| Literature DB >> 31022834 |
Meropi Karakioulaki1, Daiana Stolz2.
Abstract
Pneumonia is the leading infectious cause of mortality worldwide and one of the most common lower respiratory tract infections that is contributing significantly to the burden of antibiotic consumption. Due to the complexity of its pathophysiology, it is widely accepted that clinical diagnosis and prognosis are inadequate for the accurate assessment of the severity of the disease. The most challenging task for a physician is the risk stratification of patients with community-acquired pneumonia. Herein, early diagnosis is essential in order to reduce hospitalization and mortality. Procalcitonin and C-reactive protein remain the most widely used biomarkers, while interleukin 6 has been of particular interest in the literature. However, none of them appear to be ideal, and the search for novel biomarkers that will most sufficiently predict the severity and treatment response in pneumonia has lately intensified. Although our insight has significantly increased over the last years, a translational approach with the application of genomics, metabolomics, microbiomics, and proteomics is required to better understand the disease. In this review, we discuss this rapidly evolving area and summarize the application of novel biomarkers that appear to be promising for the accurate diagnosis and risk stratification of pneumonia.Entities:
Keywords: biomarkers; novel; pneumonia; procalcitonin
Mesh:
Substances:
Year: 2019 PMID: 31022834 PMCID: PMC6514895 DOI: 10.3390/ijms20082004
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Summary of diagnostic, prognostic, and antibiotic guidance biomarkers in pneumonia and their indications.
| Diagnostic Biomarkers | Prognostic Biomarkers | Antibiotic Guidance Biomarkers |
|---|---|---|
| Procalcitonin (PCT) [ | C-reactive protein (CRP) predicts the absence of severe complications [ | PCT guidance significantly reduces initiation and duration of antibiotic therapy [ |
| CRP indicates inflammation intensity [ | Interleukin 6 (IL-6) predicts treatment failure and mortality [ | |
| Neutrophil CD64 (nCD64) used for the diagnosis of bacterial infection and sepsis [ | Neutrophil-to-lymphocyte ratio (NLR) predicts mortality [ | |
| D-dimer levels increased in patients with severe community-acquired pneumonia (CAP) [ | Monocyte-to-lymphocyte ratio (MLR) indicates disease severity [ | |
| Triggering receptor expressed on myeloid cells 1 (TREM-1) is a good predictor of ventilator-associated pneumonia (VAP) [ | Platelets indicate CAP severity [ | |
| Atrial natriuretic peptide (ANP) levels increase during sepsis [ | Monocyte human leukocyte antigen-DR (mHLA-DR) decreases rapidly in correlation to the severity and outcome of septic shock [ | |
| Metabolomics used to differentiate CAP from other noninfective pulmonary acute disorders [ | Presepsin predicts severe CAP and progression to septic shock [ | |
| Overexpression of | D-dimer level <500 ng/mL on admission indicates a lower risk of death and morbidity [ | |
| Pro-adrenomedullin (ADM) within the first 48 h after antibiotic administration predicts hospital mortality [ | ||
| Gelsolin, serum amyloid P-component, vitamin D-binding protein, and pyruvate kinase are higher in bronchoalveolar lavage (BAL) from patients with VAP [ | C-terminal portion of copeptin (CT-pro-AVP) correlates with poor outcomes in CAP sepsis [ | |
| S100A8, lactotransferrin, actinin-1 discriminate VAP patients with acute lung injury [ | Specific metabolites as predictors of survival [ | |
| Low T3 syndrome at 24 h after admission is associated with increased rate of ICU admission and increased 30-day mortality [ | ||
| Specific patterns of lower airway microbiomes differently predict ICU admission and length of stay [ | ||
| Multibiomarker protein models for the risk assessment of CAP [ |
Summary of the biomarkers that indicate a direct evidence of infection and those that indicate the host’s response to infection.
| Biomarkers That Indicate Direct Evidence of Infection | Biomarkers That Determine the Host Response to Infection |
|---|---|
| Presepsin is released in the blood during phagocytosis [ | PCT, identifiable within 2–3 h with peak at 6 h [ |
| TREM-1 expression is upregulated in the presence of extracellular bacteria and fungi [ | CRP, identifiable within 4–6 h with peak at 36–50 h [ |
| Diverse metabolomes specific for sepsis and CAP; putrescine is a predictor for CAP [ | IL-6, immediate response to infection [ |
| Exhaled breath contains volatile organic compounds (VOCs) that result from bacterial metabolism and/or host response to the environment [ | NLR, PLR, and MLR indicate systemic inflammation and infection [ |
| Specific patterns of lower airway microbiomes differently predict ICU admission and length of stay [ | nCD64 increases during the proinflammatory state in response to infection and returns to normal when the stimulating factors disappear [ |
| Early clinical stability is associated with a significant lower 30-day and 90-day mortality rate, fewer ICU admissions, and shorter length of stay [ | |
| Personal genetic predisposition is involved in the response to a severe infection and predicts the progression of pneumonia [ | |
| Individual proteins as biomarkers for the presence of VAP [ |