infection 2 weeks prior the study&#xD;
&#xD;
          -  Any medical condition affecting intestinal absorption (inflammatory bowel disease,&#xD;
             short bowel syndrome, bariatric surgery) or severe dysmotility&#xD;
&#xD;
          -  Severe malnutrition&#xD;
&#xD;
          -  Previous kidney transplantation&#xD;
&#xD;
          -  Serious diseases altering the fina outcomes of the study: decompensated heart failure,&#xD;
             chronic liver disease, cancer, AIDS.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Alfonso M Cueto-Manzano, PhD</last_name>
    <phone>52 (33) 38097269</phone>
    <email>a_cueto_manzano@hotmail.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Fabiola Martín-del-Campo, MSc</last_name>
    <phone>52 (33) 10711190</phone>
    <email>fabi_mc@hotmail.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Umae Hospital de Especialidades</name>
      <address>
        <city>Guadalajara</city>
        <state>Jalisco</state>
        <zip>44290</zip>
        <country>Mexico</country>
      </address>
    </facility>
    <contact>
      <last_name>ALFONSO M CUETO-MANZANO, PhD</last_name>
      <phone>(52) 333668300</phone>
      <phone_ext>32204</phone_ext>
      <email>a_cueto_manzano@hotmail.com</email>
    </contact>
    <investigator>
      <last_name>Fabiola Martín-del-Campo, MSc</last_name>
      <role>Sub-Investigator</role>
    </investigator>
    <investigator>
      <last_name>Hugo E Chavez-Chavez, MD</last_name>
      <role>Sub-Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>Mexico</country>
  </location_countries>
  <link>
    <url>https://www.usrds.org/2017/view/Default.aspx</url>
    <description>United States Renal Data Sytem. 2016 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. Bethesda, MD, 2016.</description>
  </link>
  <reference>
    <citation>Duranton F, Cohen G, De Smet R, Rodriguez M, Jankowski J, Vanholder R, Argiles A; European Uremic Toxin Work Group. Normal and pathologic concentrations of uremic toxins. J Am Soc Nephrol. 2012 Jul;23(7):1258-70. doi: 10.1681/ASN.2011121175. Epub 2012 May 24. Erratum In: J Am Soc Nephrol. 2013 Dec;24(12):2127-9.</citation>
    <PMID>22626821</PMID>
  </reference>
  <reference>
    <citation>Gryp T, Vanholder R, Vaneechoutte M, Glorieux G. p-Cresyl Sulfate. Toxins (Basel). 2017 Jan 29;9(2):52. doi: 10.3390/toxins9020052.</citation>
    <PMID>28146081</PMID>
  </reference>
  <reference>
    <citation>Ito S, Yoshida M. Protein-bound uremic toxins: new culprits of cardiovascular events in chronic kidney disease patients. Toxins (Basel). 2014 Feb 20;6(2):665-78. doi: 10.3390/toxins6020665.</citation>
    <PMID>24561478</PMID>
  </reference>
  <reference>
    <citation>Vaziri ND, Yuan J, Norris K. Role of urea in intestinal barrier dysfunction and disruption of epithelial tight junction in chronic kidney disease. Am J Nephrol. 2013;37(1):1-6. doi: 10.1159/000345969. Epub 2012 Dec 19.</citation>
    <PMID>23258127</PMID>
  </reference>
  <reference>
    <citation>Schepers E, Glorieux G, Vanholder R. The gut: the forgotten organ in uremia? Blood Purif. 2010;29(2):130-6. doi: 10.1159/000245639. Epub 2010 Jan 8.</citation>
    <PMID>20093818</PMID>
  </reference>
  <reference>
    <citation>Hauser AB, Stinghen AE, Goncalves SM, Bucharles S, Pecoits-Filho R. A gut feeling on endotoxemia: causes and consequences in chronic kidney disease. Nephron Clin Pract. 2011;118(2):c165-72; discussion c172. doi: 10.1159/000321438. Epub 2010 Dec 16.</citation>
    <PMID>21160227</PMID>
  </reference>
  <reference>
    <citation>Lin CJ, Wu V, Wu PC, Wu CJ. Meta-Analysis of the Associations of p-Cresyl Sulfate (PCS) and Indoxyl Sulfate (IS) with Cardiovascular Events and All-Cause Mortality in Patients with Chronic Renal Failure. PLoS One. 2015 Jul 14;10(7):e0132589. doi: 10.1371/journal.pone.0132589. eCollection 2015.</citation>
    <PMID>26173073</PMID>
  </reference>
  <reference>
    <citation>Soleimani A, Zarrati Mojarrad M, Bahmani F, Taghizadeh M, Ramezani M, Tajabadi-Ebrahimi M, Jafari P, Esmaillzadeh A, Asemi Z. Probiotic supplementation in diabetic hemodialysis patients has beneficial metabolic effects. Kidney Int. 2017 Feb;91(2):435-442. doi: 10.1016/j.kint.2016.09.040. Epub 2016 Dec 4.</citation>
    <PMID>27927601</PMID>
  </reference>
  <reference>
    <citation>Wang IK, Wu YY, Yang YF, Ting IW, Lin CC, Yen TH, Chen JH, Wang CH, Huang CC, Lin HC. The effect of probiotics on serum levels of cytokine and endotoxin in peritoneal dialysis patients: a randomised, double-blind, placebo-controlled trial. Benef Microbes. 2015;6(4):423-30. doi: 10.3920/BM2014.0088. Epub 2015 Feb 12.</citation>
    <PMID>25609654</PMID>
  </reference>
  <reference>
    <citation>Salmean YA, Segal MS, Palii SP, Dahl WJ. Fiber supplementation lowers plasma p-cresol in chronic kidney disease patients. J Ren Nutr. 2015 May;25(3):316-20. doi: 10.1053/j.jrn.2014.09.002. Epub 2014 Nov 5.</citation>
    <PMID>25446837</PMID>
  </reference>
  <reference>
    <citation>Xie LM, Ge YY, Huang X, Zhang YQ, Li JX. Effects of fermentable dietary fiber supplementation on oxidative and inflammatory status in hemodialysis patients. Int J Clin Exp Med. 2015 Jan 15;8(1):1363-9. eCollection 2015.</citation>
    <PMID>25785138</PMID>
  </reference>
  <reference>
    <citation>Poesen R, Evenepoel P, de Loor H, Delcour JA, Courtin CM, Kuypers D, Augustijns P, Verbeke K, Meijers B. The Influence of Prebiotic Arabinoxylan Oligosaccharides on Microbiota Derived Uremic Retention Solutes in Patients with Chronic Kidney Disease: A Randomized Controlled Trial. PLoS One. 2016 Apr 21;11(4):e0153893. doi: 10.1371/journal.pone.0153893. eCollection 2016.</citation>
    <PMID>27100399</PMID>
  </reference>
  <reference>
    <citation>Viramontes-Horner D, Marquez-Sandoval F, Martin-del-Campo F, Vizmanos-Lamotte B, Sandoval-Rodriguez A, Armendariz-Borunda J, Garcia-Bejarano H, Renoirte-Lopez K, Garcia-Garcia G. Effect of a symbiotic gel (Lactobacillus acidophilus + Bifidobacterium lactis + inulin) on presence and severity of gastrointestinal symptoms in hemodialysis patients. J Ren Nutr. 2015 May;25(3):284-91. doi: 10.1053/j.jrn.2014.09.008. Epub 2014 Nov 6.</citation>
    <PMID>25455039</PMID>
  </reference>
  <reference>
    <citation>Cruz-Mora J, Martinez-Hernandez NE, Martin del Campo-Lopez F, Viramontes-Horner D, Vizmanos-Lamotte B, Munoz-Valle JF, Garcia-Garcia G, Parra-Rojas I, Castro-Alarcon N. Effects of a symbiotic on gut microbiota in Mexican patients with end-stage renal disease. J Ren Nutr. 2014 Sep;24(5):330-5. doi: 10.1053/j.jrn.2014.05.006. Epub 2014 Jul 22.</citation>
    <PMID>25066654</PMID>
  </reference>
  <reference>
    <citation>Rossi M, Johnson DW, Morrison M, Pascoe EM, Coombes JS, Forbes JM, Szeto CC, McWhinney BC, Ungerer JP, Campbell KL. Synbiotics Easing Renal Failure by Improving Gut Microbiology (SYNERGY): A Randomized Trial. Clin J Am Soc Nephrol. 2016 Feb 5;11(2):223-31. doi: 10.2215/CJN.05240515. Epub 2016 Jan 15.</citation>
    <PMID>26772193</PMID>
  </reference>
  <verification_date>December 2018</verification_date>
  <study_first_submitted>May 31, 2018</study_first_submitted>
  <study_first_submitted_qc>December 6, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 10, 2018</study_first_posted>
  <last_update_submitted>December 6, 2018</last_update_submitted>
  <last_update_submitted_qc>December 6, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">December 10, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Unidad de Investigacion Medica en Enfermedades Renales</investigator_affiliation>
    <investigator_full_name>Alfonso Martín Cueto Manzano</investigator_full_name>
    <investigator_title>Head of the Biomedical Research Unit 02</investigator_title>
  </responsible_party>
  <keyword>dialysis</keyword>
  <keyword>uremic toxin</keyword>
  <keyword>inflammation</keyword>
  <keyword>prebiotics</keyword>
  <keyword>probiotics</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Kidney Failure, Chronic</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03770611
org study id: UIMER003
nct id: NCT03770611
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
End-stage renal disease (ESRD) is a world public health problem, with high morbidity and
      mortality. Cardiovascular disease is the main cause of mortality in ESRD; uremic toxin
      retention and inflammation are considered non-traditional risk factors, as they have an
      active role in atherosclerosis and vascular calcification pathogenesis in dialysis patients.

      Uremic toxins may be generated by internal protein metabolism, however, some toxins that
      can't be efficiently eliminated by dialysis such as indoxyl sulphate and p-cresyl sulphate
      (protein bound toxins), are generated by the microbial metabolism in the large intestine by
      proteolytic bacteria, and may diffuse easily through the intestinal lumen, as a leaky gut
      characterizes kidney disease.

      The gut has been recognized as a potential source of inflammation in ESRD patients;
      accumulation of nitrogen compounds, presence of gastrointestinal symptoms, dietary changes
      and multiple drugs and supplements use, stimulates microbiota alterations as bacterial
      overgrowth and translocation. These phenomena, may active the immune system, promoting local
      and systemic inflammation, which in turn has negative effects increasing endothelial
      dysfunction, muscle catabolism, insulin and erythropoietin resistance, and decreases
      appetite.

      Some methods have been proposed to decrease inflammation and uremic toxin accumulation, as
      more efficient dialysis and anti-inflammatory drugs; however, some of them have limited
      efficacy and high cost. Nutritional treatments focused on modifying intestinal environment,
      as pre- and probiotics have promising effects by altering production and absorption of uremic
      toxins and decreasing inflammation; nevertheless, there is scarce information regarding its
      use and their role in ESRD, particularly in peritoneal dialysis, which is a widely used
      therapy in México. Furthermore, there is no clinical study comparing the effectiveness of
      prebiotics, probiotics, and symbiotics on serum concentrations of uremic toxins and
      inflammation in ESRD patients. It is possible that the administration of a nutritional
      supplement of probiotics and/or prebiotics decreases the serum concentrations of uremic
      toxins and inflammation markers in ESRD patients on automated peritoneal dialysis compared to
      placebo.
Objective:

      The aim of the present study is to evaluate and to compare the effect of a nutritional
      supplement of probiotics and/or prebiotics on serum concentrations of uremic toxins and
      inflammatory markers compared to placebo, in automated peritoneal dialysis patients.

      Sample size:

      For the sample size calculation a mean differences formula was used, with a 95% confidence
      level, a 80% sample power and accuracy of 0.05. As a reference, the study of Salmean YA, 2015
      was considered; in this study, the administration of pea fiber + inulin during 12 weeks in
      chronic kidney disease patients, significantly decreased (p<0.05) serum concentrations of
      p-cresol (5.82 ± 1.72 mg/L) in comparison to placebo (7.25 ± 1.74 mg/L). After substituting
      formula values and adding 20% of possible losses during follow-up, the sample size is: 28
      patients.

      Additionally, sample size calculation was made considering other outcomes. In the study of
      Xie LN, 2015, the administration of high-fermentable soluble fiber in ESRD patients on
      hemodialysis during 6 weeks, significantly decreased (p<0.05) inflammation markers:
      C-reactive protein (CRP), tumour necrosis factor alpha (TNFa) and interleukin 6 (IL-6) (4.8 ±
      4.5 pg/mL, 10.1 ± 1.4 pg/mL, 31.8 ± 5.3 mg/L, respectively) compared to control group (9.5 ±
      5.6 pg/mL, 13.1 ± 2.4 pg/mL, 51.5 ± 14.6 mg/L). After substituting the formula, sample size
      was 19, 7, and 5 for CRP, TNFa and IL-6, respectively.

      Thus, the highest value was finally used: 28 patients for intervention group.

      Statistical analysis:

      Quantitative variables will be shown as mean and standard deviation or median (25-75
      percentiles) according to their parametric or non-parametric distribution; Qualitative
      variables will be shown as frequency and percentage. Intergroup comparisons will be performed
      with χ2 or Fisher test for qualitative variables and one-way ANOVA or Kruskal-Wallis test for
      quantitative variables as appropriate. For intra-group comparisons Mc Nemar test will be used
      for qualitative variables and paired T-test, Wilcoxon, repeated-measures or Friedman ANOVA
      for quantitative variables as appropriate. An intention to treat analysis will be performed.
allocation: Randomized
intervention model: Factorial Assignment
intervention model description: Parallel assignment, patients in automated peritoneal dialysis will be randomly assigned to one of the four intervention groups: probiotic, prebiotic, symbiotic and placebo
primary purpose: Treatment
masking: Triple (Participant, Care Provider, Investigator)
masking description: Patient Blinding: Patients in automated peritoneal dialysis will be blinded to the intervention they will receive. Evaluator Blinding: The principal investigator and the Doctorate program student will be blinded to the intervention that patients will receive (probiotic, prebiotic, symbiotic or placebo).
Care providers will be blinded to the intervention groups.
measure: Change of uremic toxins from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Measurement of serum concentrations of the uremic toxins p-cresyl sulphate (mg/dL) and indoxyl sulphate (mg/dL) by means of liquid chromatography.
measure: Change of uremic toxins from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Measurement of serum concentrations of endotoxin (EU/mL) by means of Limulus amebocyte lisate test.
measure: Change in gut microbiota composition from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Determination of fecal bacterial composition by DNA extraction and pyrosequencing analysis.
measure: Change in gastrointestinal symptoms from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Measurement of appetite and frequency and severity of gastrointestinal symptoms (nausea, vomiting, bloating, diarrhea, constipation) by means of a gastrointestinal symptoms questionnaire.
measure: Change of inflammatory cytokines from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Measurement of serum concentrations of inflammatory cytokines Interleukin-6 (pg/mL), Interleukin-10 (pg/mL) and Tumor Necrosis Factor alpha (pg/mL) by means of ELISA.
measure: Change of inflammatory cytokines from basal to 1 and 3 months
time frame: Baseline, 1 month and 3 months
description: Measurement of serum concentrations of C-Reactive Protein (mg/L) by means of nephelometry.
arm group label: Probiotic
arm group type: Active Comparator
description: Subjects receiving probiotic supplementation: 2x108 CFU probiotic bacteria + prebiotic placebo per day during 3 months
arm group label: Prebiotic
arm group type: Active Comparator
description: Subjects receiving prebiotic supplementation: 20 g of prebiotic fiber + probiotic placebo per day during 3 months
arm group label: Symbiotic
arm group type: Experimental
description: Subjects receiving probiotic and prebiotic supplementation: 2x108 CFU probiotic bacteria + 20 g of prebiotic fiber per day during 3 months
arm group label: Placebo
arm group type: Placebo Comparator
description: Subjects receiving placebo of probiotic and prebiotic per day during 3 months
intervention type: Dietary Supplement
intervention name: Probiotic
description: The probiotic supplement is composed of the following bacterial strains: Bacillus coagulans, Bacillus subtilis, Bifidobacterium (B) bifidum, B. breve, B. longum, Lactobacillus (L) acidophilus, L. brevis, L. casei, L. helveticus, L. Paracasei, L plantarum, L. rhamnosus, L. salivarus, Lactococcus lactis, Pediococcus acidilactici, Pediococcus parvulus, Weisella confusa, Weisella paramesenteroides
arm group label: Probiotic
intervention type: Dietary Supplement
intervention name: Prebiotic
description: The prebiotic fiber is Agave inulin
arm group label: Prebiotic
intervention type: Dietary Supplement
intervention name: Symbiotic
description: The supplement is a combination of the probiotic product + the prebiotic fiber
arm group label: Symbiotic
intervention type: Dietary Supplement
intervention name: Placebo
description: The supplement is a combination of probiotic placebo and prebiotic fiber placebo. Placebo will consist on maltodextrin for both cases.
arm group label: Placebo
criteria: 
gender: All
minimum age: 18 Years
maximum age: 80 Years
healthy volunteers: No
last name: Alfonso M Cueto-Manzano, PhD
phone: 52 (33) 38097269
email: a_cueto_manzano@hotmail.com
last name: Fabiola Martín-del-Campo, MSc
phone: 52 (33) 10711190
email: fabi_mc@hotmail.com
facility: 
contact: 
investigator: 
investigator: 
country: Mexico
url: https://www.usrds.org/2017/view/Default.aspx
description: United States Renal Data Sytem. 2016 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases. Bethesda, MD, 2016.
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PMID: 22626821
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PMID: 28146081
citation: Ito S, Yoshida M. Protein-bound uremic toxins: new culprits of cardiovascular events in chronic kidney disease patients. Toxins (Basel). 2014 Feb 20;6(2):665-78. doi: 10.3390/toxins6020665.
PMID: 24561478
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PMID: 23258127
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PMID: 20093818
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PMID: 21160227
citation: Lin CJ, Wu V, Wu PC, Wu CJ. Meta-Analysis of the Associations of p-Cresyl Sulfate (PCS) and Indoxyl Sulfate (IS) with Cardiovascular Events and All-Cause Mortality in Patients with Chronic Renal Failure. PLoS One. 2015 Jul 14;10(7):e0132589. doi: 10.1371/journal.pone.0132589. eCollection 2015.
PMID: 26173073
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PMID: 27927601
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PMID: 25609654
citation: Salmean YA, Segal MS, Palii SP, Dahl WJ. Fiber supplementation lowers plasma p-cresol in chronic kidney disease patients. J Ren Nutr. 2015 May;25(3):316-20. doi: 10.1053/j.jrn.2014.09.002. Epub 2014 Nov 5.
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responsible party type: Principal Investigator
investigator affiliation: Unidad de Investigacion Medica en Enfermedades Renales
investigator full name: Alfonso Martín Cueto Manzano
investigator title: Head of the Biomedical Research Unit 02
mesh term: Kidney Failure, Chronic
sharing ipd: Undecided