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

Background: Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure (BP) readings compared to clinic measurements, resulting in misdiagnosis and suboptimal management of hypertension. The present study assessed whether BP and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic BP readings (the ‘home-clinic difference’).

Methods and results: A linear regression model predicting the home-clinic BP difference was derived in two datasets measuring automated clinic and ambulatory/home BP (n=991) using candidate predictors identified from a literature review. The model was validated in four further datasets (n=1,172) using Area Under the Receiver Operator Characteristic curve (AUROC) analysis. A masked effect was associated with male sex, a positive clinic BP change (difference between consecutive BP readings during a single visit) and a diagnosis of hypertension. Increasing age, clinic BP level and pulse pressure were associated with a white coat effect. The model showed good calibration across datasets (Pearson’s correlation 0.48-0.80) and performed well predicting ambulatory hypertension (AUROC 0.75, 95%CI 0.72-0.79 [systolic]; 0.87, 95%CI 0.85-0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient’s BP status compared with other guideline recommended approaches (PROOF-BP 93% [92-95%] classified correctly; US 73% [70-75%]; Canada 74% [71-77%]; UK 78% [76-81%]).

Conclusions: Patient characteristics from a single clinic visit can accurately predict a patient’s ambulatory BP. Utilisation of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment.