Publication Date
9-1-2022
Journal
Hypertention
Abstract
BACKGROUND: Ambulatory blood pressure monitoring (ABPM) is routinely performed in children with chronic kidney disease to identify masked hypertension, a risk factor for accelerated chronic kidney disease progression. However, ABPM is burdensome, and developing an accurate prediction of masked hypertension may allow using ABPM selectively rather than routinely.
METHODS: To create a prediction model for masked hypertension using clinic blood pressure (BP) and other clinical characteristics, we analyzed 809 ABPM studies with nonhypertensive clinic BP among the participants of the Chronic Kidney Disease in Children study.
RESULTS: Masked hypertension was identified in 170 (21.0%) observations. We created prediction models for masked hypertension via gradient boosting, random forests, and logistic regression using 109 candidate predictors and evaluated its performance using bootstrap validation. The models showed
CONCLUSIONS: ABPM could be used selectively in those with low clinic BP, for example, systolic BPBPpercentiles, although careful assessment is warranted as masked hypertension was not completely absent even in this subgroup. Above these clinic BP levels, routine ABPM remains recommended.
Keywords
Blood Pressure, Blood Pressure Monitoring, Ambulatory, Child, Humans, Machine Learning, Masked Hypertension, Renal Insufficiency, Chronic
Comments
Supplementary Materials
PMID: 35862083