Biomarkers in Pneumonia—Beyond Procalcitonin
Abstract
:1. Pneumonia
2. Impact of Incorrect Use of Antibiotics
3. The Role of Biomarkers
4. Beyond Procalcitonin
5. C-reactive Protein (CRP)
6. IL-6
7. Complete Blood Counts and Platelets
8. Neutrophil CD64 Receptor
9. Monocyte Human Leukocyte Antigen-DR (mHLA-DR)
10. Presepsin
11. D-Dimer
12. Triggering Receptor Expressed on Myeloid Cells 1 (TREM-1)
13. Prohormones
14. Precision and Personalized Medicine
15. Early Clinical Stability
16. Metabolomics
17. Genomics
18. Microbiomics
19. Proteomics
20. Conclusions and Future Perspectives
Author Contributions
Funding
Conflicts of Interest
References
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Diagnostic Biomarkers | Prognostic Biomarkers | Antibiotic Guidance Biomarkers |
---|---|---|
Procalcitonin (PCT) [32] | C-reactive protein (CRP) predicts the absence of severe complications [60] | PCT guidance significantly reduces initiation and duration of antibiotic therapy [51] |
CRP indicates inflammation intensity [40,58] | Interleukin 6 (IL-6) predicts treatment failure and mortality [39] | |
Neutrophil CD64 (nCD64) used for the diagnosis of bacterial infection and sepsis [83,84,85,86,87,88,89,90] | Neutrophil-to-lymphocyte ratio (NLR) predicts mortality [74] | |
D-dimer levels increased in patients with severe community-acquired pneumonia (CAP) [98] | Monocyte-to-lymphocyte ratio (MLR) indicates disease severity [75,76,77] | |
Triggering receptor expressed on myeloid cells 1 (TREM-1) is a good predictor of ventilator-associated pneumonia (VAP) [103] | Platelets indicate CAP severity [78] and predict mortality [79] | |
Atrial natriuretic peptide (ANP) levels increase during sepsis [115,116,117,118] | Monocyte human leukocyte antigen-DR (mHLA-DR) decreases rapidly in correlation to the severity and outcome of septic shock [94,95]; nonsurvivors express reduced levels of mHLA-DR [96] | |
Metabolomics used to differentiate CAP from other noninfective pulmonary acute disorders [133] | Presepsin predicts severe CAP and progression to septic shock [97] | |
Overexpression of TNFα gene is associated with severe sepsis and septic shock [140] | D-dimer level <500 ng/mL on admission indicates a lower risk of death and morbidity [100] | |
PIK3R3 gene expression contributes to sepsis and organ damage in critically ill patients [141] | Pro-adrenomedullin (ADM) within the first 48 h after antibiotic administration predicts hospital mortality [105] | |
Gelsolin, serum amyloid P-component, vitamin D-binding protein, and pyruvate kinase are higher in bronchoalveolar lavage (BAL) from patients with VAP [146] | C-terminal portion of copeptin (CT-pro-AVP) correlates with poor outcomes in CAP sepsis [122,123,124,125], predicts early mortality or intensive care unit (ICU) admission [124] | |
S100A8, lactotransferrin, actinin-1 discriminate VAP patients with acute lung injury [147] | Specific metabolites as predictors of survival [133] | |
Low T3 syndrome at 24 h after admission is associated with increased rate of ICU admission and increased 30-day mortality [134] | ||
FER gene single nucleotide polymorphism results in a minor allele variant strongly associated with CAP survival [138] | ||
Specific patterns of lower airway microbiomes differently predict ICU admission and length of stay [142] | ||
Multibiomarker protein models for the risk assessment of CAP [103,144,145] |
Biomarkers That Indicate Direct Evidence of Infection | Biomarkers That Determine the Host Response to Infection |
---|---|
Presepsin is released in the blood during phagocytosis [97] | PCT, identifiable within 2–3 h with peak at 6 h [32] |
TREM-1 expression is upregulated in the presence of extracellular bacteria and fungi [16] | CRP, identifiable within 4–6 h with peak at 36–50 h [40,59] |
Diverse metabolomes specific for sepsis and CAP; putrescine is a predictor for CAP [132] | IL-6, immediate response to infection [44,69], more sensitive for localized infection (e.g., effusions) [44] |
Exhaled breath contains volatile organic compounds (VOCs) that result from bacterial metabolism and/or host response to the environment [135] | NLR, PLR, and MLR indicate systemic inflammation and infection [72,73] |
Specific patterns of lower airway microbiomes differently predict ICU admission and length of stay [142] | nCD64 increases during the proinflammatory state in response to infection and returns to normal when the stimulating factors disappear [80] |
Early clinical stability is associated with a significant lower 30-day and 90-day mortality rate, fewer ICU admissions, and shorter length of stay [131] | |
Personal genetic predisposition is involved in the response to a severe infection and predicts the progression of pneumonia [9] | |
Individual proteins as biomarkers for the presence of VAP [16] |
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Karakioulaki, M.; Stolz, D. Biomarkers in Pneumonia—Beyond Procalcitonin. Int. J. Mol. Sci. 2019, 20, 2004. https://doi.org/10.3390/ijms20082004
Karakioulaki M, Stolz D. Biomarkers in Pneumonia—Beyond Procalcitonin. International Journal of Molecular Sciences. 2019; 20(8):2004. https://doi.org/10.3390/ijms20082004
Chicago/Turabian StyleKarakioulaki, Meropi, and Daiana Stolz. 2019. "Biomarkers in Pneumonia—Beyond Procalcitonin" International Journal of Molecular Sciences 20, no. 8: 2004. https://doi.org/10.3390/ijms20082004
APA StyleKarakioulaki, M., & Stolz, D. (2019). Biomarkers in Pneumonia—Beyond Procalcitonin. International Journal of Molecular Sciences, 20(8), 2004. https://doi.org/10.3390/ijms20082004