Predicting Hypertension Among Children With Incident Elevated Blood Pressure.

Acad Pediatr 2017 04 21;17(3):275-282. Epub 2017 Feb 21.

Institute for Health Research, Kaiser Permanente Colorado, Denver, Colo.

Objective: To develop a model to predict hypertension risk among children with incident elevated blood pressure (BP); to test the external validity of the model.

Methods: A retrospective cohort study was conducted in 3 organizations: Kaiser Permanente Colorado was the model derivation site; HealthPartners of Minnesota and Kaiser Permanente Northern California served as external validation sites. During study years 2006 through 2012, all children aged 3 through 17 years with incident elevated BP in an outpatient setting were identified. The predictor variables were demographic and clinical characteristics collected during routine care. Cox proportional hazards regression was used to predict subsequent hypertension, and diagnostic statistics were used to assess model performance.

Results: Among 5598 subjects at the derivation site with incident elevated BP, 160 (2.9%) developed hypertension during the study period. Eight characteristics were used to predict hypertension risk: age, sex, race, BP preceding incident elevated BP, body mass index percentile, systolic BP percentile, diastolic BP percentile, and clinical setting of the incident elevated BP. At the derivation site, the model discriminated well between those at higher versus lower risk of hypertension (c-statistic = 0.77). At external validation sites, the observed risk of hypertension was higher than the predicted risk, and the model showed poor discrimination (c-statistic ranged from 0.64 to 0.67).

Conclusions: Among children with incident elevated BP, a risk model demonstrated good internal validity with respect to predicting subsequent hypertension. However, the risk model did not perform well at 2 external validation sites, which might limit transportability to other settings.

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Source
http://dx.doi.org/10.1016/j.acap.2016.09.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384864PMC
April 2017
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