Exploring circadian blood pressure patterns

dc.check.embargoformatNot applicableen
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dc.contributor.advisorFitzgerald, Tonyen
dc.contributor.advisorKearney, Patricia M.en
dc.contributor.advisorLi, Xiaen
dc.contributor.authorMadden, Jamie M.
dc.contributor.funderHealth Research Boarden
dc.date.accessioned2017-04-25T12:30:44Z
dc.date.available2017-04-25T12:30:44Z
dc.date.issued2017
dc.date.submitted2017
dc.description.abstractDespite our comprehensive knowledge of the importance of reducing mean levels of blood pressure (BP), we are less informed about the benefits of reducing other parameters of BP, specifically BP variability (BPV). Ambulatory blood pressure monitoring (ABPM), which can be used to obtain estimates of BP over a 24h period, offers a powerful tool in the analysis of circadian patterns and short-term BPV. The main aims of this thesis were to explore and identify circadian BP patterns between individuals and groups, and extract meaningful measures that describe these patterns while appropriately accounting for the inherent cyclical structure of ABPM data. Specifically, the thesis includes a systematic review which identifies summary measures of BPV, such as standard deviation. A meta-analysis exploring the correlation between short-term BPV and subclinical target organ damage (TOD) is included. The association between the identified summary measures and subclinical TOD is then explored in a group of middle aged adults. In an attempt to maximise the power of the repeated cyclical readings in ABPM and incorporate the data together in one model, different random-effects models were explored which allowed us to obtain estimates of both within and between-individual variation of model parameters. A piece-wise linear mixed-effects model was considered as a simple but suitable approach to capture BP trajectory throughout the day. Finally, a two-component cosinor random-effects model is outlined where derivatives of the model fit presents a novel alternative method to locate and quantify the magnitude of slopes at critical points along the trajectory. This is used to obtain a measure of morning BP surge. We compare the random-effects from this model to principle component scores obtained through functional principle component analysis. Our motivating data comes from the Mitchelstown Study, a population based study of Irish adults where a subsample underwent 24h ABPM.en
dc.description.sponsorshipHealth Research Board, Ireland (Scholars Programme in Health Services Research)en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMadden, J. 2017. Exploring circadian blood pressure patterns. PhD Thesis, University College Cork.en
dc.identifier.endpage260en
dc.identifier.urihttps://hdl.handle.net/10468/3888
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2017, Jamie Madden.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectBlood pressure variabilityen
dc.subjectCircadian rhythmen
dc.subjectBiostatisticsen
dc.subjectEpidemiologyen
dc.subjectCircadian modellingen
dc.thesis.opt-outfalse
dc.titleExploring circadian blood pressure patternsen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoral Degree (Structured)en
dc.type.qualificationnamePhD (Health Services Research)en
ucc.workflow.supervisort.fitzgerald@ucc.ie
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