Biomarkers are widely used to confirm the presence of
infection. However, it would be of the greatest importance to predict in advance the occurrence or worsening of organ dysfunction in infected patients allowing timely
antibiotic escalation. This study investigates the ability of
procalcitonin (PCT) and MR-proADM to predict the transition to
sepsis in infected patients. The study was conducted in a neurointensive care unit over a three-month period. We included both patients with and without
infection to investigate the specificity of organ dysfunction prediction in infected patients. Daily measurement of PCT and MR-proADM, SOFA, Pitt, and CPIS were performed. To measure the correlation between each
biomarker and each severity score, linear mixed-effects models were developed. For each
biomarker-score combination we tested the correlation of the score with the
biomarker measured one and two days before, the same day, and the day after. Sixty-four
critically ill patients, 31 with
infection, were enrolled. The statistically significant
biomarker-score combinations were PCT-SOFA, MR-proADM-SOFA, MR-proADM-Pitt, and MR-proADM-CPIS. The MR-proADM models predicting Pitt and CPIS variations with 24-hour anticipation showed the best fit. The scores increased by 0.6 ± 0.3 and 0.4 ± 0.2 for each unitary
biomarker increase, respectively. The MR-proADM-SOFA combinations were equivalent when the
biomarker was measured the day before or the same day (score increases were 1.5 ± 0.4 and 1.9 ± 0.4, respectively). The PCT-SOFA model had the best fit when PCT was measured the same day of the score. There was no difference in the predictive ability of the
biomarker in infected and non-infected patients. This was a pivotal study conducted in a single neurointensive centre on a limited number of patients, and as such it does not provide definitive conclusions. PR-proADM predicted occurrence and worsening of organ failure in
critically ill patients with and without
infection. The combination with
infection diagnostic
biomarkers such as PCT would allow predicting evolution to
sepsis in infected patients.