Title |
Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP)
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Published in |
Hypertension, March 2016
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DOI | 10.1161/hypertensionaha.115.07108 |
Pubmed ID | |
Authors |
James P Sheppard, Richard Stevens, Paramjit Gill, Una Martin, Marshall Godwin, Janet Hanley, Carl Heneghan, F D Richard Hobbs, Jonathan Mant, Brian McKinstry, Martin Myers, David Nunan, Alison Ward, Bryan Williams, Richard J McManus |
Abstract |
Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure readings compared with clinic measurements, resulting in misdiagnosis of hypertension. The present study assessed whether blood pressure and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic blood pressure readings (the home-clinic difference). A linear regression model predicting the home-clinic blood pressure difference was derived in 2 data sets measuring automated clinic and ambulatory/home blood pressure (n=991) using candidate predictors identified from a literature review. The model was validated in 4 further data sets (n=1172) using area under the receiver operator characteristic curve analysis. A masked effect was associated with male sex, a positive clinic blood pressure change (difference between consecutive measurements during a single visit), and a diagnosis of hypertension. Increasing age, clinic blood pressure level, and pulse pressure were associated with a white coat effect. The model showed good calibration across data sets (Pearson correlation, 0.48-0.80) and performed well-predicting ambulatory hypertension (area under the receiver operator characteristic curve, 0.75; 95% confidence interval, 0.72-0.79 [systolic]; 0.87; 0.85-0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient's blood pressure status compared with other guideline recommended approaches (93% [92% to 95%] classified correctly; United States, 73% [70% to 75%]; Canada, 74% [71% to 77%]; United Kingdom, 78% [76% to 81%]). This study demonstrates that patient characteristics from a single clinic visit can accurately predict a patient's ambulatory blood pressure. Usage of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment. |
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United States | 3 | 14% |
Canada | 2 | 10% |
Unknown | 7 | 33% |
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Scientists | 6 | 29% |
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Mendeley readers
Geographical breakdown
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Kenya | 1 | 1% |
Switzerland | 1 | 1% |
Brazil | 1 | 1% |
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Researcher | 11 | 14% |
Student > Ph. D. Student | 10 | 13% |
Professor | 6 | 8% |
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Other | 16 | 21% |
Unknown | 13 | 17% |
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Computer Science | 2 | 3% |
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Other | 8 | 11% |
Unknown | 22 | 29% |