Title |
Understanding short-term blood-pressure-variability phenotypes: from concept to clinical practice
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Published in |
International Journal of General Medicine, June 2018
|
DOI | 10.2147/ijgm.s164903 |
Pubmed ID | |
Authors |
Veerendra Melagireppa Chadachan, Min Tun Ye, Jam Chin Tay, Kannan Subramaniam, Sajita Setia |
Abstract |
Clinic blood pressure (BP) is recognized as the gold standard for the screening, diagnosis, and management of hypertension. However, optimal diagnosis and successful management of hypertension cannot be achieved exclusively by a handful of conventionally acquired BP readings. It is critical to estimate the magnitude of BP variability by estimating and quantifying each individual patient's specific BP variations. Short-term BP variability or exaggerated circadian BP variations that occur within a day are associated with increased cardiovascular events, mortality and target-organ damage. Popular concepts of BP variability, including "white-coat hypertension" and "masked hypertension", are well recognized in clinical practice. However, nocturnal hypertension, morning surge, and morning hypertension are also important phenotypes of short-term BP variability that warrant attention, especially in the primary-care setting. In this review, we try to theorize and explain these phenotypes to ensure they are better understood and recognized in day-to-day clinical practice. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 50% |
India | 2 | 14% |
Philippines | 1 | 7% |
Canada | 1 | 7% |
Cyprus | 1 | 7% |
Unknown | 2 | 14% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 86% |
Practitioners (doctors, other healthcare professionals) | 2 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 134 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 21 | 16% |
Student > Bachelor | 13 | 10% |
Researcher | 12 | 9% |
Student > Postgraduate | 10 | 7% |
Student > Master | 7 | 5% |
Other | 20 | 15% |
Unknown | 51 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 31 | 23% |
Engineering | 13 | 10% |
Nursing and Health Professions | 7 | 5% |
Neuroscience | 4 | 3% |
Agricultural and Biological Sciences | 3 | 2% |
Other | 17 | 13% |
Unknown | 59 | 44% |