White Coat Hypertension Persistence in Children and Adolescents: The Pediatric Nephrology Research Consortium Study.

OBJECTIVES: To determine whether youth with white coat hypertension on initial ambulatory blood pressure monitoring (ABPM) continue to demonstrate the same pattern on repeat ABPM. STUDY DESIGN: Retrospective longitudinal cohort study of patients referred for high blood pressure (BP) and diagnosed with white coat hypertension by ABPM who had follow-up ABPM 0.5-4.6 years later at 11 centers in the Pediatric Nephrology Research Consortium. We classified ABPM phenotype using the American Heart Association guidelines. At baseline, we classified those with hypertensive BP in the clinic as "stable white coat hypertension," and those with normal BP as "intermittent white coat hypertension." We used multivariable generalized linear mixed effect models to estimate the association of baseline characteristics with abnormal ABPM phenotype progression. RESULTS: Eighty-nine patients met the inclusion criteria (median age, 13.9 years; 78% male). Median interval time between ABPM measurements was 14 months. On follow-up ABPM, 61% progressed to an abnormal ABPM phenotype (23% ambulatory hypertension, 38% ambulatory prehypertension). Individuals age 12-17 years and those with stable white coat hypertension had greater proportions progressing to either prehypertension or ambulatory hypertension. In the multivariable models, baseline wake systolic BP index ≥0.9 was significantly associated with higher odds of progressing to ambulatory hypertension (OR 3.07, 95% CI 1.02-9.23). CONCLUSIONS: The majority of the patients with white coat hypertension progressed to an abnormal ABPM phenotype. This study supports the 2017 American Academy of Pediatrics Clinical Practice Guideline's recommendation for follow-up of ABPM in patients with white coat hypertension.

Estimation of covariate effects with current status data and differential mortality.

The assessment of the impact that socioeconomic determinants have on the prevalence of certain chronic conditions reported by respondents in population surveys must confront two problems. First, the self-reports could be in error (false positives and false negatives). Second, those reporting are a selected sample of those who ever experience the problem, and this selection is heavily influenced by excess mortality attributable to the condition being reported. In this article, we use a combination of empirical data and microsimulation to (a) assess the magnitude of the bias attributable to the selection problem, and (b) suggest an adjustment procedure that corrects for this bias. We find that the proposed adjustment procedure considerably reduces the bias arising from differential mortality.