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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |