{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T15:03:24Z","timestamp":1793113404064,"version":"4.5.0"},"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T00:00:00Z","timestamp":1744243200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Hypertension, a leading global cause of death, poses challenges in stabilizing blood pressure within target values despite various therapeutic options, often necessitating multiple therapy adjustments and delayed impact assessments. Recently, the first wrist-based wearable blood pressure measurement devices were introduced which allow for a continuous assessment of blood pressure trajectories. This enables the development of statistical methodology for prediction of saturated steady-state of blood pressure under treatment\u2014and thus allowing physicians to adjust the therapy earlier. As a prerequisite for the evaluation of such models and algorithms, it is necessary to simulate reliable and realistic hypothetical patient trajectories under treatment with antihypertensive medication. In this paper, we propose a simulation framework for blood pressure profiles through Pharmacokinetic-Pharmacodynamic modeling, which incorporates individual daily rhythms, patient characteristics, and medication effects. We also propose and evaluate two models for steady-state prediction under antihypertensive therapy, a Gaussian process and a non-linear mixed effect model. When only one day of measurements is available, the Gaussian process is preferred, but in real-world situations with more data, the non-linear mixed effect model is favored. It effectively reduces RMSE and bias in noisy data, outperforming the Gaussian process regardless of sample size.<\/jats:p>","DOI":"10.1371\/journal.pone.0318549","type":"journal-article","created":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T20:03:38Z","timestamp":1744315418000},"page":"e0318549","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["A simulation-based framework for modeling and prediction of personalized blood pressure trajectories in hypertensive patients after antihypertensive treatment"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6362-2321","authenticated-orcid":true,"given":"Berit","family":"Hunsdieck","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johanna","family":"Mielke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katja","family":"Ickstadt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eren","family":"El\u00e7i","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,4,10]]},"reference":[{"key":"pone.0318549.ref001","article-title":"Hypertension","author":"WHO","year":"2021"},{"key":"pone.0318549.ref002","article-title":"Global report on hypertension: the race against a silent killer","author":"WHO","year":"2023"},{"issue":"7","key":"pone.0318549.ref003","doi-asserted-by":"crossref","first-page":"1472","DOI":"10.1097\/HJH.0b013e32832a9ba3","article-title":"The global cost of nonoptimal blood pressure","volume":"27","author":"TA Gaziano","year":"2009","journal-title":"J Hypertens"},{"issue":"33","key":"pone.0318549.ref004","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1093\/eurheartj\/ehy339","article-title":"2018 ESC\/ESH Guidelines for the management of arterial hypertension","volume":"39","author":"B Williams","year":"2018","journal-title":"Eur Heart J"},{"key":"pone.0318549.ref005","doi-asserted-by":"crossref","first-page":"1138647","DOI":"10.3389\/fphys.2023.1138647","article-title":"Developing a real-time detection tool and an early warning score using a continuous wearable multi-parameter monitor","volume":"14","author":"A Eisenkraft","year":"2023","journal-title":"Front Physiol"},{"issue":"1","key":"pone.0318549.ref006","doi-asserted-by":"crossref","first-page":"20644","DOI":"10.1038\/s41598-021-99294-w","article-title":"Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure","volume":"11","author":"J Sola","year":"2021","journal-title":"Sci Rep"},{"issue":"2","key":"pone.0318549.ref007","doi-asserted-by":"crossref","first-page":"e18","DOI":"10.3346\/jkms.2024.39.e18","article-title":"First-in-human study for evaluating the accuracy of smart ring based cu\ufb04ess blood pressure measurement","volume":"39","author":"J Kim","year":"2024","journal-title":"J Korean Med Sci"},{"key":"pone.0318549.ref008"},{"issue":"3","key":"pone.0318549.ref009","doi-asserted-by":"crossref","first-page":"e1001779","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"C Sudlow","year":"2015","journal-title":"PLoS Med"},{"issue":"21","key":"pone.0318549.ref010","doi-asserted-by":"crossref","first-page":"1771","DOI":"10.1136\/hrt.2010.221473","article-title":"How quickly should we titrate antihypertensive medication? 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