How Many Blood Pressure Values We Should Use to Predict Out-of-Office Blood Pressure on Proof-Bp Algorithm. Is the More Better Than the Less ?

Abstract

Objective: Compare the performance of 3 or 6 sequential blood pressure (BP) measurements to predict awake BP (ABP) values by Predicting Out of Office Blood Pressure in the clinic (PROOF BP). Design and method: This study is a secondary analysis of published research. A nursey collected clinical characteristics, in all participants, taking six sequential observed BP measurements, with a 1-minute interval (Microlife-BP3BTOA). Also, it was recorded ABPM (DynaMAPA). We selected 426 suspected people having hypertension. We estimated out-of-office BP on an algorithm from first to third BP (PROOF BP 1–3) and fourth to sixth (PROOF BP 4–6). We classified the patients in four BP categories, such as true hypertension (HT), true normotension (NT), masked hypertension (MH), and white coat hypertension (WCT). The office standard average considered the first three measurements as office BP (cut off – 140/90) and ABP as a reference standard, and for ABP and tested BP, the cut off was 135/85. We correctly compared the proportion of classified patients, coefficient of correlation (r), receiver operating characteristic curve (AUC), and Bland–Altman plot. The differences of proportions were evaluated using the chi-square test for media analysis of covariance. Results: Among 446 patients, 40.1% were classified as HT, 17.4% (MH), 11.7% (WCH) and 30.8% (NT), age 43.3 ± 13.3, women (44.6%), white people (67.8%), diabetes (2.6%), dyslipidemia (19.2%), obese (39.9%), body mass index 28. 9 ± 5.3, smokers (8.6%). The algorithm recommended AMBP in 41.07%. The proportion of HT was 40.1% MH 17.4%, WCH 11.7%, and NT 30.8%. The main clinical characteristics were age 43.3 ± 13.3, women (44.6%), white people (67.8%), diabetic (2.6%), dyslipidemia (19.2%), obese (39.9%), body mass index 28. 9 ± 5.3, smokers (8.6%). The mains results are in Table 1. Figure 1 shows a Bland and Altman plot of PROOF BP 1–3 and 4–6 against ABP. Conclusions: In conclusion, this secondary analysis data reinforce that the algorithm correctly classifies the vast majority of hypertensive patients and recommends ABPM in less than half of patients. It also adds that six sequential measurements no longer add accuracy to the ambulatory BP prediction tool.