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

Frontiers in Medicine

The RISC-19-ICU Investigators¹  The CoViD-19 ICU-Research Group Zurich¹  Silvio D. Brugger²  Ahmed Allam³  Nicolas A. Perez Gonzalez³  Jan Bartussek³  Michael Krauthammer³  Martina A. Maibach⁴  Reto A. Schuepbach⁴  Matthias P. Hilty⁴  Christoph C. Ganter⁴  Philipp K. Buehler⁴  Pedro D. Wendel Garcia⁴ 

[1] ;Department of Infectious Diseases and Hospital Epidemiology, University and University Hospital Zurich, Zurich, Switzerland;Department of Quantitative Biomedicine, University and University Hospital Zurich, Zurich, Switzerland;Institute for Intensive Care Medicine, University and University Hospital Zurich, Zurich, Switzerland;

关键词: COVID-19;    longitudinal data;    synchronization;    subgroup comparison;    risk stratification;    biomarker;   

DOI  :  10.3389/fmed.2021.607594

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown