Lifestyle Modification for the Treatment of Symptomatic Atrial Fibrillation (LIFE-AF) (LIFE-AF)

Lifestyle Modification for the Treatment of Symptomatic Atrial Fibrillation - A Pilot Study - The LIFE-AF Trial

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).

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.

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.

Multicomponent Risk Factor Modification Intervention focused on healthy eating, regular exercise and behavioural therapy

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).

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.

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.

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.

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.

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.

To assess the impact of a lifestyle intervention on weight changes relative to weight measured at baseline.

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.

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.

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.

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.

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.

Inclusion Criteria: paroxysmal or persistent AFIB (in sinus rhythm at the time of randomization) BMI > 30 kg/m^2 or a waist circumference greater than 100 cm (male) or 90 cm (female) have daily access to an iPhone have at least one of the following risk factors:hypertension, diabetes or pre-diabetes, hyperlipidemia, smoker, obstructive sleep apnea Exclusion Criteria: Permanent AFIB (AFIB lasting > 1 year) Prior or actively on waiting list for catheter ablation for AFIB History of unstable angina not corrected with revascularization Left ventricular ejection fraction <30% Left atrial size >5.5 cm New York Heart Association (NYHA) classification IV heart failure Moderate or severe cardiac valvular lesion (stenosis or regurgitation) on echocardiography or valvular lesion requiring intervention. Participation in a cardiac rehabilitation program within the last year Serious underlying psychiatric disorder: e.g. eating disorder, severe psychotic disorder with recent (3 month) hospitalization or psychiatric illness requiring supervised care precluding full independent function. Participants who are unable or unwilling to provide fully informed consent. Currently performing exercise training 150 minutes/week of moderate to vigorous physical activity Gastrointestinal malabsorption disorder: A previously diagnosed gastrointestinal malabsorption disorder interfering with macro or micronutrient absorption. If receiving warfarin and unstable international normalized ratio (INR) defined as persistently outside of the therapeutic range (2.0-3.0) for greater than 14 consecutive days. Other non-cardiovascular medical conditions making 1-year survival unlikely.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

International Classification of Sleep Disorders: Diagnostic and Coding Manual. 2. Westchester: American Academy of Sleep Medicine; 2005

Harvard Medical School Special Health Reports. (2015). Starting to Exercise. by L. Howard Hartley, I-Min Lee, Harvard Health Publications.