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Exploring diurnal variation using piecewise linear splines: an example using blood pressure

BACKGROUND: There are many examples of physiological processes that follow a circadian cycle and researchers are interested in alternative methods to illustrate and quantify this diurnal variation. Circadian blood pressure (BP) deserves additional attention given uncertainty relating to the prognost...

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Autores principales: Madden, Jamie M., Li, Xia, Kearney, Patricia M., Tilling, Kate, Fitzgerald, Anthony P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290604/
https://www.ncbi.nlm.nih.gov/pubmed/28184234
http://dx.doi.org/10.1186/s12982-017-0055-5
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author Madden, Jamie M.
Li, Xia
Kearney, Patricia M.
Tilling, Kate
Fitzgerald, Anthony P.
author_facet Madden, Jamie M.
Li, Xia
Kearney, Patricia M.
Tilling, Kate
Fitzgerald, Anthony P.
author_sort Madden, Jamie M.
collection PubMed
description BACKGROUND: There are many examples of physiological processes that follow a circadian cycle and researchers are interested in alternative methods to illustrate and quantify this diurnal variation. Circadian blood pressure (BP) deserves additional attention given uncertainty relating to the prognostic significance of BP variability in relation to cardiovascular disease. However, the majority of studies exploring variability in ambulatory blood pressure monitoring (ABPM) collapse the data into single readings ignoring the temporal nature of the data. Advanced statistical techniques are required to explore complete variation over 24 h. METHODS: We use piecewise linear splines in a mixed-effects model with a constraint to ensure periodicity as a novel application for modelling daily blood pressure. Data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47–73 years (n = 2047) was utilized. A subsample (1207) underwent 24-h ABPM. We compared patterns between those with and without evidence of subclinical target organ damage (microalbuminuria). RESULTS: We were able to quantify the steepest rise and fall in SBP, which occurred just after waking (2.23 mmHg/30 min) and immediately after falling asleep (−1.93 mmHg/30 min) respectively. The variation about an individual’s trajectory over 24 h was 12.3 mmHg (standard deviation). On average those with microalbuminuria were found to have significantly higher SBP (7.6 mmHg, 95% CI 5.0–10.1) after adjustment for age, sex and BMI. Including an interaction term between each linear spline and microalbuminuria did not improve model fit. CONCLUSION: We have introduced a practical method for the analysis of ABPM where we can determine the rate of increase or decrease for different periods of the day. This may be particularly useful in examining chronotherapy effects of antihypertensive medication. It offers new measures of short-term BP variability as we can quantify the variation about an individual’s trajectory but also allows examination of the variation in slopes between individuals (random-effects). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12982-017-0055-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-52906042017-02-09 Exploring diurnal variation using piecewise linear splines: an example using blood pressure Madden, Jamie M. Li, Xia Kearney, Patricia M. Tilling, Kate Fitzgerald, Anthony P. Emerg Themes Epidemiol Research Article BACKGROUND: There are many examples of physiological processes that follow a circadian cycle and researchers are interested in alternative methods to illustrate and quantify this diurnal variation. Circadian blood pressure (BP) deserves additional attention given uncertainty relating to the prognostic significance of BP variability in relation to cardiovascular disease. However, the majority of studies exploring variability in ambulatory blood pressure monitoring (ABPM) collapse the data into single readings ignoring the temporal nature of the data. Advanced statistical techniques are required to explore complete variation over 24 h. METHODS: We use piecewise linear splines in a mixed-effects model with a constraint to ensure periodicity as a novel application for modelling daily blood pressure. Data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47–73 years (n = 2047) was utilized. A subsample (1207) underwent 24-h ABPM. We compared patterns between those with and without evidence of subclinical target organ damage (microalbuminuria). RESULTS: We were able to quantify the steepest rise and fall in SBP, which occurred just after waking (2.23 mmHg/30 min) and immediately after falling asleep (−1.93 mmHg/30 min) respectively. The variation about an individual’s trajectory over 24 h was 12.3 mmHg (standard deviation). On average those with microalbuminuria were found to have significantly higher SBP (7.6 mmHg, 95% CI 5.0–10.1) after adjustment for age, sex and BMI. Including an interaction term between each linear spline and microalbuminuria did not improve model fit. CONCLUSION: We have introduced a practical method for the analysis of ABPM where we can determine the rate of increase or decrease for different periods of the day. This may be particularly useful in examining chronotherapy effects of antihypertensive medication. It offers new measures of short-term BP variability as we can quantify the variation about an individual’s trajectory but also allows examination of the variation in slopes between individuals (random-effects). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12982-017-0055-5) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-02 /pmc/articles/PMC5290604/ /pubmed/28184234 http://dx.doi.org/10.1186/s12982-017-0055-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Madden, Jamie M.
Li, Xia
Kearney, Patricia M.
Tilling, Kate
Fitzgerald, Anthony P.
Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title_full Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title_fullStr Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title_full_unstemmed Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title_short Exploring diurnal variation using piecewise linear splines: an example using blood pressure
title_sort exploring diurnal variation using piecewise linear splines: an example using blood pressure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290604/
https://www.ncbi.nlm.nih.gov/pubmed/28184234
http://dx.doi.org/10.1186/s12982-017-0055-5
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