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Hawaii J Med Public Health ; 76(11): 314-317, 2017 11.
Article in English | MEDLINE | ID: mdl-29164016

ABSTRACT

Hypertension is one of the leading causes of death and disability worldwide. Blood pressure reduction and control are associated with reduced risk of stroke and cardiovascular disease. To achieve optimal reduction and control, reliable and valid methods for blood pressure measurement are needed. Office based measurements can result in 'white coat' hypertension, which is when a patient's blood pressure in a clinical setting is higher than in other settings, or 'masked' hypertension, which occurs when a patient's blood pressure is normal in a clinical setting, but elevated outside the clinical setting. In 2015, the US Preventative Services Task Force recommended Ambulatory Blood Pressure Monitoring (ABPM) as the "best method" for measuring blood pressure, endorsing its use both for confirming the diagnosis of hypertension and for excluding 'white coat' hypertension. ABPM is a safe, painless and non-invasive test wherein patients wear a small digital blood pressure machine attached to a belt around their body and connected to a cuff around their upper arm that enables multiple automated blood pressure measurements at designated intervals (typically every 15 to 30 minutes) throughout the day and night for a specified period (eg, 24 hours). Patients can go about their typical daily activities wearing the device as much as possible, except when they are bathing, showering, or engaging in heavy exercise. Given the importance of blood pressure monitoring and control to population public health, this article provides details on the relevance and challenges of blood pressure measurement broadly then describes ABPM generally and specifically in the Hawai'i context.


Subject(s)
Blood Pressure Monitoring, Ambulatory/statistics & numerical data , Blood Pressure Monitoring, Ambulatory/standards , Guideline Adherence/statistics & numerical data , Hawaii , Humans , Hypertension/diagnosis , Practice Guidelines as Topic/standards , Practice Patterns, Physicians'/statistics & numerical data
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