How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the...

Area of Science:

• Critical Care Medicine
• Digital Health
• Immunology

Background:

• Digitalization increases longitudinal patient data availability for disease research.
• Accurate synchronization of patient trajectories using temporal markers is essential for comparing disease progression and pathophysiology.
• Current alignment markers like symptom onset or admission dates may lack precision for critical illness.

Purpose of the Study:

• To compare traditional temporal markers with a novel objective method using C-reactive protein (CRP) peak for synchronizing longitudinal data in ICU COVID-19 patients.
• To evaluate the impact of CRP-based alignment on mortality risk stratification.
• To assess the utility of objective temporal markers in defining pathophysiological windows and improving subgroup analysis.

Main Methods:

• Utilized longitudinal data from critically ill ICU COVID-19 patients.
• Compared alignment based on "onset of symptoms," "hospital admission," and "ICU admission" with a novel method using the peak value of C-reactive protein (CRP).
• Applied CRP-based alignment to synchronize neutrophil and lymphocyte progression data.

Main Results:

• A CRP-based alignment method was developed and applied to COVID-19 patient data.
• This objective synchronization defined a pathophysiological window.
• The CRP-based alignment improved mortality risk stratification within the COVID-19 patient cohort.

Conclusions:

• Objective temporal markers, such as CRP peak, are crucial for accurate synchronization of longitudinal patient data.
• Proper synchronization facilitates precise inter-patient comparisons and the identification of relevant patient subgroups.
• The use of objective markers like CRP enhances translational research and multicenter clinical trials in critical care settings.