Research progress on biomarkers of pulmonary embolism

Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis

Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.

Role of serum biomarkers in predicting management strategies for acute pulmonary embolism

Background

Acute pulmonary embolism (APE) is a condition that can be fatal. The severity of the disease influences therapeutic decisions, and mortality varies significantly depending on the condition's severity. Identification of patients with a high mortality risk is crucial. Since inflammation, hemostatic, and coagulation abnormalities are linked to APE, serum biomarkers may be helpful for prognostication.

Aim

To evaluate the significance of serum biomarkers in APE risk assessment and the suitability of these biomarkers for management and decision-making.

Methods

This study involved 60 adult patients with APE who were divided according to risk categorization. It was conducted in Chest, Cardiology and Internal Medicine department, Zagazig University Hospitals from December 2022 to May 2023. Several hematological biomarkers and their significance in APE risk assessment were measured with a comparison with the latest risk stratification methods which include haemodynamic measures and right ventricular (RV) dysfunction echocardiographic markers.

Results

Each risk group involved 20 patients (high, intermediate (10 were intermediate-high and 10 were intermediate-low) and low risk group). They were 34 females and 26 males with the mean ± SD of their age was 59.25 ± 13.06 years. Regarding hematological biomarkers, there were statistically significant differences as regards; lymphocytes, platelet to lymphocyte ratio (PLR), albumin, blood urea nitrogen (BUN), C-reactive protein (CRP) and D-dimer with highly statistically significant differences as regards; neutrophil to lymphocyte ratio (NLR), BUN to albumin (B/A) ratio, troponin I (TnI), and brain natriuretic peptide (BNP). TnI had the highest specificity and predictive value positive (PVP) and BNP had the highest sensitivity and predictive value negative (PVN) in predicting high risk groups. The Lymphocyte and NLR showed the lowest sensitivity and the albumin and B/A ratio had the lowest specificity. Regarding transthoracic echocardiography (TEE); there was a statistically significant increase regarding pulmonary artery systolic pressure (PASP) and a highly statistically significant increase regarding the right ventricle/left ventricle (RV/LV) ratio. There were statistically significant decreases regarding tricuspid annular plane systolic excursion (TAPSE) and peak systolic velocity of tricuspid annulus (S') among risk groups.

Conclusion

APE prognosis can be judged accurately by simultaneously measuring a few biomarkers along with haemodynamic variables and echocardiographic parameters of RV dysfunction.

C-Reactive Protein: Pathophysiology, Diagnosis, False Test Results and a Novel Diagnostic Algorithm for Clinicians

The current literature provides a body of evidence on C-Reactive Protein (CRP) and its potential role in inflammation. However, most pieces of evidence are sparse and controversial. This critical state-of-the-art monography provides all the crucial data on the potential biochemical properties of the protein, along with further evidence on its potential pathobiology, both for its pentameric and monomeric forms, including information for its ligands as well as the possible function of autoantibodies against the protein. Furthermore, the current evidence on its potential utility as a biomarker of various diseases is presented, of all cardiovascular, respiratory, hepatobiliary, gastrointestinal, pancreatic, renal, gynecological, andrological, dental, oral, otorhinolaryngological, ophthalmological, dermatological, musculoskeletal, neurological, mental, splenic, thyroid conditions, as well as infections, autoimmune-supposed conditions and neoplasms, including other possible factors that have been linked with elevated concentrations of that protein. Moreover, data on molecular diagnostics on CRP are discussed, and possible etiologies of false test results are highlighted. Additionally, this review evaluates all current pieces of evidence on CRP and systemic inflammation, and highlights future goals. Finally, a novel diagnostic algorithm to carefully assess the CRP level for a precise diagnosis of a medical condition is illustrated.

Right ventricular area predicts short-term mortality in acute pulmonary embolism based on CT pulmonary angiography: A retrospective study

We performed this cohort study to assess the prognostic value of right ventricular size, including diameter, area, and volume, in short-term mortality of acute pulmonary embolism (APE) based on 256-slice computed tomography compared with D-dimer, creatine kinase muscle and brain isoenzyme, and Wells scores. A total of 225 patients with APE, who were followed up for 30 days were enrolled in this cohort study. Clinical data, laboratory indices (creatine kinase, creatine kinase muscle and brain isoenzyme, and D-dimer), and Wells scores were collected. The 256-slice computed tomography was used to quantify cardiac parameters (RVV/LVV, RVD/LVD-ax, RVA/LVA-ax, RVD/LVD-4ch, RVA/LVA-4ch) and the diameter of the coronary sinus. Participants were divided into non-death and death groups. The values mentioned above were compared between the 2 groups. The RVD/LVD-ax, RVA/LVA-ax, RVA/LVA-4ch, RVV/LVV, D-dimer, and creatine kinase levels were significantly higher in the death group than in the non-death group (P < .05). The active period of the malignant tumor, heart rate ≥ 100 beats/minutes, and RVA/LVA-ax were positively correlated with early death from APE (P < .05). Active stage of malignant tumor (OR:9.247, 95%CI:2.682-31.888, P < .001) and RVA/LVA-ax (OR:3.073, 95%CI:1.447-6.528, P = .003) were independent predictors of early death due to APE. According to the receiver operating characteristic curve, the cutoff point of RVA/LVA-ax was 1.68 with a sensitivity of 46.7% and specificity of 84.8%. The measurement of ventricular size in the short-axis plane is more convenient and reliable than that in the 4-chamber cardiac plane. RVA/LVA-ax is an independent predictor of early death from APE, and when RVA/LVA-ax > 1.68, the risk of early death from APE increases.

A new machine learning model for predicting severity prognosis in patients with pulmonary embolism: Study protocol from Wenzhou, China

Introduction

Pulmonary embolism (PE) is a common thrombotic disease and potentially deadly cardiovascular disorder. The ratio of clinical misdiagnosis and missed diagnosis of PE is very large because patients with PE are asymptomatic or non-specific.

Methods

Using the clinical data from the First Affiliated Hospital of Wenzhou Medical University (Wenzhou, China), we proposed a swarm intelligence algorithm-based kernel extreme learning machine model (SSACS-KELM) to recognize and discriminate the severity of the PE by patient's basic information and serum biomarkers. First, an enhanced method (SSACS) is presented by combining the salp swarm algorithm (SSA) with the cuckoo search (CS). Then, the SSACS algorithm is introduced into the KELM classifier to propose the SSACS-KELM model to improve the accuracy and stability of the traditional classifier.

Results

In the experiments, the benchmark optimization performance of SSACS is confirmed by comparing SSACS with five original classical methods and five high-performance improved algorithms through benchmark function experiments. Then, the overall adaptability and accuracy of the SSACS-KELM model are tested using eight public data sets. Further, to highlight the superiority of SSACS-KELM on PE datasets, this paper conducts comparison experiments with other classical classifiers, swarm intelligence algorithms, and feature selection approaches.

Discussion

The experimental results show that high D-dimer concentration, hypoalbuminemia, and other indicators are important for the diagnosis of PE. The classification results showed that the accuracy of the prediction model was 99.33%. It is expected to be a new and accurate method to distinguish the severity of PE.

Diagnostic accuracy of adropin as a preliminary test to exclude acute pulmonary embolism: a prospective study

Background

This study aims to investigate the diagnostic accuracy of adropin as a biomarker to exclude the diagnosis of acute pulmonary embolism (PE).

Methods

Patients admitted to the emergency department of a tertiary health centre between August 2019 and August 2020 and diagnosed with PE were included in this prospective cohort study. The amount of serum adropin was determined in patients with (PE) and compared with that of healthy volunteers. Receiver operating characteristic analysis was performed with the obtained data, and the area under the curve (AUC) with a 95% confidence interval was determined. The parameters of diagnostic accuracy for PE were determined.

Results

A total of 57 participants were included in the study (28 controls and 29 PE patients). The mean adropin level in the PE group was 187.33 ± 62.40 pg/ml, which was significantly lower than that in the control group (524.06 ± 421.68 pg/ml) (p < 0.001). When the optimal adropin cut-off value was 213.78 pg/ml, the likelihood ratio of the adropin test was 3.4, and the sensitivity of the adropin test at this value was 82% with specificity of 75% (95% CI; AUC: 0.821).

Conclusion

Our results suggest that adropin may be considered for further study as a candidate marker for the exclusion of the diagnosis of PE. However, more research is required to verify and support the generalizability of our study results.

Pulmonary Embolism Presenting with Pulmonary Infarction: Update and Practical Review of Literature Data

Pulmonary infarction (PI) is a possible consequence of pulmonary embolism (PE). The real incidence of PI could be underestimated considering only non-fatal PE presentation. However, following postmortem examination, the prevalence of PI is considerably higher. This evidence suggests the necessity of proper diagnostic protocol for identifying PI. Unfortunately, PI diagnosis can sometimes be challenging, due to the overlapping of symptoms with other diseases. Nowadays, the diagnosis is mainly based on radiological evaluation, although the combination with emerging imaging techniques such as ultrasound and nuclear scanning might improve the diagnostic algorithm for PI. This review aims to summarize the available data on the prevalence of PI, the main predisposing factors for the development of PI among patients with PE, to resume the possible diagnostic tools, and finally the clinical and prognostic implications.

Proteomics in thrombosis research

A State of the Art lecture titled “Proteomics in Thrombosis Research” was presented at the ISTH Congress in 2021. In clinical practice, there is a need for improved plasma biomarker‐based tools for diagnosis and risk prediction of venous thromboembolism (VTE). Analysis of blood, to identify plasma proteins with potential utility for such tools, could enable an individualized approach to treatment and prevention. Technological advances to study the plasma proteome on a large scale allows broad screening for the identification of novel plasma biomarkers, both by targeted and nontargeted proteomics methods. However, assay limitations need to be considered when interpreting results, with orthogonal validation required before conclusions are drawn. Here, we review and provide perspectives on the application of affinity‐ and mass spectrometry‐based methods for the identification and analysis of plasma protein biomarkers, with potential application in the field of VTE. We also provide a future perspective on discovery strategies and emerging technologies for targeted proteomics in thrombosis research. Finally, we summarize relevant new data on this topic, presented during the 2021 ISTH Congress.