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Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study

Antihypertensive medications complicate studies of blood pressure (BP) natural history; BP if untreated (“underlying BP”) needs to be estimated. Our objectives were to compare validity of five missing data imputation methods to estimate underlying BP and longitudinal associations of underlying BP an...

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Autores principales: Balakrishnan, Poojitha, Beaty, Terri, Young, J. Hunter, Colantuoni, Elizabeth, Matsushita, Kunihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507409/
https://www.ncbi.nlm.nih.gov/pubmed/28700596
http://dx.doi.org/10.1371/journal.pone.0179234
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author Balakrishnan, Poojitha
Beaty, Terri
Young, J. Hunter
Colantuoni, Elizabeth
Matsushita, Kunihiro
author_facet Balakrishnan, Poojitha
Beaty, Terri
Young, J. Hunter
Colantuoni, Elizabeth
Matsushita, Kunihiro
author_sort Balakrishnan, Poojitha
collection PubMed
description Antihypertensive medications complicate studies of blood pressure (BP) natural history; BP if untreated (“underlying BP”) needs to be estimated. Our objectives were to compare validity of five missing data imputation methods to estimate underlying BP and longitudinal associations of underlying BP and age. We simulated BP treatment in untreated hypertensive participants from Atherosclerosis Risk in Communities (ARIC) in visits 1–5 (1987–2013) using matched treated hypertensive participants. The underlying BP was imputed: #1, set as missing; #2, add 10 mmHg for systolic, 5 mmHg for diastolic; #3, add medication class-specific constant; #4, truncated normal regression; and #5, truncated normal regression including prior visit data. Longitudinal associations were estimated using linear mixed models of imputed underlying BP for simulated treated and measured BP for untreated participants. Method 3 was the best-performing for systolic BP; lowest relative bias (5.3% for intercept at age 50, 0% for age coefficient) and average deviation from expected (0.04 to -1.79). Method 2 performed best for diastolic BP; lowest relative bias (0.6% intercept at age 50, 33.3% age <60, 9.1% age 60+) and average deviation (-1.25 to -1.68). Methods 4 and 5 were comparable or slightly inferior. In conclusion, constant addition methods yielded valid and precise underlying BP and longitudinal associations.
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spelling pubmed-55074092017-07-25 Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study Balakrishnan, Poojitha Beaty, Terri Young, J. Hunter Colantuoni, Elizabeth Matsushita, Kunihiro PLoS One Research Article Antihypertensive medications complicate studies of blood pressure (BP) natural history; BP if untreated (“underlying BP”) needs to be estimated. Our objectives were to compare validity of five missing data imputation methods to estimate underlying BP and longitudinal associations of underlying BP and age. We simulated BP treatment in untreated hypertensive participants from Atherosclerosis Risk in Communities (ARIC) in visits 1–5 (1987–2013) using matched treated hypertensive participants. The underlying BP was imputed: #1, set as missing; #2, add 10 mmHg for systolic, 5 mmHg for diastolic; #3, add medication class-specific constant; #4, truncated normal regression; and #5, truncated normal regression including prior visit data. Longitudinal associations were estimated using linear mixed models of imputed underlying BP for simulated treated and measured BP for untreated participants. Method 3 was the best-performing for systolic BP; lowest relative bias (5.3% for intercept at age 50, 0% for age coefficient) and average deviation from expected (0.04 to -1.79). Method 2 performed best for diastolic BP; lowest relative bias (0.6% intercept at age 50, 33.3% age <60, 9.1% age 60+) and average deviation (-1.25 to -1.68). Methods 4 and 5 were comparable or slightly inferior. In conclusion, constant addition methods yielded valid and precise underlying BP and longitudinal associations. Public Library of Science 2017-07-11 /pmc/articles/PMC5507409/ /pubmed/28700596 http://dx.doi.org/10.1371/journal.pone.0179234 Text en © 2017 Balakrishnan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Balakrishnan, Poojitha
Beaty, Terri
Young, J. Hunter
Colantuoni, Elizabeth
Matsushita, Kunihiro
Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title_full Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title_fullStr Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title_full_unstemmed Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title_short Methods to estimate underlying blood pressure: The Atherosclerosis Risk in Communities (ARIC) Study
title_sort methods to estimate underlying blood pressure: the atherosclerosis risk in communities (aric) study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507409/
https://www.ncbi.nlm.nih.gov/pubmed/28700596
http://dx.doi.org/10.1371/journal.pone.0179234
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