Hypertension Clinical Trial
Official title:
ACtivity Trackers to ImproVe Blood Pressure: a Pilot Study
NCT number | NCT03325426 |
Other study ID # | 16-18605 |
Secondary ID | |
Status | Completed |
Phase | N/A |
First received | |
Last updated | |
Start date | June 1, 2017 |
Est. completion date | January 1, 2021 |
Verified date | March 2024 |
Source | University of California, San Francisco |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The study aims to determine if use of physical activity trackers coupled with provider feedback will increase awareness of young adults of their physical fitness and improve blood pressure levels. The goal of this pilot study is feasibility, with a secondary goal of examining potential effect sizes for planning purposes for a larger randomized controlled trial.
Status | Completed |
Enrollment | 63 |
Est. completion date | January 1, 2021 |
Est. primary completion date | January 1, 2021 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 8 Years to 30 Years |
Eligibility | Inclusion Criteria: - ages 8-30 receiving anti-hypertensive therapy at the time of recruitment. - diabetes, non-dialysis requiring chronic kidney disease, kidney transplant, or other etiologies of hypertension - have phones compatible for wireless device (FitBitsĀ©) data transmission Exclusion Criteria: - history of decompensated congestive heart failure - pregnant - cognitive impairment - unable to perform physical activity - BP >180/110 mm Hg - prisoners - contraindication to use or wear of home activity tracker (such as allergy to activity tracker band) - presence of any co-morbidity that would preclude physical activity - actively using physical activity tracking devices prior to the study will be excluded. |
Country | Name | City | State |
---|---|---|---|
United States | University of California, San Francisco | San Francisco | California |
Lead Sponsor | Collaborator |
---|---|
University of California, San Francisco |
United States,
Agarwal R, Bills JE, Hecht TJ, Light RP. Role of home blood pressure monitoring in overcoming therapeutic inertia and improving hypertension control: a systematic review and meta-analysis. Hypertension. 2011 Jan;57(1):29-38. doi: 10.1161/HYPERTENSIONAHA.110.160911. Epub 2010 Nov 29. — View Citation
Akber A, Portale AA, Johansen KL. Pedometer-assessed physical activity in children and young adults with CKD. Clin J Am Soc Nephrol. 2012 May;7(5):720-6. doi: 10.2215/CJN.06330611. Epub 2012 Mar 15. — View Citation
Akber A, Portale AA, Johansen KL. Use of pedometers to increase physical activity among children and adolescents with chronic kidney disease. Pediatr Nephrol. 2014 Aug;29(8):1395-402. doi: 10.1007/s00467-014-2787-6. Epub 2014 Mar 20. — View Citation
Applebaum MA, Lawson EF, von Scheven E. Perception of transition readiness and preferences for use of technology in transition programs: teens' ideas for the future. Int J Adolesc Med Health. 2013;25(2):119-25. doi: 10.1515/ijamh-2013-0019. — View Citation
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Flynn JT, Daniels SR, Hayman LL, Maahs DM, McCrindle BW, Mitsnefes M, Zachariah JP, Urbina EM; American Heart Association Atherosclerosis, Hypertension and Obesity in Youth Committee of the Council on Cardiovascular Disease in the Young. Update: ambulatory blood pressure monitoring in children and adolescents: a scientific statement from the American Heart Association. Hypertension. 2014 May;63(5):1116-35. doi: 10.1161/HYP.0000000000000007. Epub 2014 Mar 3. No abstract available. — View Citation
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Logan AG, McIsaac WJ, Tisler A, Irvine MJ, Saunders A, Dunai A, Rizo CA, Feig DS, Hamill M, Trudel M, Cafazzo JA. Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. Am J Hypertens. 2007 Sep;20(9):942-8. doi: 10.1016/j.amjhyper.2007.03.020. — View Citation
Mohammed J, Deda L, Clarson CL, Stein RI, Cuerden MS, Mahmud FH. Assessment of habitual physical activity in adolescents with type 1 diabetes. Can J Diabetes. 2014 Aug;38(4):250-5. doi: 10.1016/j.jcjd.2014.05.010. — View Citation
Negri C, Bacchi E, Morgante S, Soave D, Marques A, Menghini E, Muggeo M, Bonora E, Moghetti P. Supervised walking groups to increase physical activity in type 2 diabetic patients. Diabetes Care. 2010 Nov;33(11):2333-5. doi: 10.2337/dc10-0877. — View Citation
Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN, Jones DW, Kurtz T, Sheps SG, Roccella EJ. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Circulation. 2005 Feb 8;111(5):697-716. doi: 10.1161/01.CIR.0000154900.76284.F6. — View Citation
Takacs J, Pollock CL, Guenther JR, Bahar M, Napier C, Hunt MA. Validation of the Fitbit One activity monitor device during treadmill walking. J Sci Med Sport. 2014 Sep;17(5):496-500. doi: 10.1016/j.jsams.2013.10.241. Epub 2013 Oct 31. — View Citation
Ting TV, Kudalkar D, Nelson S, Cortina S, Pendl J, Budhani S, Neville J, Taylor J, Huggins J, Drotar D, Brunner HI. Usefulness of cellular text messaging for improving adherence among adolescents and young adults with systemic lupus erythematosus. J Rheumatol. 2012 Jan;39(1):174-9. doi: 10.3899/jrheum.110771. Epub 2011 Nov 15. — View Citation
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* Note: There are 15 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Change in Mean Office Systolic BP | Change in mean systolic BP is modeled using all blood pressure data points collected between baseline and month 12 to provide an average change over time, accounting for repeated values from patients using a mixed linear regression approach. | Between baseline and month 12 | |
Primary | Change in Mean Office Systolic BP | Change in mean systolic BP using blood pressure data points collected between baseline and month 6 to provide an average change over time | Between baseline and month 6 | |
Secondary | Number of Participants Retained | Rate of study participant retention | Months 0-12 | |
Secondary | Change in Weight (Z-score) | Weights were measured in clinic using a standardized scale. Z score of 0 represents the population mean. A z-score of +1.96 represents the 95th percentile of weight and -1.96 represents the 5th percentile of weight. Change in weight (z-score) is modeled using all weight data points collected between baseline and month 12 to provide an average change over time accounting for repeated values from patients using a mixed linear regression approach. | Months 0-12 |
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