A proposed algorithm for diagnosing hypertension using automated office blood pressure measurement

J Hypertens. 2010 Apr;28(4):703-8. doi: 10.1097/HJH.0b013e328335d091.

Abstract

Objective: To validate an algorithm for the interpretation of automated office blood pressure (AOBP) measurement based upon data from untreated patients referred by physicians in the community for 24-h ambulatory blood pressure monitoring (ABPM).

Methods: An algorithm for interpreting AOBP readings was developed taking into account the previously documented equivalence of AOBP and mean awake ambulatory BP (ABP; mmHg), which were each classified as optimum BP (<130/80), borderline BP (130-139/80-89) and hypertension (>or=140/90). This classification was applied to data derived from 254 untreated patients undergoing 24-h ABPM, AOBP and routine manual BP taken at the patient's own family physician's office.

Results: The mean awake ABP (135.3 +/- 12.4/81.0 +/- 10.2) was similar to the mean AOBP (132.6 +/- 17.4/80.0 +/- 11.1) with both values being significantly (P < 0.001) lower than the routine manual BP (149.7 +/- 15.2/89.3 +/- 9.5). Of the 69 patients with a systolic AOBP at least 140, only five (7.3%) exhibited white-coat hypertension with a normal mean awake ambulatory systolic BP less than 130. Similarly, of the 47 patients with a diastolic AOBP at least 90, none had optimum BP (diastolic BP < 80 mmHg on ABPM). White-coat hypertension was significantly (P = 0.005/P = 0.006) more prevalent for systolic/diastolic BP (22.1%/13.4%) when routine, manual BP readings were analysed.

Conclusion: In contrast to routine manual office BP, a diagnosis of hypertension by AOBP is unlikely to be associated with an optimum awake ABP.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Algorithms*
  • Blood Pressure / physiology*
  • Blood Pressure Monitoring, Ambulatory
  • Female
  • Humans
  • Hypertension / diagnosis*
  • Hypertension / physiopathology
  • Male
  • Middle Aged
  • Office Automation*
  • Systole