<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/NCT03785418</url>
  </required_header>
  <id_info>
    <org_study_id>6022511</org_study_id>
    <nct_id>NCT03785418</nct_id>
  </id_info>
  <brief_title>Lifestyle Modification for the Treatment of Symptomatic Atrial Fibrillation (LIFE-AF)</brief_title>
  <acronym>LIFE-AF</acronym>
  <official_title>Lifestyle Modification for the Treatment of Symptomatic Atrial Fibrillation - A Pilot Study - The LIFE-AF Trial</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Dr. Benedict Glover</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Abbott</agency>
      <agency_class>Industry</agency_class>
    </collaborator>
    <collaborator>
      <agency>University of Toronto</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Queen's University</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>
      The purpose of this study is to evaluate the effectiveness of a lifestyle modification&#xD;
      intervention focused on healthy eating, regular exercise and behavioural therapy to decrease&#xD;
      the length and number of atrial fibrillation episodes as well as gain an understanding of the&#xD;
      impact of these changes on the gut microbiome.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Proposed research:&#xD;
&#xD;
      This pilot study will evaluate the potential efficacy and feasibility of risk factor&#xD;
      modification in patients with a known history of symptomatic paroxysmal and persistent AFIB&#xD;
      (in sinus rhythm) by implementing current evidence-based lifestyle recommendations as well as&#xD;
      gain an understanding of the impact of these changes in the gut microbiome.&#xD;
&#xD;
      Objectives:&#xD;
&#xD;
      This study aims to determine if a multicomponent risk factor modification intervention&#xD;
      (dietary intervention, exercise regimen and behavioural therapy) implemented using a basic&#xD;
      healthcare team reduces the burden of AFIB at 12 months by decreasing the length and number&#xD;
      of AFIB episodes. This study aims to assess the impact of these interventions on AFIB-related&#xD;
      symptoms, quality of life and rhythm status (documented on an implantable loop recorder&#xD;
      [ILR]).This study aims to examine the gut microbiota and identify potential organisms which&#xD;
      may be present in higher concentrations in patients with an elevated BMI and AFIB and how&#xD;
      these organism levels may alter with dietary changes.&#xD;
&#xD;
      Study Design:&#xD;
&#xD;
      Baseline Screening &amp; Follow-Up Assessments and Procedures:&#xD;
&#xD;
      As part of our current clinical practice, all participants will undergo a clinical assessment&#xD;
      which includes a 12-lead ECG and BP (this will be repeated at all follow-up visits: 1, 3, 6,&#xD;
      and 12 months). Demographic data and body composition measurements (i.e. waist circumference)&#xD;
      will also be obtained from participants' medical charts or from each participant directly.&#xD;
      Screening for Diabetes mellitus, hyperlipidemia, obstructive sleep apnea and hypertension&#xD;
      will also be completed at the first baseline visit.&#xD;
&#xD;
      If not checked within the prior 6 months, all participants will have a baseline blood sample&#xD;
      drawn at the first baseline visit to test for baseline sodium (Na), potassium (K), urea,&#xD;
      creatinine, free thyroxine (T4) and thyroid stimulating hormone (TSH) (this will be repeated&#xD;
      at 12 months). HbA1C (prediabetes/Diabetes mellitus testing) and a fasting lipid profile&#xD;
      (hyperlipidemia testing) will also be measured at baseline and repeated at 12 months if&#xD;
      applicable (i.e. HbA1C in those with prediabetes or Diabetes mellitus and a fasting lipid&#xD;
      profile in those with hyperlipidemia).&#xD;
&#xD;
      If not performed within the past 12 months, all participants will undergo a baseline&#xD;
      transthoracic echocardiogram (TTE). A follow-up TTE will be repeated at the 12-month visit.&#xD;
&#xD;
      AFIB: At the first baseline visit and all follow-up visits, AFIB-related symptom burden&#xD;
      (using the AFSS - Appendix I) and quality of life (using the AFEQT - Appendix II) will be&#xD;
      assessed. All participants will undergo implantation of an implantable loop recorder (ILR) at&#xD;
      their first baseline visit (Appendix VIII). This device will continually record the&#xD;
      participants' heart rate and rhythm for a period of 12 months and will record any episodes of&#xD;
      AFIB. These data will be downloaded by a technician during each follow-up visit (1, 3, 6, and&#xD;
      12 months) and stored in a secure manner. Principal and Co-Investigators will be blinded to&#xD;
      these data. The ILR will be removed from participants during their final follow-up visit (at&#xD;
      12 months).&#xD;
&#xD;
      Apple Watch: All participants will be supplied with an Apple Watch in order to monitor their&#xD;
      levels of physical activity (i.e. step counts and physical activity duration). For this&#xD;
      reason, participants are required to own/have daily access to (i.e. provided by the research&#xD;
      team) an iPhone to sync with the Apple Watch. The watch will be integrated with 2 apps&#xD;
      (Cardiogram and Lose It) to record and keep track of physical activity, caloric intake and&#xD;
      will also monitor heart rate. Participants will be trained on the use of the watch and apps.&#xD;
      Participants will also be instructed to put this watch on first thing in the morning and not&#xD;
      remove it until the evening when heading to bed throughout the duration of the trial.&#xD;
      Participants will be asked to send data from the apps to the research team by email on a&#xD;
      weekly basis. Participants will be asked to return the Apple Watch at their final follow-up&#xD;
      visit (at 12 months).&#xD;
&#xD;
      Physical activity: Physical activity levels will be assessed using the IPAQ and MESA TWPAS&#xD;
      Questionnaire at the first baseline visit. These questionnaires will also be administered at&#xD;
      all follow-up visits (1, 3, 6, and 12 months). Participants will be asked to share data from&#xD;
      the Cardiogram app with the research team on a weekly basis.&#xD;
&#xD;
      Diet: The diets of all participants will be evaluated at the first baseline visit and&#xD;
      follow-ups (1, 3, 6, and 12 months) using the Mediterranean Diet Score Tool. Participants&#xD;
      will be asked to enter all food consumed into the Lose It app each day and send this&#xD;
      information to the research team on a weekly basis. Only participants in the intervention&#xD;
      group will be provided with the Mediterranean Diet Handout at baseline.&#xD;
&#xD;
      Gut microbiota: Participants will be provided with and trained on the use of &quot;Poop&quot; Kits.&#xD;
      Stool samples will be collected (2nd baseline visit and at 1, 3, 6, and 12 months) and&#xD;
      immediately stored at -80°C in Zymo collection devices. This deactivates active pathogens and&#xD;
      preserves DNA for future extraction. Analyses will occur in the Centre for the Analysis of&#xD;
      Genome Evolution and Function (CAGEF) at the University of Toronto, directed by Professor&#xD;
      David Guttman. Microbial DNA will then be extracted from the frozen fecal samples and the 16S&#xD;
      rRNA gene will be amplified. Analyses will be performed to determine levels of specific&#xD;
      metabolites that have been strongly correlated to obesity and metabolic syndrome, namely&#xD;
      monosaccharides and short-chain fatty acids (SCFAs).&#xD;
&#xD;
      Randomization: A randomization schedule will be prepared by the data coordinating centre at&#xD;
      Queens University, Kingston, Ontario using a computerized random number-generator. Random&#xD;
      allocation will be determined by a participant randomization software application (Dacima&#xD;
      Software Inc., IWRS: Interactive Web Response System). Participants will be randomized on a&#xD;
      1:1 fashion between active intervention and control.&#xD;
&#xD;
      Experimental arm: Multicomponent Risk Factor Modification Baseline - 12 months: Active&#xD;
      Lifestyle Intervention Participants in this intervention group will undergo the baseline and&#xD;
      follow-up assessments described earlier. The specific components of the experimental arm will&#xD;
      be tailored to the needs of the participants at their baseline visit for the study.&#xD;
      Throughout the trial, participants in this group will be called weekly by a member of the&#xD;
      research team to review and discuss each component of the lifestyle intervention (diet,&#xD;
      exercise, and behavioural therapy). Details of each component are explained below.&#xD;
&#xD;
      Diet will be assessed (at baseline and all follow-up visits) using the Mediterranean Diet&#xD;
      Score Tool (a 14-item questionnaire of adherence to the specified diet).Nutrition&#xD;
      prescription will be based on a Mediterranean-style diet and individualized based on the&#xD;
      participant's current weight and diet practices to optimize adherence. The diet will be&#xD;
      comprised of recommended daily intakes of 50% carbohydrates, 35% unsaturated fats, and 15%&#xD;
      protein. At baseline, basic information will be provided in written format using the&#xD;
      Mediterranean Diet Handout. Data from the individuals' Apple Watches will be monitored and&#xD;
      analyzed throughout the trial in order to assess compliance with these recommendations. Each&#xD;
      participant will receive feedback and advice from the research assistant during weekly&#xD;
      telephone sessions to motivate participants to make healthy changes to their diet in line&#xD;
      with the Mediterranean Diet recommendations. Personal individual recommendations for changes&#xD;
      to be introduced in the participant's diet in order to achieve a personalized goal. Research&#xD;
      personnel will highlight the advantages of following this diet as opposed to the risks of not&#xD;
      adhering to it. This approach has been successful in previous studies where behavioural&#xD;
      intervention was used to help participants quit smoking.&#xD;
&#xD;
      Physical activity levels will be assessed (at baseline and all follow-up visits) using the&#xD;
      IPAQ and MESA TWPAS. Exercise prescription was selected by investigators based on a recently&#xD;
      published Harvard Medical School Health Report 'Starting to Exercise'. This report recommends&#xD;
      individuals to perform 150 minutes of moderate aerobic exercise per week (equal to &gt;30&#xD;
      minutes/day, most days of the week). Data from the individuals' Apple Watches will be&#xD;
      monitored and analyzed throughout the trial in order to assess compliance with these&#xD;
      recommendations. Each participant will receive feedback and advice from the research&#xD;
      assistant during weekly telephone sessions to motivate participants to gradually achieve&#xD;
      higher levels of physical activity. Participants will be invited to attend an optional&#xD;
      exercise class in which they walk along an indoor walking track for 60 minutes biweekly at&#xD;
      Providence Care Hospital, supervised by a research assistant and monitored by a medically&#xD;
      qualified Co-Investigator.&#xD;
&#xD;
      Comprehensive lifestyle intervention will include a structured behavioural change program&#xD;
      that includes regular self-monitoring of food intake, by entering all food consumed into the&#xD;
      Lose It app, which automatically calculates caloric intake, and physical activity. The&#xD;
      qualified research assistant will facilitate participant engagement sessions by telephone on&#xD;
      a weekly basis. During each session, the research assistant will assess the participant's&#xD;
      current level of adherence to the diet and exercise recommendations and will motivate them to&#xD;
      gradually achieve higher levels of exercise following the Harvard Medical School Health&#xD;
      Report and to make healthy adjustments to their diet following the Mediterranean Diet&#xD;
      Handout.&#xD;
&#xD;
      Control arm: Baseline - 12 months: Standard Clinical Practice In addition to receiving&#xD;
      standard of care AFIB treatment, participants in the control arm of this trial will undergo&#xD;
      all of the same baseline screening and follow-up assessments and procedures as the&#xD;
      intervention arm but will receive no lifestyle intervention (no diet, exercise regimen, or&#xD;
      behavioural therapy).&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">October 29, 2018</start_date>
  <completion_date type="Anticipated">July 2020</completion_date>
  <primary_completion_date type="Anticipated">July 2020</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>Parallel Assignment</intervention_model>
    <intervention_model_description>A randomization schedule will be prepared by the data coordinating centre at Queen's University, Kingston, Ontario using a computerized random number-generator. Random allocation will be determined by a patient randomization software application. Participants will be randomized on a 1:1 fashion between active intervention and control.</intervention_model_description>
    <primary_purpose>Treatment</primary_purpose>
    <masking>Single (Outcomes Assessor)</masking>
    <masking_description>Data downloaded from the participants' implantable loop recorders will not be available to the investigators nor anyone involved in direct patient interaction in the study. A blinded event committee composed of three physicians with a specialization in cardiology, who are not directly involved in the research study, will have access to this data.</masking_description>
  </study_design_info>
  <primary_outcome>
    <measure>Changes in AFIB-related symptom burden</measure>
    <time_frame>baseline to 1, 3, 6 and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention on AFIB-related symptom burden as measured by the University of Toronto AFIB Severity Scale (AFSS) scores at 1, 3, 6, and 12 months. This is a validated scale (range, 3.25 [single minimally symptomatic episode lasting minutes] to 30 [continuous highly symptomatic episode lasting &gt;48hours]) which encompasses 3 domains of atrial fibrillation: event frequency (scored 1-10), duration (scored 1.25-10), and global episode severity (scored 1-10).</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in AFIB burden</measure>
    <time_frame>baseline to 1, 3, 6, and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention on AFIB burden as documented from implantable loop recorders at 1, 3, 6 and 12 months. We will document the change in the number of AFIB episodes. This will be monitored by the ILR recording device where any episode of AFIB over 30 seconds will count as 1 episode. The AFIB events recorded by the device will be adjudicated for accuracy using 2 raters.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in Quality of Life based on Treatment Concerns and Daily Activity</measure>
    <time_frame>baseline to 1, 3, 6, and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on quality of life at 1, 3, 6, and 12-months using the Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) questionnaire. This assesses treatment concerns and daily activity.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Combined incidence of stroke, myocardial infarction and hospitalization</measure>
    <time_frame>12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention on a composite end-point at 12 months (combined stroke, myocardial infarction and hospitalization). This information will be collected from hospital records.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in levels of monosaccharides in the gut microbiota</measure>
    <time_frame>baseline to 12 months</time_frame>
    <description>Identification of the gastrointestinal microbiota composition at baseline and dysbiosis at 12 months as a result of dietary intervention. Microbial DNA will be extracted from fecal samples, 16S rRNA genes will be amplified, and analyses will be performed to determine levels of monosaccharides in the gut microbiota at baseline and at 12 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in levels of short-chain fatty acids in the gut microbiota</measure>
    <time_frame>baseline to 12 months</time_frame>
    <description>Identification of the gastrointestinal microbiota composition at baseline and dysbiosis at 12 months as a result of dietary intervention. Microbial DNA will be extracted from fecal samples, 16S rRNA genes will be amplified, and analyses will be performed to determine levels of short-chain fatty acids in the gut microbiota at baseline and at 12 months.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Change in weight</measure>
    <time_frame>baseline to 1, 3, 6 and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention on weight changes relative to weight measured at baseline.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Adherence to the lifestyle intervention physical activity recommendations using IPAQ</measure>
    <time_frame>1, 3, 6 and 12 months</time_frame>
    <description>To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the International Physical Activity Questionnaire (IPAQ) Short Last 7 Days Self-Administered Format at 1, 3, 6, and 12 months.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in Physical Activity Levels Based on Step-Counts</measure>
    <time_frame>1, 3, 6, and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on 1-, 3-, 6-, and 12-month physical activity levels measured using the Apple Watch step counts per week.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Adherence to the lifestyle intervention physical activity recommendations using MESA TWPAS</measure>
    <time_frame>1, 3, 6 and 12 months</time_frame>
    <description>To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the Multi-Ethnic Study of Atherosclerosis (MESA) Typical Week Physical Activity Survey (TWPAS) at 1, 3, 6, and 12 months.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Adherence to the lifestyle intervention diet recommendations</measure>
    <time_frame>1, 3, 6 and 12 months</time_frame>
    <description>To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the Mediterranean Diet Score Tool, a validated 14-item Questionnaire of Mediterranean diet adherence at 1, 3, 6, and 12 months.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes in Physical Activity Levels Based on Duration (minutes) of Physical Activity</measure>
    <time_frame>1, 3, 6, and 12 months</time_frame>
    <description>To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on 1-, 3-, 6-, and 12-month physical activity levels measured using the Apple Watch duration (minutes) of physical activity per week.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">60</enrollment>
  <condition>Atrial Fibrillation</condition>
  <arm_group>
    <arm_group_label>Experimental Arm</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Multicomponent Risk Factor Modification Intervention focused on healthy eating, regular exercise and behavioural therapy</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control Arm</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Standard Clinical Practice</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Multicomponent Risk Factor Modification</intervention_name>
    <description>Healthy eating, regular exercise and behavioural therapy.</description>
    <arm_group_label>Experimental Arm</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  paroxysmal or persistent AFIB (in sinus rhythm at the time of randomization)&#xD;
&#xD;
          -  BMI &gt; 30 kg/m^2 or a waist circumference greater than 100 cm (male) or 90 cm (female)&#xD;
&#xD;
          -  have daily access to an iPhone&#xD;
&#xD;
          -  have at least one of the following risk factors:hypertension, diabetes or&#xD;
             pre-diabetes, hyperlipidemia, smoker, obstructive sleep apnea&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Permanent AFIB (AFIB lasting &gt; 1 year)&#xD;
&#xD;
          -  Prior or actively on waiting list for catheter ablation for AFIB&#xD;
&#xD;
          -  History of unstable angina not corrected with revascularization&#xD;
&#xD;
          -  Left ventricular ejection fraction &lt;30%&#xD;
&#xD;
          -  Left atrial size &gt;5.5 cm&#xD;
&#xD;
          -  New York Heart Association (NYHA) classification IV heart failure&#xD;
&#xD;
          -  Moderate or severe cardiac valvular lesion (stenosis or regurgitation) on&#xD;
             echocardiography or valvular lesion requiring intervention.&#xD;
&#xD;
          -  Participation in a cardiac rehabilitation program within the last year&#xD;
&#xD;
          -  Serious underlying psychiatric disorder: e.g. eating disorder, severe psychotic&#xD;
             disorder with recent (3 month) hospitalization or psychiatric illness requiring&#xD;
             supervised care precluding full independent function.&#xD;
&#xD;
          -  Participants who are unable or unwilling to provide fully informed consent.&#xD;
&#xD;
          -  Currently performing exercise training 150 minutes/week of moderate to vigorous&#xD;
             physical activity&#xD;
&#xD;
          -  Gastrointestinal malabsorption disorder: A previously diagnosed gastrointestinal&#xD;
             malabsorption disorder interfering with macro or micronutrient absorption.&#xD;
&#xD;
          -  If receiving warfarin and unstable international normalized ratio (INR) defined as&#xD;
             persistently outside of the therapeutic range (2.0-3.0) for greater than 14&#xD;
             consecutive days.&#xD;
&#xD;
          -  Other non-cardiovascular medical conditions making 1-year survival unlikely.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Benedict M Glover, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Queen's University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Christopher Simpson, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Queen's Unviersity</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Christopher Simpson, MD</last_name>
    <phone>6135496666</phone>
    <phone_ext>3804</phone_ext>
    <email>simpsonc@kgh.kari.net</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Milena A Bullen, BScH</last_name>
    <phone>6135496666</phone>
    <phone_ext>7304</phone_ext>
    <email>12mb98@queensu.ca</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Kingston Health Sciences Centre</name>
      <address>
        <city>Kingston</city>
        <state>Ontario</state>
        <zip>K7L2V7</zip>
        <country>Canada</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Christopher Simpson, MD</last_name>
      <phone>6135496666</phone>
      <phone_ext>3804</phone_ext>
      <email>simpsonc@kgh.kari.net</email>
    </contact>
    <contact_backup>
      <last_name>Milena A Bullen, BScH</last_name>
      <phone>6135496666</phone>
      <phone_ext>7304</phone_ext>
      <email>12mb98@queensu.ca</email>
    </contact_backup>
    <investigator>
      <last_name>Christopher Simpson, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
    <investigator>
      <last_name>Benedict M Glover, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
    <investigator>
      <last_name>Sanoj Chacko, MD</last_name>
      <role>Sub-Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>Canada</country>
  </location_countries>
  <link>
    <url>https://www.mayoclinic.org/tests-procedures/implantable-loop-recorder/pyc-20384986</url>
    <description>Implantable Loop Recorder description from the Mayo Clinic</description>
  </link>
  <reference>
    <citation>Chugh SS, Havmoeller R, Narayanan K, Singh D, Rienstra M, Benjamin EJ, Gillum RF, Kim YH, McAnulty JH Jr, Zheng ZJ, Forouzanfar MH, Naghavi M, Mensah GA, Ezzati M, Murray CJ. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014 Feb 25;129(8):837-47. doi: 10.1161/CIRCULATIONAHA.113.005119. Epub 2013 Dec 17.</citation>
    <PMID>24345399</PMID>
  </reference>
  <reference>
    <citation>Miyasaka Y, Barnes ME, Gersh BJ, Cha SS, Bailey KR, Abhayaratna WP, Seward JB, Tsang TS. Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence. Circulation. 2006 Jul 11;114(2):119-25. doi: 10.1161/CIRCULATIONAHA.105.595140. Epub 2006 Jul 3. Erratum In: Circulation. 2006 Sep 12;114(11):e498.</citation>
    <PMID>16818816</PMID>
  </reference>
  <reference>
    <citation>Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991 Aug;22(8):983-8. doi: 10.1161/01.str.22.8.983.</citation>
    <PMID>1866765</PMID>
  </reference>
  <reference>
    <citation>Fuster V, Ryden LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, Halperin JL, Kay GN, Le Huezey JY, Lowe JE, Olsson SB, Prystowsky EN, Tamargo JL, Wann LS, Smith SC Jr, Priori SG, Estes NA 3rd, Ezekowitz MD, Jackman WM, January CT, Lowe JE, Page RL, Slotwiner DJ, Stevenson WG, Tracy CM, Jacobs AK, Anderson JL, Albert N, Buller CE, Creager MA, Ettinger SM, Guyton RA, Halperin JL, Hochman JS, Kushner FG, Ohman EM, Stevenson WG, Tarkington LG, Yancy CW; American College of Cardiology Foundation/American Heart Association Task Force. 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2011 Mar 15;123(10):e269-367. doi: 10.1161/CIR.0b013e318214876d. Epub 2011 Mar 7. No abstract available.</citation>
    <PMID>21382897</PMID>
  </reference>
  <reference>
    <citation>Lau DH, Nattel S, Kalman JM, Sanders P. Modifiable Risk Factors and Atrial Fibrillation. Circulation. 2017 Aug 8;136(6):583-596. doi: 10.1161/CIRCULATIONAHA.116.023163.</citation>
    <PMID>28784826</PMID>
  </reference>
  <reference>
    <citation>Lavie CJ, Pandey A, Lau DH, Alpert MA, Sanders P. Obesity and Atrial Fibrillation Prevalence, Pathogenesis, and Prognosis: Effects of Weight Loss and Exercise. J Am Coll Cardiol. 2017 Oct 17;70(16):2022-2035. doi: 10.1016/j.jacc.2017.09.002.</citation>
    <PMID>29025560</PMID>
  </reference>
  <reference>
    <citation>Nalliah CJ, Sanders P, Kalman JM. Obesity and atrial fibrillation outcomes and risk: Increasing the weight of evidence. Heart Rhythm. 2017 Jun;14(6):828-829. doi: 10.1016/j.hrthm.2017.03.013. Epub 2017 Mar 15. No abstract available.</citation>
    <PMID>28315404</PMID>
  </reference>
  <reference>
    <citation>Dublin S, French B, Glazer NL, Wiggins KL, Lumley T, Psaty BM, Smith NL, Heckbert SR. Risk of new-onset atrial fibrillation in relation to body mass index. Arch Intern Med. 2006 Nov 27;166(21):2322-8. doi: 10.1001/archinte.166.21.2322.</citation>
    <PMID>17130384</PMID>
  </reference>
  <reference>
    <citation>Guijian L, Jinchuan Y, Rongzeng D, Jun Q, Jun W, Wenqing Z. Impact of body mass index on atrial fibrillation recurrence: a meta-analysis of observational studies. Pacing Clin Electrophysiol. 2013 Jun;36(6):748-56. doi: 10.1111/pace.12106. Epub 2013 Feb 25.</citation>
    <PMID>23437987</PMID>
  </reference>
  <reference>
    <citation>Wong CX, Ganesan AN, Selvanayagam JB. Epicardial fat and atrial fibrillation: current evidence, potential mechanisms, clinical implications, and future directions. Eur Heart J. 2017 May 1;38(17):1294-1302. doi: 10.1093/eurheartj/ehw045.</citation>
    <PMID>26935271</PMID>
  </reference>
  <reference>
    <citation>Pathak RK, Middeldorp ME, Meredith M, Mehta AB, Mahajan R, Wong CX, Twomey D, Elliott AD, Kalman JM, Abhayaratna WP, Lau DH, Sanders P. Long-Term Effect of Goal-Directed Weight Management in an Atrial Fibrillation Cohort: A Long-Term Follow-Up Study (LEGACY). J Am Coll Cardiol. 2015 May 26;65(20):2159-69. doi: 10.1016/j.jacc.2015.03.002. Epub 2015 Mar 16.</citation>
    <PMID>25792361</PMID>
  </reference>
  <reference>
    <citation>Abed HS, Wittert GA, Leong DP, Shirazi MG, Bahrami B, Middeldorp ME, Lorimer MF, Lau DH, Antic NA, Brooks AG, Abhayaratna WP, Kalman JM, Sanders P. Effect of weight reduction and cardiometabolic risk factor management on symptom burden and severity in patients with atrial fibrillation: a randomized clinical trial. JAMA. 2013 Nov 20;310(19):2050-60. doi: 10.1001/jama.2013.280521.</citation>
    <PMID>24240932</PMID>
  </reference>
  <reference>
    <citation>Beto JA, Schury KA, Bansal VK. Strategies to promote adherence to nutritional advice in patients with chronic kidney disease: a narrative review and commentary. Int J Nephrol Renovasc Dis. 2016 Feb 2;9:21-33. doi: 10.2147/IJNRD.S76831. eCollection 2016.</citation>
    <PMID>26893578</PMID>
  </reference>
  <reference>
    <citation>Tesfaye S, Chaturvedi N, Eaton SE, Ward JD, Manes C, Ionescu-Tirgoviste C, Witte DR, Fuller JH; EURODIAB Prospective Complications Study Group. Vascular risk factors and diabetic neuropathy. N Engl J Med. 2005 Jan 27;352(4):341-50. doi: 10.1056/NEJMoa032782.</citation>
    <PMID>15673800</PMID>
  </reference>
  <reference>
    <citation>Dimmer C, Tavernier R, Gjorgov N, Van Nooten G, Clement DL, Jordaens L. Variations of autonomic tone preceding onset of atrial fibrillation after coronary artery bypass grafting. Am J Cardiol. 1998 Jul 1;82(1):22-5. doi: 10.1016/s0002-9149(98)00231-8.</citation>
    <PMID>9671003</PMID>
  </reference>
  <reference>
    <citation>Dublin S, Glazer NL, Smith NL, Psaty BM, Lumley T, Wiggins KL, Page RL, Heckbert SR. Diabetes mellitus, glycemic control, and risk of atrial fibrillation. J Gen Intern Med. 2010 Aug;25(8):853-8. doi: 10.1007/s11606-010-1340-y. Epub 2010 Apr 20.</citation>
    <PMID>20405332</PMID>
  </reference>
  <reference>
    <citation>Di Carli MF, Bianco-Batlles D, Landa ME, Kazmers A, Groehn H, Muzik O, Grunberger G. Effects of autonomic neuropathy on coronary blood flow in patients with diabetes mellitus. Circulation. 1999 Aug 24;100(8):813-9. doi: 10.1161/01.cir.100.8.813.</citation>
    <PMID>10458716</PMID>
  </reference>
  <reference>
    <citation>Sacre JW, Franjic B, Jellis CL, Jenkins C, Coombes JS, Marwick TH. Association of cardiac autonomic neuropathy with subclinical myocardial dysfunction in type 2 diabetes. JACC Cardiovasc Imaging. 2010 Dec;3(12):1207-15. doi: 10.1016/j.jcmg.2010.09.014.</citation>
    <PMID>21163448</PMID>
  </reference>
  <reference>
    <citation>Pop-Busui R, Kirkwood I, Schmid H, Marinescu V, Schroeder J, Larkin D, Yamada E, Raffel DM, Stevens MJ. Sympathetic dysfunction in type 1 diabetes: association with impaired myocardial blood flow reserve and diastolic dysfunction. J Am Coll Cardiol. 2004 Dec 21;44(12):2368-74. doi: 10.1016/j.jacc.2004.09.033.</citation>
    <PMID>15607400</PMID>
  </reference>
  <reference>
    <citation>Chung MK, Martin DO, Sprecher D, Wazni O, Kanderian A, Carnes CA, Bauer JA, Tchou PJ, Niebauer MJ, Natale A, Van Wagoner DR. C-reactive protein elevation in patients with atrial arrhythmias: inflammatory mechanisms and persistence of atrial fibrillation. Circulation. 2001 Dec 11;104(24):2886-91. doi: 10.1161/hc4901.101760.</citation>
    <PMID>11739301</PMID>
  </reference>
  <reference>
    <citation>Ajala O, English P, Pinkney J. Systematic review and meta-analysis of different dietary approaches to the management of type 2 diabetes. Am J Clin Nutr. 2013 Mar;97(3):505-16. doi: 10.3945/ajcn.112.042457. Epub 2013 Jan 30.</citation>
    <PMID>23364002</PMID>
  </reference>
  <reference>
    <citation>Mitsou EK, Kakali A, Antonopoulou S, Mountzouris KC, Yannakoulia M, Panagiotakos DB, Kyriacou A. Adherence to the Mediterranean diet is associated with the gut microbiota pattern and gastrointestinal characteristics in an adult population. Br J Nutr. 2017 Jun;117(12):1645-1655. doi: 10.1017/S0007114517001593.</citation>
    <PMID>28789729</PMID>
  </reference>
  <reference>
    <citation>Schiffrin EL, Campbell NR, Feldman RD, Kaczorowski J, Lewanczuk R, Padwal R, Tobe SW. Hypertension in Canada: Past, Present, and Future. Ann Glob Health. 2016 Mar-Apr;82(2):288-99. doi: 10.1016/j.aogh.2016.02.006.</citation>
    <PMID>27372532</PMID>
  </reference>
  <reference>
    <citation>Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003 May 21;289(19):2560-72. doi: 10.1001/jama.289.19.2560. Epub 2003 May 14. Erratum In: JAMA. 2003 Jul 9;290(2):197.</citation>
    <PMID>12748199</PMID>
  </reference>
  <reference>
    <citation>McAlister FA, Wilkins K, Joffres M, Leenen FH, Fodor G, Gee M, Tremblay MS, Walker R, Johansen H, Campbell N. Changes in the rates of awareness, treatment and control of hypertension in Canada over the past two decades. CMAJ. 2011 Jun 14;183(9):1007-13. doi: 10.1503/cmaj.101767. Epub 2011 May 16.</citation>
    <PMID>21576297</PMID>
  </reference>
  <reference>
    <citation>Pathak RK, Middeldorp ME, Lau DH, Mehta AB, Mahajan R, Twomey D, Alasady M, Hanley L, Antic NA, McEvoy RD, Kalman JM, Abhayaratna WP, Sanders P. Aggressive risk factor reduction study for atrial fibrillation and implications for the outcome of ablation: the ARREST-AF cohort study. J Am Coll Cardiol. 2014 Dec 2;64(21):2222-31. doi: 10.1016/j.jacc.2014.09.028. Epub 2014 Nov 24.</citation>
    <PMID>25456757</PMID>
  </reference>
  <reference>
    <citation>Moore SC, Patel AV, Matthews CE, Berrington de Gonzalez A, Park Y, Katki HA, Linet MS, Weiderpass E, Visvanathan K, Helzlsouer KJ, Thun M, Gapstur SM, Hartge P, Lee IM. Leisure time physical activity of moderate to vigorous intensity and mortality: a large pooled cohort analysis. PLoS Med. 2012;9(11):e1001335. doi: 10.1371/journal.pmed.1001335. Epub 2012 Nov 6.</citation>
    <PMID>23139642</PMID>
  </reference>
  <reference>
    <citation>Hunter GR, Kekes-Szabo T, Snyder SW, Nicholson C, Nyikos I, Berland L. Fat distribution, physical activity, and cardiovascular risk factors. Med Sci Sports Exerc. 1997 Mar;29(3):362-9. doi: 10.1097/00005768-199703000-00011.</citation>
    <PMID>9139175</PMID>
  </reference>
  <reference>
    <citation>Papaetis GS, Papakyriakou P, Panagiotou TN. Central obesity, type 2 diabetes and insulin: exploring a pathway full of thorns. Arch Med Sci. 2015 Jun 19;11(3):463-82. doi: 10.5114/aoms.2015.52350.</citation>
    <PMID>26170839</PMID>
  </reference>
  <reference>
    <citation>Goto C, Higashi Y, Kimura M, Noma K, Hara K, Nakagawa K, Kawamura M, Chayama K, Yoshizumi M, Nara I. Effect of different intensities of exercise on endothelium-dependent vasodilation in humans: role of endothelium-dependent nitric oxide and oxidative stress. Circulation. 2003 Aug 5;108(5):530-5. doi: 10.1161/01.CIR.0000080893.55729.28. Epub 2003 Jul 21.</citation>
    <PMID>12874192</PMID>
  </reference>
  <reference>
    <citation>Yang MH, Kang SY, Lee JA, Kim YS, Sung EJ, Lee KY, Kim JS, Oh HJ, Kang HC, Lee SY. The Effect of Lifestyle Changes on Blood Pressure Control among Hypertensive Patients. Korean J Fam Med. 2017 Jul;38(4):173-180. doi: 10.4082/kjfm.2017.38.4.173. Epub 2017 Jul 20. Erratum In: Korean J Fam Med. 2017 Sep;38(5):311-312.</citation>
    <PMID>28775806</PMID>
  </reference>
  <reference>
    <citation>Otto ME, Belohlavek M, Romero-Corral A, Gami AS, Gilman G, Svatikova A, Amin RS, Lopez-Jimenez F, Khandheria BK, Somers VK. Comparison of cardiac structural and functional changes in obese otherwise healthy adults with versus without obstructive sleep apnea. Am J Cardiol. 2007 May 1;99(9):1298-302. doi: 10.1016/j.amjcard.2006.12.052. Epub 2007 Mar 20.</citation>
    <PMID>17478161</PMID>
  </reference>
  <reference>
    <citation>Colish J, Walker JR, Elmayergi N, Almutairi S, Alharbi F, Lytwyn M, Francis A, Bohonis S, Zeglinski M, Kirkpatrick IDC, Sharma S, Jassal DS. Obstructive sleep apnea: effects of continuous positive airway pressure on cardiac remodeling as assessed by cardiac biomarkers, echocardiography, and cardiac MRI. Chest. 2012 Mar;141(3):674-681. doi: 10.1378/chest.11-0615. Epub 2011 Aug 11.</citation>
    <PMID>21835901</PMID>
  </reference>
  <reference>
    <citation>Patel D, Mohanty P, Di Biase L, Shaheen M, Lewis WR, Quan K, Cummings JE, Wang P, Al-Ahmad A, Venkatraman P, Nashawati E, Lakkireddy D, Schweikert R, Horton R, Sanchez J, Gallinghouse J, Hao S, Beheiry S, Cardinal DS, Zagrodzky J, Canby R, Bailey S, Burkhardt JD, Natale A. Safety and efficacy of pulmonary vein antral isolation in patients with obstructive sleep apnea: the impact of continuous positive airway pressure. Circ Arrhythm Electrophysiol. 2010 Oct;3(5):445-51. doi: 10.1161/CIRCEP.109.858381. Epub 2010 Aug 5.</citation>
    <PMID>20689107</PMID>
  </reference>
  <reference>
    <citation>Fein AS, Shvilkin A, Shah D, Haffajee CI, Das S, Kumar K, Kramer DB, Zimetbaum PJ, Buxton AE, Josephson ME, Anter E. Treatment of obstructive sleep apnea reduces the risk of atrial fibrillation recurrence after catheter ablation. J Am Coll Cardiol. 2013 Jul 23;62(4):300-5. doi: 10.1016/j.jacc.2013.03.052. Epub 2013 Apr 23.</citation>
    <PMID>23623910</PMID>
  </reference>
  <reference>
    <citation>Canadian Diabetes Association Clinical Practice Guidelines Expert Committee; Imran SA, Rabasa-Lhoret R, Ross S. Targets for glycemic control. Can J Diabetes. 2013 Apr;37 Suppl 1:S31-4. doi: 10.1016/j.jcjd.2013.01.016. Epub 2013 Mar 26. No abstract available.</citation>
    <PMID>24070959</PMID>
  </reference>
  <reference>
    <citation>Parekh PJ, Balart LA, Johnson DA. The Influence of the Gut Microbiome on Obesity, Metabolic Syndrome and Gastrointestinal Disease. Clin Transl Gastroenterol. 2015 Jun 18;6(6):e91. doi: 10.1038/ctg.2015.16.</citation>
    <PMID>26087059</PMID>
  </reference>
  <reference>
    <citation>Di Daniele N, Noce A, Vidiri MF, Moriconi E, Marrone G, Annicchiarico-Petruzzelli M, D'Urso G, Tesauro M, Rovella V, De Lorenzo A. Impact of Mediterranean diet on metabolic syndrome, cancer and longevity. Oncotarget. 2017 Jan 31;8(5):8947-8979. doi: 10.18632/oncotarget.13553.</citation>
    <PMID>27894098</PMID>
  </reference>
  <reference>
    <citation>International Classification of Sleep Disorders: Diagnostic and Coding Manual. 2. Westchester: American Academy of Sleep Medicine; 2005</citation>
  </reference>
  <reference>
    <citation>Harvard Medical School Special Health Reports. (2015). Starting to Exercise. by L. Howard Hartley, I-Min Lee, Harvard Health Publications.</citation>
  </reference>
  <verification_date>December 2018</verification_date>
  <study_first_submitted>December 18, 2018</study_first_submitted>
  <study_first_submitted_qc>December 19, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 24, 2018</study_first_posted>
  <last_update_submitted>December 21, 2018</last_update_submitted>
  <last_update_submitted_qc>December 21, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">December 26, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Queen's University</investigator_affiliation>
    <investigator_full_name>Dr. Benedict Glover</investigator_full_name>
    <investigator_title>Principal Investigator, Chief of Cardiac Arrhythmia Service, Department of Medicine</investigator_title>
  </responsible_party>
  <keyword>Atrial Fibrillation</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Atrial Fibrillation</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/NCT03785418
org study id: 6022511
nct id: NCT03785418
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The purpose of this study is to evaluate the effectiveness of a lifestyle modification
      intervention focused on healthy eating, regular exercise and behavioural therapy to decrease
      the length and number of atrial fibrillation episodes as well as gain an understanding of the
      impact of these changes on the gut microbiome.
Proposed research:

      This pilot study will evaluate the potential efficacy and feasibility of risk factor
      modification in patients with a known history of symptomatic paroxysmal and persistent AFIB
      (in sinus rhythm) by implementing current evidence-based lifestyle recommendations as well as
      gain an understanding of the impact of these changes in the gut microbiome.

      Objectives:

      This study aims to determine if a multicomponent risk factor modification intervention
      (dietary intervention, exercise regimen and behavioural therapy) implemented using a basic
      healthcare team reduces the burden of AFIB at 12 months by decreasing the length and number
      of AFIB episodes. This study aims to assess the impact of these interventions on AFIB-related
      symptoms, quality of life and rhythm status (documented on an implantable loop recorder
      [ILR]).This study aims to examine the gut microbiota and identify potential organisms which
      may be present in higher concentrations in patients with an elevated BMI and AFIB and how
      these organism levels may alter with dietary changes.

      Study Design:

      Baseline Screening & Follow-Up Assessments and Procedures:

      As part of our current clinical practice, all participants will undergo a clinical assessment
      which includes a 12-lead ECG and BP (this will be repeated at all follow-up visits: 1, 3, 6,
      and 12 months). Demographic data and body composition measurements (i.e. waist circumference)
      will also be obtained from participants' medical charts or from each participant directly.
      Screening for Diabetes mellitus, hyperlipidemia, obstructive sleep apnea and hypertension
      will also be completed at the first baseline visit.

      If not checked within the prior 6 months, all participants will have a baseline blood sample
      drawn at the first baseline visit to test for baseline sodium (Na), potassium (K), urea,
      creatinine, free thyroxine (T4) and thyroid stimulating hormone (TSH) (this will be repeated
      at 12 months). HbA1C (prediabetes/Diabetes mellitus testing) and a fasting lipid profile
      (hyperlipidemia testing) will also be measured at baseline and repeated at 12 months if
      applicable (i.e. HbA1C in those with prediabetes or Diabetes mellitus and a fasting lipid
      profile in those with hyperlipidemia).

      If not performed within the past 12 months, all participants will undergo a baseline
      transthoracic echocardiogram (TTE). A follow-up TTE will be repeated at the 12-month visit.

      AFIB: At the first baseline visit and all follow-up visits, AFIB-related symptom burden
      (using the AFSS - Appendix I) and quality of life (using the AFEQT - Appendix II) will be
      assessed. All participants will undergo implantation of an implantable loop recorder (ILR) at
      their first baseline visit (Appendix VIII). This device will continually record the
      participants' heart rate and rhythm for a period of 12 months and will record any episodes of
      AFIB. These data will be downloaded by a technician during each follow-up visit (1, 3, 6, and
      12 months) and stored in a secure manner. Principal and Co-Investigators will be blinded to
      these data. The ILR will be removed from participants during their final follow-up visit (at
      12 months).

      Apple Watch: All participants will be supplied with an Apple Watch in order to monitor their
      levels of physical activity (i.e. step counts and physical activity duration). For this
      reason, participants are required to own/have daily access to (i.e. provided by the research
      team) an iPhone to sync with the Apple Watch. The watch will be integrated with 2 apps
      (Cardiogram and Lose It) to record and keep track of physical activity, caloric intake and
      will also monitor heart rate. Participants will be trained on the use of the watch and apps.
      Participants will also be instructed to put this watch on first thing in the morning and not
      remove it until the evening when heading to bed throughout the duration of the trial.
      Participants will be asked to send data from the apps to the research team by email on a
      weekly basis. Participants will be asked to return the Apple Watch at their final follow-up
      visit (at 12 months).

      Physical activity: Physical activity levels will be assessed using the IPAQ and MESA TWPAS
      Questionnaire at the first baseline visit. These questionnaires will also be administered at
      all follow-up visits (1, 3, 6, and 12 months). Participants will be asked to share data from
      the Cardiogram app with the research team on a weekly basis.

      Diet: The diets of all participants will be evaluated at the first baseline visit and
      follow-ups (1, 3, 6, and 12 months) using the Mediterranean Diet Score Tool. Participants
      will be asked to enter all food consumed into the Lose It app each day and send this
      information to the research team on a weekly basis. Only participants in the intervention
      group will be provided with the Mediterranean Diet Handout at baseline.

      Gut microbiota: Participants will be provided with and trained on the use of "Poop" Kits.
      Stool samples will be collected (2nd baseline visit and at 1, 3, 6, and 12 months) and
      immediately stored at -80°C in Zymo collection devices. This deactivates active pathogens and
      preserves DNA for future extraction. Analyses will occur in the Centre for the Analysis of
      Genome Evolution and Function (CAGEF) at the University of Toronto, directed by Professor
      David Guttman. Microbial DNA will then be extracted from the frozen fecal samples and the 16S
      rRNA gene will be amplified. Analyses will be performed to determine levels of specific
      metabolites that have been strongly correlated to obesity and metabolic syndrome, namely
      monosaccharides and short-chain fatty acids (SCFAs).

      Randomization: A randomization schedule will be prepared by the data coordinating centre at
      Queens University, Kingston, Ontario using a computerized random number-generator. Random
      allocation will be determined by a participant randomization software application (Dacima
      Software Inc., IWRS: Interactive Web Response System). Participants will be randomized on a
      1:1 fashion between active intervention and control.

      Experimental arm: Multicomponent Risk Factor Modification Baseline - 12 months: Active
      Lifestyle Intervention Participants in this intervention group will undergo the baseline and
      follow-up assessments described earlier. The specific components of the experimental arm will
      be tailored to the needs of the participants at their baseline visit for the study.
      Throughout the trial, participants in this group will be called weekly by a member of the
      research team to review and discuss each component of the lifestyle intervention (diet,
      exercise, and behavioural therapy). Details of each component are explained below.

      Diet will be assessed (at baseline and all follow-up visits) using the Mediterranean Diet
      Score Tool (a 14-item questionnaire of adherence to the specified diet).Nutrition
      prescription will be based on a Mediterranean-style diet and individualized based on the
      participant's current weight and diet practices to optimize adherence. The diet will be
      comprised of recommended daily intakes of 50% carbohydrates, 35% unsaturated fats, and 15%
      protein. At baseline, basic information will be provided in written format using the
      Mediterranean Diet Handout. Data from the individuals' Apple Watches will be monitored and
      analyzed throughout the trial in order to assess compliance with these recommendations. Each
      participant will receive feedback and advice from the research assistant during weekly
      telephone sessions to motivate participants to make healthy changes to their diet in line
      with the Mediterranean Diet recommendations. Personal individual recommendations for changes
      to be introduced in the participant's diet in order to achieve a personalized goal. Research
      personnel will highlight the advantages of following this diet as opposed to the risks of not
      adhering to it. This approach has been successful in previous studies where behavioural
      intervention was used to help participants quit smoking.

      Physical activity levels will be assessed (at baseline and all follow-up visits) using the
      IPAQ and MESA TWPAS. Exercise prescription was selected by investigators based on a recently
      published Harvard Medical School Health Report 'Starting to Exercise'. This report recommends
      individuals to perform 150 minutes of moderate aerobic exercise per week (equal to >30
      minutes/day, most days of the week). Data from the individuals' Apple Watches will be
      monitored and analyzed throughout the trial in order to assess compliance with these
      recommendations. Each participant will receive feedback and advice from the research
      assistant during weekly telephone sessions to motivate participants to gradually achieve
      higher levels of physical activity. Participants will be invited to attend an optional
      exercise class in which they walk along an indoor walking track for 60 minutes biweekly at
      Providence Care Hospital, supervised by a research assistant and monitored by a medically
      qualified Co-Investigator.

      Comprehensive lifestyle intervention will include a structured behavioural change program
      that includes regular self-monitoring of food intake, by entering all food consumed into the
      Lose It app, which automatically calculates caloric intake, and physical activity. The
      qualified research assistant will facilitate participant engagement sessions by telephone on
      a weekly basis. During each session, the research assistant will assess the participant's
      current level of adherence to the diet and exercise recommendations and will motivate them to
      gradually achieve higher levels of exercise following the Harvard Medical School Health
      Report and to make healthy adjustments to their diet following the Mediterranean Diet
      Handout.

      Control arm: Baseline - 12 months: Standard Clinical Practice In addition to receiving
      standard of care AFIB treatment, participants in the control arm of this trial will undergo
      all of the same baseline screening and follow-up assessments and procedures as the
      intervention arm but will receive no lifestyle intervention (no diet, exercise regimen, or
      behavioural therapy).
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: A randomization schedule will be prepared by the data coordinating centre at Queen's University, Kingston, Ontario using a computerized random number-generator. Random allocation will be determined by a patient randomization software application. Participants will be randomized on a 1:1 fashion between active intervention and control.
primary purpose: Treatment
masking: Single (Outcomes Assessor)
masking description: Data downloaded from the participants' implantable loop recorders will not be available to the investigators nor anyone involved in direct patient interaction in the study. A blinded event committee composed of three physicians with a specialization in cardiology, who are not directly involved in the research study, will have access to this data.
measure: Changes in AFIB-related symptom burden
time frame: baseline to 1, 3, 6 and 12 months
description: To assess the impact of a lifestyle intervention on AFIB-related symptom burden as measured by the University of Toronto AFIB Severity Scale (AFSS) scores at 1, 3, 6, and 12 months. This is a validated scale (range, 3.25 [single minimally symptomatic episode lasting minutes] to 30 [continuous highly symptomatic episode lasting >48hours]) which encompasses 3 domains of atrial fibrillation: event frequency (scored 1-10), duration (scored 1.25-10), and global episode severity (scored 1-10).
measure: Changes in AFIB burden
time frame: baseline to 1, 3, 6, and 12 months
description: To assess the impact of a lifestyle intervention on AFIB burden as documented from implantable loop recorders at 1, 3, 6 and 12 months. We will document the change in the number of AFIB episodes. This will be monitored by the ILR recording device where any episode of AFIB over 30 seconds will count as 1 episode. The AFIB events recorded by the device will be adjudicated for accuracy using 2 raters.
measure: Changes in Quality of Life based on Treatment Concerns and Daily Activity
time frame: baseline to 1, 3, 6, and 12 months
description: To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on quality of life at 1, 3, 6, and 12-months using the Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) questionnaire. This assesses treatment concerns and daily activity.
measure: Combined incidence of stroke, myocardial infarction and hospitalization
time frame: 12 months
description: To assess the impact of a lifestyle intervention on a composite end-point at 12 months (combined stroke, myocardial infarction and hospitalization). This information will be collected from hospital records.
measure: Changes in levels of monosaccharides in the gut microbiota
time frame: baseline to 12 months
description: Identification of the gastrointestinal microbiota composition at baseline and dysbiosis at 12 months as a result of dietary intervention. Microbial DNA will be extracted from fecal samples, 16S rRNA genes will be amplified, and analyses will be performed to determine levels of monosaccharides in the gut microbiota at baseline and at 12 months.
measure: Changes in levels of short-chain fatty acids in the gut microbiota
time frame: baseline to 12 months
description: Identification of the gastrointestinal microbiota composition at baseline and dysbiosis at 12 months as a result of dietary intervention. Microbial DNA will be extracted from fecal samples, 16S rRNA genes will be amplified, and analyses will be performed to determine levels of short-chain fatty acids in the gut microbiota at baseline and at 12 months.
measure: Change in weight
time frame: baseline to 1, 3, 6 and 12 months
description: To assess the impact of a lifestyle intervention on weight changes relative to weight measured at baseline.
measure: Adherence to the lifestyle intervention physical activity recommendations using IPAQ
time frame: 1, 3, 6 and 12 months
description: To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the International Physical Activity Questionnaire (IPAQ) Short Last 7 Days Self-Administered Format at 1, 3, 6, and 12 months.
measure: Changes in Physical Activity Levels Based on Step-Counts
time frame: 1, 3, 6, and 12 months
description: To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on 1-, 3-, 6-, and 12-month physical activity levels measured using the Apple Watch step counts per week.
measure: Adherence to the lifestyle intervention physical activity recommendations using MESA TWPAS
time frame: 1, 3, 6 and 12 months
description: To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the Multi-Ethnic Study of Atherosclerosis (MESA) Typical Week Physical Activity Survey (TWPAS) at 1, 3, 6, and 12 months.
measure: Adherence to the lifestyle intervention diet recommendations
time frame: 1, 3, 6 and 12 months
description: To evaluate the adherence to the lifestyle intervention (multicomponent risk factor modification) as measured using the Mediterranean Diet Score Tool, a validated 14-item Questionnaire of Mediterranean diet adherence at 1, 3, 6, and 12 months.
measure: Changes in Physical Activity Levels Based on Duration (minutes) of Physical Activity
time frame: 1, 3, 6, and 12 months
description: To assess the impact of a lifestyle intervention (multicomponent risk factor modification) on 1-, 3-, 6-, and 12-month physical activity levels measured using the Apple Watch duration (minutes) of physical activity per week.
arm group label: Experimental Arm
arm group type: Experimental
description: Multicomponent Risk Factor Modification Intervention focused on healthy eating, regular exercise and behavioural therapy
arm group label: Control Arm
arm group type: No Intervention
description: Standard Clinical Practice
intervention type: Behavioral
intervention name: Multicomponent Risk Factor Modification
description: Healthy eating, regular exercise and behavioural therapy.
arm group label: Experimental Arm
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Benedict M Glover, MD
role: Principal Investigator
affiliation: Queen's University
last name: Christopher Simpson, MD
role: Principal Investigator
affiliation: Queen's Unviersity
last name: Christopher Simpson, MD
phone: 6135496666
phone ext: 3804
email: simpsonc@kgh.kari.net
last name: Milena A Bullen, BScH
phone: 6135496666
phone ext: 7304
email: 12mb98@queensu.ca
facility: 
status: Recruiting
contact: 
contact backup: 
investigator: 
investigator: 
investigator: 
country: Canada
url: https://www.mayoclinic.org/tests-procedures/implantable-loop-recorder/pyc-20384986
description: Implantable Loop Recorder description from the Mayo Clinic
citation: Chugh SS, Havmoeller R, Narayanan K, Singh D, Rienstra M, Benjamin EJ, Gillum RF, Kim YH, McAnulty JH Jr, Zheng ZJ, Forouzanfar MH, Naghavi M, Mensah GA, Ezzati M, Murray CJ. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014 Feb 25;129(8):837-47. doi: 10.1161/CIRCULATIONAHA.113.005119. Epub 2013 Dec 17.
PMID: 24345399
citation: Miyasaka Y, Barnes ME, Gersh BJ, Cha SS, Bailey KR, Abhayaratna WP, Seward JB, Tsang TS. Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence. Circulation. 2006 Jul 11;114(2):119-25. doi: 10.1161/CIRCULATIONAHA.105.595140. Epub 2006 Jul 3. Erratum In: Circulation. 2006 Sep 12;114(11):e498.
PMID: 16818816
citation: Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991 Aug;22(8):983-8. doi: 10.1161/01.str.22.8.983.
PMID: 1866765
citation: Fuster V, Ryden LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, Halperin JL, Kay GN, Le Huezey JY, Lowe JE, Olsson SB, Prystowsky EN, Tamargo JL, Wann LS, Smith SC Jr, Priori SG, Estes NA 3rd, Ezekowitz MD, Jackman WM, January CT, Lowe JE, Page RL, Slotwiner DJ, Stevenson WG, Tracy CM, Jacobs AK, Anderson JL, Albert N, Buller CE, Creager MA, Ettinger SM, Guyton RA, Halperin JL, Hochman JS, Kushner FG, Ohman EM, Stevenson WG, Tarkington LG, Yancy CW; American College of Cardiology Foundation/American Heart Association Task Force. 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2011 Mar 15;123(10):e269-367. doi: 10.1161/CIR.0b013e318214876d. Epub 2011 Mar 7. No abstract available.
PMID: 21382897
citation: Lau DH, Nattel S, Kalman JM, Sanders P. Modifiable Risk Factors and Atrial Fibrillation. Circulation. 2017 Aug 8;136(6):583-596. doi: 10.1161/CIRCULATIONAHA.116.023163.
PMID: 28784826
citation: Lavie CJ, Pandey A, Lau DH, Alpert MA, Sanders P. Obesity and Atrial Fibrillation Prevalence, Pathogenesis, and Prognosis: Effects of Weight Loss and Exercise. J Am Coll Cardiol. 2017 Oct 17;70(16):2022-2035. doi: 10.1016/j.jacc.2017.09.002.
PMID: 29025560
citation: Nalliah CJ, Sanders P, Kalman JM. Obesity and atrial fibrillation outcomes and risk: Increasing the weight of evidence. Heart Rhythm. 2017 Jun;14(6):828-829. doi: 10.1016/j.hrthm.2017.03.013. Epub 2017 Mar 15. No abstract available.
PMID: 28315404
citation: Dublin S, French B, Glazer NL, Wiggins KL, Lumley T, Psaty BM, Smith NL, Heckbert SR. Risk of new-onset atrial fibrillation in relation to body mass index. Arch Intern Med. 2006 Nov 27;166(21):2322-8. doi: 10.1001/archinte.166.21.2322.
PMID: 17130384
citation: Guijian L, Jinchuan Y, Rongzeng D, Jun Q, Jun W, Wenqing Z. Impact of body mass index on atrial fibrillation recurrence: a meta-analysis of observational studies. Pacing Clin Electrophysiol. 2013 Jun;36(6):748-56. doi: 10.1111/pace.12106. Epub 2013 Feb 25.
PMID: 23437987
citation: Wong CX, Ganesan AN, Selvanayagam JB. Epicardial fat and atrial fibrillation: current evidence, potential mechanisms, clinical implications, and future directions. Eur Heart J. 2017 May 1;38(17):1294-1302. doi: 10.1093/eurheartj/ehw045.
PMID: 26935271
citation: Pathak RK, Middeldorp ME, Meredith M, Mehta AB, Mahajan R, Wong CX, Twomey D, Elliott AD, Kalman JM, Abhayaratna WP, Lau DH, Sanders P. Long-Term Effect of Goal-Directed Weight Management in an Atrial Fibrillation Cohort: A Long-Term Follow-Up Study (LEGACY). J Am Coll Cardiol. 2015 May 26;65(20):2159-69. doi: 10.1016/j.jacc.2015.03.002. Epub 2015 Mar 16.
PMID: 25792361
citation: Abed HS, Wittert GA, Leong DP, Shirazi MG, Bahrami B, Middeldorp ME, Lorimer MF, Lau DH, Antic NA, Brooks AG, Abhayaratna WP, Kalman JM, Sanders P. Effect of weight reduction and cardiometabolic risk factor management on symptom burden and severity in patients with atrial fibrillation: a randomized clinical trial. JAMA. 2013 Nov 20;310(19):2050-60. doi: 10.1001/jama.2013.280521.
PMID: 24240932
citation: Beto JA, Schury KA, Bansal VK. Strategies to promote adherence to nutritional advice in patients with chronic kidney disease: a narrative review and commentary. Int J Nephrol Renovasc Dis. 2016 Feb 2;9:21-33. doi: 10.2147/IJNRD.S76831. eCollection 2016.
PMID: 26893578
citation: Tesfaye S, Chaturvedi N, Eaton SE, Ward JD, Manes C, Ionescu-Tirgoviste C, Witte DR, Fuller JH; EURODIAB Prospective Complications Study Group. Vascular risk factors and diabetic neuropathy. N Engl J Med. 2005 Jan 27;352(4):341-50. doi: 10.1056/NEJMoa032782.
PMID: 15673800
citation: Dimmer C, Tavernier R, Gjorgov N, Van Nooten G, Clement DL, Jordaens L. Variations of autonomic tone preceding onset of atrial fibrillation after coronary artery bypass grafting. Am J Cardiol. 1998 Jul 1;82(1):22-5. doi: 10.1016/s0002-9149(98)00231-8.
PMID: 9671003
citation: Dublin S, Glazer NL, Smith NL, Psaty BM, Lumley T, Wiggins KL, Page RL, Heckbert SR. Diabetes mellitus, glycemic control, and risk of atrial fibrillation. J Gen Intern Med. 2010 Aug;25(8):853-8. doi: 10.1007/s11606-010-1340-y. Epub 2010 Apr 20.
PMID: 20405332
citation: Di Carli MF, Bianco-Batlles D, Landa ME, Kazmers A, Groehn H, Muzik O, Grunberger G. Effects of autonomic neuropathy on coronary blood flow in patients with diabetes mellitus. Circulation. 1999 Aug 24;100(8):813-9. doi: 10.1161/01.cir.100.8.813.
PMID: 10458716
citation: Sacre JW, Franjic B, Jellis CL, Jenkins C, Coombes JS, Marwick TH. Association of cardiac autonomic neuropathy with subclinical myocardial dysfunction in type 2 diabetes. JACC Cardiovasc Imaging. 2010 Dec;3(12):1207-15. doi: 10.1016/j.jcmg.2010.09.014.
PMID: 21163448
citation: Pop-Busui R, Kirkwood I, Schmid H, Marinescu V, Schroeder J, Larkin D, Yamada E, Raffel DM, Stevens MJ. Sympathetic dysfunction in type 1 diabetes: association with impaired myocardial blood flow reserve and diastolic dysfunction. J Am Coll Cardiol. 2004 Dec 21;44(12):2368-74. doi: 10.1016/j.jacc.2004.09.033.
PMID: 15607400
citation: Chung MK, Martin DO, Sprecher D, Wazni O, Kanderian A, Carnes CA, Bauer JA, Tchou PJ, Niebauer MJ, Natale A, Van Wagoner DR. C-reactive protein elevation in patients with atrial arrhythmias: inflammatory mechanisms and persistence of atrial fibrillation. Circulation. 2001 Dec 11;104(24):2886-91. doi: 10.1161/hc4901.101760.
PMID: 11739301
citation: Ajala O, English P, Pinkney J. Systematic review and meta-analysis of different dietary approaches to the management of type 2 diabetes. Am J Clin Nutr. 2013 Mar;97(3):505-16. doi: 10.3945/ajcn.112.042457. Epub 2013 Jan 30.
PMID: 23364002
citation: Mitsou EK, Kakali A, Antonopoulou S, Mountzouris KC, Yannakoulia M, Panagiotakos DB, Kyriacou A. Adherence to the Mediterranean diet is associated with the gut microbiota pattern and gastrointestinal characteristics in an adult population. Br J Nutr. 2017 Jun;117(12):1645-1655. doi: 10.1017/S0007114517001593.
PMID: 28789729
citation: Schiffrin EL, Campbell NR, Feldman RD, Kaczorowski J, Lewanczuk R, Padwal R, Tobe SW. Hypertension in Canada: Past, Present, and Future. Ann Glob Health. 2016 Mar-Apr;82(2):288-99. doi: 10.1016/j.aogh.2016.02.006.
PMID: 27372532
citation: Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003 May 21;289(19):2560-72. doi: 10.1001/jama.289.19.2560. Epub 2003 May 14. Erratum In: JAMA. 2003 Jul 9;290(2):197.
PMID: 12748199
citation: McAlister FA, Wilkins K, Joffres M, Leenen FH, Fodor G, Gee M, Tremblay MS, Walker R, Johansen H, Campbell N. Changes in the rates of awareness, treatment and control of hypertension in Canada over the past two decades. CMAJ. 2011 Jun 14;183(9):1007-13. doi: 10.1503/cmaj.101767. Epub 2011 May 16.
PMID: 21576297
citation: Pathak RK, Middeldorp ME, Lau DH, Mehta AB, Mahajan R, Twomey D, Alasady M, Hanley L, Antic NA, McEvoy RD, Kalman JM, Abhayaratna WP, Sanders P. Aggressive risk factor reduction study for atrial fibrillation and implications for the outcome of ablation: the ARREST-AF cohort study. J Am Coll Cardiol. 2014 Dec 2;64(21):2222-31. doi: 10.1016/j.jacc.2014.09.028. Epub 2014 Nov 24.
PMID: 25456757
citation: Moore SC, Patel AV, Matthews CE, Berrington de Gonzalez A, Park Y, Katki HA, Linet MS, Weiderpass E, Visvanathan K, Helzlsouer KJ, Thun M, Gapstur SM, Hartge P, Lee IM. Leisure time physical activity of moderate to vigorous intensity and mortality: a large pooled cohort analysis. PLoS Med. 2012;9(11):e1001335. doi: 10.1371/journal.pmed.1001335. Epub 2012 Nov 6.
PMID: 23139642
citation: Hunter GR, Kekes-Szabo T, Snyder SW, Nicholson C, Nyikos I, Berland L. Fat distribution, physical activity, and cardiovascular risk factors. Med Sci Sports Exerc. 1997 Mar;29(3):362-9. doi: 10.1097/00005768-199703000-00011.
PMID: 9139175
citation: Papaetis GS, Papakyriakou P, Panagiotou TN. Central obesity, type 2 diabetes and insulin: exploring a pathway full of thorns. Arch Med Sci. 2015 Jun 19;11(3):463-82. doi: 10.5114/aoms.2015.52350.
PMID: 26170839
citation: Goto C, Higashi Y, Kimura M, Noma K, Hara K, Nakagawa K, Kawamura M, Chayama K, Yoshizumi M, Nara I. Effect of different intensities of exercise on endothelium-dependent vasodilation in humans: role of endothelium-dependent nitric oxide and oxidative stress. Circulation. 2003 Aug 5;108(5):530-5. doi: 10.1161/01.CIR.0000080893.55729.28. Epub 2003 Jul 21.
PMID: 12874192
citation: Yang MH, Kang SY, Lee JA, Kim YS, Sung EJ, Lee KY, Kim JS, Oh HJ, Kang HC, Lee SY. The Effect of Lifestyle Changes on Blood Pressure Control among Hypertensive Patients. Korean J Fam Med. 2017 Jul;38(4):173-180. doi: 10.4082/kjfm.2017.38.4.173. Epub 2017 Jul 20. Erratum In: Korean J Fam Med. 2017 Sep;38(5):311-312.
PMID: 28775806
citation: Otto ME, Belohlavek M, Romero-Corral A, Gami AS, Gilman G, Svatikova A, Amin RS, Lopez-Jimenez F, Khandheria BK, Somers VK. Comparison of cardiac structural and functional changes in obese otherwise healthy adults with versus without obstructive sleep apnea. Am J Cardiol. 2007 May 1;99(9):1298-302. doi: 10.1016/j.amjcard.2006.12.052. Epub 2007 Mar 20.
PMID: 17478161
citation: Colish J, Walker JR, Elmayergi N, Almutairi S, Alharbi F, Lytwyn M, Francis A, Bohonis S, Zeglinski M, Kirkpatrick IDC, Sharma S, Jassal DS. Obstructive sleep apnea: effects of continuous positive airway pressure on cardiac remodeling as assessed by cardiac biomarkers, echocardiography, and cardiac MRI. Chest. 2012 Mar;141(3):674-681. doi: 10.1378/chest.11-0615. Epub 2011 Aug 11.
PMID: 21835901
citation: Patel D, Mohanty P, Di Biase L, Shaheen M, Lewis WR, Quan K, Cummings JE, Wang P, Al-Ahmad A, Venkatraman P, Nashawati E, Lakkireddy D, Schweikert R, Horton R, Sanchez J, Gallinghouse J, Hao S, Beheiry S, Cardinal DS, Zagrodzky J, Canby R, Bailey S, Burkhardt JD, Natale A. Safety and efficacy of pulmonary vein antral isolation in patients with obstructive sleep apnea: the impact of continuous positive airway pressure. Circ Arrhythm Electrophysiol. 2010 Oct;3(5):445-51. doi: 10.1161/CIRCEP.109.858381. Epub 2010 Aug 5.
PMID: 20689107
citation: Fein AS, Shvilkin A, Shah D, Haffajee CI, Das S, Kumar K, Kramer DB, Zimetbaum PJ, Buxton AE, Josephson ME, Anter E. Treatment of obstructive sleep apnea reduces the risk of atrial fibrillation recurrence after catheter ablation. J Am Coll Cardiol. 2013 Jul 23;62(4):300-5. doi: 10.1016/j.jacc.2013.03.052. Epub 2013 Apr 23.
PMID: 23623910
citation: Canadian Diabetes Association Clinical Practice Guidelines Expert Committee; Imran SA, Rabasa-Lhoret R, Ross S. Targets for glycemic control. Can J Diabetes. 2013 Apr;37 Suppl 1:S31-4. doi: 10.1016/j.jcjd.2013.01.016. Epub 2013 Mar 26. No abstract available.
PMID: 24070959
citation: Parekh PJ, Balart LA, Johnson DA. The Influence of the Gut Microbiome on Obesity, Metabolic Syndrome and Gastrointestinal Disease. Clin Transl Gastroenterol. 2015 Jun 18;6(6):e91. doi: 10.1038/ctg.2015.16.
PMID: 26087059
citation: Di Daniele N, Noce A, Vidiri MF, Moriconi E, Marrone G, Annicchiarico-Petruzzelli M, D'Urso G, Tesauro M, Rovella V, De Lorenzo A. Impact of Mediterranean diet on metabolic syndrome, cancer and longevity. Oncotarget. 2017 Jan 31;8(5):8947-8979. doi: 10.18632/oncotarget.13553.
PMID: 27894098
citation: International Classification of Sleep Disorders: Diagnostic and Coding Manual. 2. Westchester: American Academy of Sleep Medicine; 2005
citation: Harvard Medical School Special Health Reports. (2015). Starting to Exercise. by L. Howard Hartley, I-Min Lee, Harvard Health Publications.
responsible party type: Sponsor-Investigator
investigator affiliation: Queen's University
investigator full name: Dr. Benedict Glover
investigator title: Principal Investigator, Chief of Cardiac Arrhythmia Service, Department of Medicine
mesh term: Atrial Fibrillation
sharing ipd: Undecided