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Predicting out-of-office blood pressure in the clinic (PROOF-BP): derivation and validation of a tool to improve the accuracy of blood pressure measurement in clinical practice

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1161/HYPERTENSIONAHA.115.07108

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Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Role:
Author
ORCID:
0000-0002-9258-4060


More from this funder
Funding agency for:
Sheppard, JP
Grant:
RP-PG-1209–10051
More from this funder
Funding agency for:
Sheppard, JP
McManus, RJ
Hobbs, FDR
Williams, B
Grant:
RP-PG-1209–10051


Publisher:
American Heart Association
Journal:
Hypertension More from this journal
Volume:
67
Issue:
5
Pages:
940-951
Publication date:
2016-03-21
Acceptance date:
2016-02-03
DOI:
EISSN:
1524-4563
ISSN:
0194-911X


Language:
English
Keywords:
Pubs id:
pubs:598673
UUID:
uuid:92b64e75-ca77-4dd4-a910-8df19f158e97
Local pid:
pubs:598673
Source identifiers:
598673
Deposit date:
2016-02-03
ARK identifier:

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