Combined serum biomarkers in the noninvasive diagnosis of complicated parapneumonic effusions and empyema

The Review of Current Knowledge on Neutrophil Gelatinase-Associated Lipocalin (NGAL)

Neutrophil gelatinase-associated lipocalin (NGAL) is a 25-kDa protein that is secreted mostly by immune cells such as neutrophils, macrophages, and dendritic cells. Its production is stimulated in response to inflammation. The concentrations of NGAL can be measured in plasma, urine, and biological fluids such as peritoneal effluent. NGAL is known mainly as a biomarker of acute kidney injury and is released after tubular damage and during renal regeneration processes. NGAL is also elevated in chronic kidney disease and dialysis patients. It may play a role as a predictor of the progression of renal function decreases with complications and mortality due to kidney failure. NGAL is also useful in the diagnostic processes of cardiovascular diseases. It is highly expressed in injured heart tissue and atherosclerostic plaque; its serum concentrations correlate with the severity of heart failure and coronary artery disease. NGAL increases inflammatory states and its levels rise in arterial hypertension, obesity, diabetes, and metabolic complications such as insulin resistance, and is also involved in carcinogenesis. In this review, we present the current knowledge on NGAL and its involvement in different pathologies, especially its role in renal and cardiovascular diseases.

Diagnostic value of soluble biomarkers for parapneumonic pleural effusion

Parapneumonic pleural effusion (PPE) is a common complication in patients with pneumonia. Timely and accurate diagnosis of PPE is of great value for its management. Measurement of biomarkers in circulating and pleural fluid have the advantages of easy accessibility, short turn-around time, objectiveness and low cost and thus have utility for PPE diagnosis and stratification. To date, many biomarkers have been reported to be of value for the management of PPE. Here, we review the values of pleural fluid and circulating biomarkers for the diagnosis and stratification PPE. The biomarkers discussed are C-reactive protein, procalcitonin, presepsin, soluble triggering receptor expressed on myeloid cells 1, lipopolysaccharide-binding protein, inflammatory markers, serum amyloid A, soluble urokinase plasminogen activator receptor, matrix metalloproteinases, pentraxin-3 and cell-free DNA. We found that none of the available biomarkers has adequate performance for diagnosing and stratifying PPE. Therefore, further work is needed to identify and validate novel biomarkers, and their combinations, for the management of PPE.

Discrimination of Exudative Pleural Effusions Based on Pleural Adenosine Deaminase (ADA)-C-Reactive Protein (CRP) Levels, and Their Combination: An Observational Prospective Study

(1) Background: Malignant (MPE), parapneumonic (PPE) and tuberculous (TPE) pleural effusions constitute common causes of pleurisy. Discriminating among them is usually challenging. C-reactive protein (CRP) and adenosine deaminase (ADA) pleural levels (p-CRP, p-ADA) have been used as differentiators in many studies showing promising results. This study aims to evaluate the diagnostic value of p-CRP, p-ADA levels and their combination among the three categories. (2) Methods: A prospective study of 100 patients with MPE (n = 59), PPE (n = 34) and TPE (n = 7) from a single centre was performed. p-CRP levels were evaluated between PPE and non-PPE and between complicated (CPPE) and non-complicated PPE. ADA levels were also measured to classify patients among MPE and non- MPE. Eventually, the combination of p-CRP and p-ADA values was used as a discrimination factor among PPE, MPE and TPE. (3) Results: ROC analysis revealed that p-CRP with a cut-off value: 4.4 mg/dL can successfully differentiate PPE (AUC = 0.998). The cut-off level of 10 mg/dL can predict CPPE with sensitivity: 63%, specificity: 71.4%, positive predictive value (PPV): 89%, and negative predictive value (NPV): 33%. Furthermore, patients with ADA levels ≤ 32 U/L were more likely to belong to the malignant group sensitivity: 93%, specificity: 78%, PPV: 85.9%, and NPV: 88.9%. Discriminant analysis showed that the combination of p-CRP and p-ADA levels can discriminate PPE, MPE and TPE in 93% of cases. (4) Conclusion: This study provides evidence that p-CRP and p-ADA levels could be possibly used in clinal practice in order to establish a diagnosis among MPE, PPE and TPE.

Exploring the value of pleural fluid biomarkers for complementary pleural effusion disease examination

OBJECTIVE

Pleural fluid biomarkers are beneficial for the complementary diagnosis of pleural effusion etiologies. This study focuses on the multidimensional evaluation of deep learning to investigate the pleural effusion biomarkers value and the diagnostic utility of combining these markers, in distinguishing pleural effusion etiologies.

METHODS

Pleural effusion were divided into three groups according to the diagnosis and treatment guidelines: malignant pleural effusion (MPE), parapneumonic effusion (PPE), and congestive heart failure (CHF). First, the value of the biomarker was analyzed by a receiver operating characteristic (ROC) curve. Then by utilizing deep learning and entropy weight method (EWM), the clinical value of biomarkers was computed multidimensionally for complementary diagnosis of pleural effusion diseases.

RESULTS

There were significant differences in the six biomarkers, TP, ADA, CEA, CYFRA211, NSE, MNC% (p < 0.05) and no significant differences in three physical characteristics including color, transparency, specific gravity and six other biomarkers such as WBC, PNC%, MTC%, pH level, GLU, LDH (p > 0.05) among the three pleural effusion groups. The comprehensive test of pleural fluid biomarkers based on deep learning is of high accuracy. The clinical value of cytomorphology biomarkers WBC, MNC %, PNC %, MTC % was higher among pleural fluid biomarkers.

CONCLUSION

The clinical value of multi-dimensional analysis of biomarkers by deep learning and entropy weight method is different from the ROC curve analysis. It is suggested that during the clinical examination process, more attention should be paid to the cell morphology biomarkers, but the physical properties of the pleural fluid are less clinical significance.

Calprotectin: An Ignored Biomarker of Neutrophilia in Pediatric Respiratory Diseases

Calprotectin (CP) is a non-covalent heterodimer formed by the subunits S100A8 (A8) and S100A9 (A9). When neutrophils become activated, undergo disruption, or die, this abundant cytosolic neutrophil protein is released. By fervently chelating trace metal ions that are essential for bacterial development, CP plays an important role in human innate immunity. It also serves as an alarmin by controlling the inflammatory response after it is released. Extracellular concentrations of CP increase in response to infection and inflammation, and are used as a biomarker of neutrophil activation in a variety of inflammatory diseases. Although it has been almost 40 years since CP was discovered, its use in daily pediatric practice is still limited. Current evidence suggests that CP could be used as a biomarker in a variety of pediatric respiratory diseases, and could become a valuable key factor in promoting diagnostic and therapeutic capacity. The aim of this study is to re-introduce CP to the medical community and to emphasize its potential role with the hope of integrating it as a useful adjunct, in the practice of pediatric respiratory medicine.

A retrospective study on the combined biomarkers and ratios in serum and pleural fluid to distinguish the multiple types of pleural effusion

Purpose

Pleural effusion (PE) is a common clinical manifestation, and millions of people suffer from pleural disease. Herein, this retrospective study was performed to evaluate the biomarkers and ratios in serum and pleural fluid (PF) for the differential diagnosis of the multiple types of PE and search for a new diagnostic strategy for PE.

Methods

In-patients, who developed tuberculous PE (TPE), malignant PE (MPE), complicated parapneumonic effusion (CPPE), uncomplicated PPE (UPPE), or PE caused by connective tissue diseases (CTDs) and underwent thoracentesis at Peking University People’s Hospital from November 2016 to April 2019, were included in this study. Eleven biomarkers and their ratios in serum and PF were investigated and compared between pairs of the different PE groups, and a decision-tree was developed.

Results

Totally 112 PE cases, including 25 MPE, 33 TPE, 19 CPPE, 27 UPPE, and 8 PE caused by CTDs, were reviewed. Biomarkers and ratios showed good diagnostic performance with high area under the curve values, sensitivities, and specificities for the differential diagnosis of the multiple types of PE. According to the decision-tree analysis, the combination of adenosine deaminase (ADA), serum albumin, serum lactate dehydrogenase, total protein, PF-LDH/ADA, and PF-LDH/TP provided the best predictive capacity with an overall accuracy of 84.8%; the sensitivity and specificity for TPE diagnosis were 100% and 98.7%, respectively.

Conclusion

The biomarkers and ratios showed good diagnostic performance, and a decision-tree with an overall accuracy of 84.8% was developed to differentiate the five types of PE in clinical settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01459-w.

Diagnostic Value of C-Reactive Protein in Discrimination between Uncomplicated and Complicated Parapneumonic Effusion

Objectives: The role of serum C-reactive protein (CRPs) and pleural fluid CRP (CRPpf) in discriminating uncomplicated parapneumonic effusion (UCPPE) from complicated parapneumonic effusion (CPPE) is yet to be validated since most of the previous studies were on small cohorts and with variable results. The role of CRPs and CRPpf gradient (CRPg) and of their ratio (CRPr) in this discrimination has not been previously reported. The study aims to assess the diagnostic efficacy of CRPs, CRPpf, CRPr, and CRPg in discriminating UCPPE from CPPE in a relatively large cohort. Methods: The study population included 146 patients with PPE, 86 with UCPPE and 60 with CPPE. Levels of CRPs and CRPpf were measured, and the CRPg and CRPr were calculated. The values are presented as mean ± SD. Results: Mean levels of CRPs, CRPpf, CRPg, and CRPr of the UCPPE group were 145.3 ± 67.6 mg/L, 58.5 ± 38.5 mg/L, 86.8 ± 37.3 mg/L, and 0.39 ± 0.11, respectively, and for the CPPE group were 302.2 ± 75.6 mg/L, 112 ± 65 mg/L, 188.3 ± 62.3 mg/L, and 0.36 ± 0.19, respectively. Levels of CRPs, CRPpf, and CRPg were significantly higher in the CPPE than in the UCPPE group (p < 0.0001). No significant difference was found between the two groups for levels of CRPr (p = 0.26). The best cut-off value calculated by the receiver operating characteristic (ROC) analysis for discriminating UCPPE from CPPE was for CRPs, 211.5 mg/L with area under the curve (AUC) = 94% and p < 0.0001, for CRPpf, 90.5 mg/L with AUC = 76.3% and p < 0.0001, and for CRPg, 142 mg/L with AUC = 91% and p < 0.0001. Conclusions: CRPs, CRPpf, and CRPg are strong markers for discrimination between UCPPE and CPPE, while CRPr has no role in this discrimination.