Related Experiment Videos
Serial C-Reactive Protein Measurements for Prognostication and Antimicrobial Decision-Making in ICU Sepsis Patients:
Hasan M Al-Dorzi1,2,3, Abdullah Mohammed Aleid1, Abdulmajid Abdullah Alqahtani1
1College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
International Journal of General Medicine
|June 22, 2026
Summary
Serial C-reactive protein (CRP) measurements do not reliably predict mortality in intensive care unit (ICU) sepsis patients. Routine CRP monitoring in sepsis patients may have limited prognostic value.
Area of Science:
- Critical Care Medicine
- Biomarker Research
- Sepsis Management
Background:
- C-reactive protein (CRP) is a common sepsis biomarker.
- Its prognostic value in intensive care unit (ICU) patients with sepsis is uncertain.
- This study investigates serial CRP measurements for predicting sepsis mortality.
Purpose of the Study:
- To evaluate the association between serial C-reactive protein (CRP) measurements and 90-day mortality in ICU patients with sepsis.
- To assess the prognostic value of CRP in sepsis management.
- To compare CRP's predictive performance with procalcitonin.
Main Methods:
- Retrospective cohort study of 171 adult ICU patients with sepsis (2020-2023).
- Included patients with at least three serial CRP measurements (days 1, 3, 7).
- Examined the relationship between CRP levels and 90-day mortality using logistic regression and ROC analysis.
Main Results:
- Day-1 CRP levels and temporal changes showed poor prediction for 90-day mortality (AUC=0.590).
- Non-survivors had slightly higher day-1 CRP (91 mg/L vs. 70 mg/L, p=0.08).
- Day-1 procalcitonin showed slightly better prediction (AUC=0.658); day-1 CRP was not associated with mortality in multivariable analysis.
Conclusions:
- Serial CRP measurements did not reliably predict mortality in ICU sepsis patients.
- CRP monitoring may influence antibiotic duration but has limited prognostic value.
- Routine CRP monitoring in ICU sepsis patients may not be beneficial for predicting outcomes.