Cargando…

How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19

The continued digitalization of medicine has led to an increased availability of longitudinal patient data that allows the investigation of novel and known diseases in unprecedented detail. However, to accurately describe any underlying pathophysiology and allow inter-patient comparisons, individual...

Descripción completa

Detalles Bibliográficos
Autores principales: Maibach, Martina A., Allam, Ahmed, Hilty, Matthias P., Perez Gonzalez, Nicolas A., Buehler, Philipp K., Wendel Garcia, Pedro D., Brugger, Silvio D., Ganter, Christoph C., Krauthammer, Michael, Schuepbach, Reto A., Bartussek, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295502/
https://www.ncbi.nlm.nih.gov/pubmed/34307391
http://dx.doi.org/10.3389/fmed.2021.607594
_version_ 1783725442522415104
author Maibach, Martina A.
Allam, Ahmed
Hilty, Matthias P.
Perez Gonzalez, Nicolas A.
Buehler, Philipp K.
Wendel Garcia, Pedro D.
Brugger, Silvio D.
Ganter, Christoph C.
Krauthammer, Michael
Schuepbach, Reto A.
Bartussek, Jan
author_facet Maibach, Martina A.
Allam, Ahmed
Hilty, Matthias P.
Perez Gonzalez, Nicolas A.
Buehler, Philipp K.
Wendel Garcia, Pedro D.
Brugger, Silvio D.
Ganter, Christoph C.
Krauthammer, Michael
Schuepbach, Reto A.
Bartussek, Jan
author_sort Maibach, Martina A.
collection PubMed
description The continued digitalization of medicine has led to an increased availability of longitudinal patient data that allows the investigation of novel and known diseases in unprecedented detail. However, to accurately describe any underlying pathophysiology and allow inter-patient comparisons, individual patient trajectories have to be synchronized based on temporal markers. In this pilot study, we use longitudinal data from critically ill ICU COVID-19 patients to compare the commonly used alignment markers “onset of symptoms,” “hospital admission,” and “ICU admission” with a novel objective method based on the peak value of the inflammatory marker C-reactive protein (CRP). By applying our CRP-based method to align the progression of neutrophils and lymphocytes, we were able to define a pathophysiological window that improved mortality risk stratification in our COVID-19 patient cohort. Our data highlights that proper synchronization of longitudinal patient data is crucial for accurate interpatient comparisons and the definition of relevant subgroups. The use of objective temporal disease markers will facilitate both translational research efforts and multicenter trials.
format Online
Article
Text
id pubmed-8295502
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-82955022021-07-23 How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19 Maibach, Martina A. Allam, Ahmed Hilty, Matthias P. Perez Gonzalez, Nicolas A. Buehler, Philipp K. Wendel Garcia, Pedro D. Brugger, Silvio D. Ganter, Christoph C. Krauthammer, Michael Schuepbach, Reto A. Bartussek, Jan Front Med (Lausanne) Medicine The continued digitalization of medicine has led to an increased availability of longitudinal patient data that allows the investigation of novel and known diseases in unprecedented detail. However, to accurately describe any underlying pathophysiology and allow inter-patient comparisons, individual patient trajectories have to be synchronized based on temporal markers. In this pilot study, we use longitudinal data from critically ill ICU COVID-19 patients to compare the commonly used alignment markers “onset of symptoms,” “hospital admission,” and “ICU admission” with a novel objective method based on the peak value of the inflammatory marker C-reactive protein (CRP). By applying our CRP-based method to align the progression of neutrophils and lymphocytes, we were able to define a pathophysiological window that improved mortality risk stratification in our COVID-19 patient cohort. Our data highlights that proper synchronization of longitudinal patient data is crucial for accurate interpatient comparisons and the definition of relevant subgroups. The use of objective temporal disease markers will facilitate both translational research efforts and multicenter trials. Frontiers Media S.A. 2021-07-08 /pmc/articles/PMC8295502/ /pubmed/34307391 http://dx.doi.org/10.3389/fmed.2021.607594 Text en Copyright © 2021 Maibach, Allam, Hilty, Perez Gonzalez, Buehler, Wendel Garcia, Brugger, Ganter, The CoViD-19 ICU-Research Group Zurich, The RISC-19-ICU Investigators, Krauthammer, Schuepbach and Bartussek. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Maibach, Martina A.
Allam, Ahmed
Hilty, Matthias P.
Perez Gonzalez, Nicolas A.
Buehler, Philipp K.
Wendel Garcia, Pedro D.
Brugger, Silvio D.
Ganter, Christoph C.
Krauthammer, Michael
Schuepbach, Reto A.
Bartussek, Jan
How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title_full How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title_fullStr How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title_full_unstemmed How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title_short How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
title_sort how to synchronize longitudinal patient data with the underlying disease progression: a pilot study using the biomarker crp for timing covid-19
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295502/
https://www.ncbi.nlm.nih.gov/pubmed/34307391
http://dx.doi.org/10.3389/fmed.2021.607594
work_keys_str_mv AT maibachmartinaa howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT allamahmed howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT hiltymatthiasp howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT perezgonzaleznicolasa howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT buehlerphilippk howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT wendelgarciapedrod howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT bruggersilviod howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT ganterchristophc howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT krauthammermichael howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT schuepbachretoa howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19
AT bartussekjan howtosynchronizelongitudinalpatientdatawiththeunderlyingdiseaseprogressionapilotstudyusingthebiomarkercrpfortimingcovid19