Bayesian analysis supports use of ambulatory blood pressure monitors for screening.

ABSTRACT

To assess whether there is a role for ambulatory blood pressure monitoring (ABPM) in screening for hypertension, we conducted Bayesian analysis of office blood pressure (OBP) as a diagnostic "test" in populations with different prior probabilities (PP) of hypertension. OBP was considered a positive test if systolic blood pressure was greater than 140 mm Hg or diastolic pressure was greater than 90 mm Hg. Chosen daytime ABPM cutoffs for a "gold standard" diagnosis of hypertension were systolic pressure of 139 and diastolic pressure of 88 mm Hg. Sensitivity and specificity of OBP were determined in 72 patients with established hypertension (PP = 1). After 3 weeks off therapy, OBP was 168 +/- 3/101 +/- 1 and ABPM was 151 +/- 2/94 +/- 1 mm Hg. Systolic ABPM was in the normotensive range in 17 patients and diastolic in 15 patients. OBP was falsely positive in 14 and 15 of these patients, respectively. Thus, sensitivity and specificity of OBP were 0.8909 and 0.1765 (systolic) and 0.9825 and 0 (diastolic). These data cannot be extrapolated to populations with lower PPs for use of Bayes' theorem. Hence, we calculated sensitivity and specificity for PP = 0 from published series of ABPM in normotensive subjects and used our measurements and these calculations in arithmetic interpolations for populations with PP 0.1-0.9. Sigmoid relations between PP and predictability of hypertension by a positive OBP were disclosed by use of Bayes' theorem. Their best-fit cubic polynomials predict that an elevated OBP will misdiagnose hypertension 46-50% of the time in a general population (PP = 0.2) but only 8-9% in a specialty practice (PP = 0.9).(ABSTRACT TRUNCATED AT 250 WORDS)