Misleading measurments: modelling the effects of blood pressure misclassification in a United States population
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Objective. The clinical diagnosis of hypertension is subject to misclassification, and this may be clinically important. This article calculates positive and negative predictive values for blood pressure measurement and assesses the frequency of clinically important blood pressure misclassification. Design, Setting, and Participants. A modeling study was carried out on 4763 adults in the National Health and Nutrition Examination Survey (NHANES) population. True treatment eligibility was determined by applying Joint National Committee (JNC) V11 criteria to individuals in the study population. Each individual was also allocated a series of blood pressures incorporating an error term reflecting day-to-day measurement variation. Test positives are persons classified as needing treatment on the basis of the :mean of 2 blood pressure measurements. Measurements and Main Results. Positive predictive values of a diagnosis of hypertension based on 2 measurements were calculated for each age-sex group. Low-risk false positives and high-risk false negatives were categorized as clinically important errors. Positive predictive values are high in persons older than age 65. In persons ages 16 to 34, the positive predictive value is 0.24 (95% confidence interval [CI]: 0.17-0.32) in men and 0.16 (95% CI: 0.06-0.26) in women. Persons younger than age 35 are almost always at low risk of cardiovascular disease, and therefore this misclassification is clinically important. Even with 24-hour ambulatory blood pressure measurement, positive predictive values in young adults ore under 0.5. Conclusions. Blood pressure estimation is a poor diagnostic test in low-prevalence populations such as young adults. Estimation of blood pressure should be informed by prior estimation of cardiovascular risk.
|Number of pages||9|
|Journal||Medical Decision Making|
|Publication status||Published - 1 Nov 2006|
- heart disease, screening, blood pressure, measurement error, diagnostic tests