| Literature DB >> 28794881 |
Ashitha L Vijayan1, Shilpa Ravindran1, R Saikant1, S Lakshmi1, R Kartik1, Manoj G1.
Abstract
BACKGROUND: Sepsis is a global healthcare problem, characterized by whole body inflammation in response to microbial infection, which leads to organ dysfunction. It is becoming a frequent complication in hospitalized patients. Early and differential diagnosis of sepsis is needed critically to avoid unnecessary usage of antimicrobial agents and for proper antibiotic treatments through the screening of biomarkers that sustains with diagnostic significance. MAIN BODY OF ABSTRACT: Current targeting conventional markers (C-reactive protein, white blood cell, tumour necrosis factor-α, interleukins, etc.) are non-specific for diagnosing sepsis. Procalcitonin (PCT), a member of the calcitonin super family could be a critical tool for the diagnosis of sepsis. But to distinguish between bacterial versus viral infections, procalcitonin alone may not be effective. Rapid elevation in the concentration of procalcitonin and other newly emerging biomarkers during an infection and its correlation with severity of illness makes it an ideal biomarker for bacterial infection. Beside this, the procalcitonin levels can be used for monitoring response to antimicrobial therapy, diagnosis of secondary inflammations, diagnosis of renal involvement in paediatric urinary tract infection, etc. The present article summarizes the relevance of procalcitonin in the diagnosis of sepsis and how it can be useful in determining the therapeutic approaches.Entities:
Keywords: Antibiotic therapy; Diagnostic marker; Procalcitonin; Sepsis
Year: 2017 PMID: 28794881 PMCID: PMC5543591 DOI: 10.1186/s40560-017-0246-8
Source DB: PubMed Journal: J Intensive Care ISSN: 2052-0492
Fig. 1Fate of procalcitonin during inflammation and normal condition
Comparison of diagnostic potential of procalcitonin and presepsin
| Reports | No. of subject | Area under curve (AUC) for the diagnosis of sepsis | |
|---|---|---|---|
| Procalcitonin | Presepsine | ||
| Dunja Mihajlovic et al. (2017) [ | 100 | 0.750 | 0.730 |
| Christian Leli et al.(2016) [ | 0 92 | 0.876 | 0.788 |
| Kada Klouche et al. (2016) [ | 144 | 0.800 | 0.750 |
| Enguix-Armada A et al.(2016) [ | 388 | 0.989 | 0.948 |
Fig. 2PCT algorithm for antibiotic therapy