Thromboinflammation and the Role of Platelets

From Circulating Biomarkers to Polymorphic Variants: A Narrative Review of Challenges in Thrombophilia Evaluation

Thrombophilia is characterized by a hypercoagulable state that predisposes individuals to venous and arterial thrombotic events, posing significant challenges for clinical evaluation and management. This narrative review critically examines the current landscape of thrombophilia testing, focusing on the utility and limitations of both circulating and genetic biomarkers. Circulating biomarkers-such as D-dimer, antithrombin, protein C, and protein S-offer dynamic insights into the coagulation process yet often suffer from low specificity in varied clinical settings. In contrast, genetic biomarkers, notably Factor V Leiden and the prothrombin G20210A mutation, provide stable risk stratification but are limited by their low prevalence in the general population. Emerging markers, including selectins, Factor VIII, Factor XI, neutrophil extracellular traps, and extracellular vesicles, are also discussed for their potential to refine thrombotic risk assessment. By integrating evidence-based guidelines from international health organizations, this review underscores the need for a personalized approach to thrombophilia evaluation that balances comprehensive risk assessment with the avoidance of over-testing. Such an approach is crucial for optimizing patient outcomes and informing the duration and intensity of anticoagulant therapy.

The Red Blood Cell Distribution Width to Albumin Ratio Is Associated with in Hospital Mortality and Adverse Outcome in Elderly Chinese Patients with Gastrointestinal Bleeding

Background

Gastrointestinal bleeding (GIB) in elderly patients is a common and life-threatening condition, often complicated by comorbidities. The ratio of red blood cell distribution width to albumin (RAR) has recently been proposed as a prognostic marker in various diseases, but its role in predicting adverse outcomes in GIB patients remains unclear.

Methods

A total of 51,824 aged 65 years or older patients were initially screened for inclusion in the study. After excluding those lost to follow-up, with missing vital information during the screening period (n = 50,423), 1401 hospitalized patients with GIB in Beijing Hospital (2013-2019) were included. Restricted cubic spline modeling and logistic regression analyses assessed the relationships between RAR, adverse outcomes, and in hospital mortality.

Results

Among the 1, 401 patients, 648 experienced adverse outcomes, and 427 patients died during hospitalization. Higher RAR was significantly associated with an increased risk of both in-hospital mortality and adverse outcomes, even after adjusting for age, sex, education level, body mass index (BMI), chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), cancer, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), white blood cell count (WBC), estimated glomerular filtration rate (eGFR), hemoglobin, heart failure, blood urea nitrogen (BUN), and heart rate.

Conclusion

RAR is a novel and independent predictor of mortality and adverse outcomes in elderly patients with GIB. Its simplicity and cost-effectiveness make it a valuable tool for identifying high-risk patients. Further studies in larger, multicenter cohorts are needed to confirm these findings and evaluate the clinical benefits of RAR-based interventions.

Special Issue "Molecular Research on Platelet Activity in Health and Disease 2024"

Platelets, once viewed primarily for their role in hemostasis, are now recognized to play a pivotal role in a broad spectrum of physiological and pathological processes, including thrombosis [...].

Enhanced preoperative prediction of pancreatic fistula using radiomics and clinical features with SHAP visualization

Background

Clinically relevant postoperative pancreatic fistula (CR-POPF) represents a significant complication after pancreaticoduodenectomy (PD). Therefore, the early prediction of CR-POPF is of paramount importance. Based on above, this study sought to develop a CR-POPF prediction model that amalgamates radiomics and clinical features to predict CR-POPF, utilizing Shapley Additive explanations (SHAP) for visualization.

Methods

Extensive radiomics features were extracted from preoperative enhanced Computed Tomography (CT) images of patients scheduled for PD. Subsequently, feature selection was performed using Least Absolute Shrinkage and Selection Operator (Lasso) regression and random forest (RF) algorithm to select pertinent radiomics and clinical features. Last, 15 CR-POPF prediction models were developed using five distinct machine learning (ML) predictors, based on selected radiomics features, selected clinical features, and a combination of both. Model performance was compared using DeLong's test for the area under the receiver operating characteristic curve (AUC) differences.

Results

The CR-POPF prediction model based on the XGBoost predictor with the combination of the radiomics and clinical features selected by Lasso regression and RF exhibited superior performance among these 15 CR-POPF prediction models, achieving an accuracy of 0.85, an AUC of 0.93. DeLong's test showed statistically significant differences (P < 0.05) when compared to the radiomics-only and clinical-only models, with recall of 0.63, precision of 0.65, and F1 score of 0.64.

Conclusion

The proposed CR-POPF prediction model based on the XGBoost predictor with the combination of the radiomics and clinical features selected by Lasso regression and RF can effectively predicting the CR-POPF and may provide strong support for early clinical management of CR-POPF.

Machine Learning-Based Immuno-Inflammatory Index Integrating Clinical Characteristics for Predicting Coronary Artery Plaque Rupture

BACKGROUND

Coronary artery plaque rupture (PR) is closely associated with immune-inflammatory responses. The systemic inflammatory index (SII) and the systemic inflammatory response index (SIRI) have shown potential in predicting the occurrence of PR.

OBJECTIVE

This study aims to establish a machine learning (ML) model that integrates baseline patient characteristics, SII, and SIRI to predict PR. The goal is to identify high-risk PR patients before intravascular imaging examinations.

METHODS

We included 337 patients with acute coronary syndrome who underwent emergency percutaneous coronary intervention and coronary optical coherence tomography (OCT) at the Affiliated Hospital of Zunyi Medical University, China, from May 2023 to October 2023. PR was determined by OCT images. Through manual feature selection, nine features, including SII and SIRI, were included, and an ML model was built using the XGBoost algorithm. Model performance was evaluated using receiver operating characteristic curves and calibration curves. SHAP values were used to assess the contribution of each feature to the model.

RESULTS

The ML model demonstrated a higher area under the curve value (AUC = 0.81) compared to using SII or SIRI alone for prediction. The ML model also showed good calibration. SHAP values revealed that the top three features in the ML model were SII, LDL-C, and SIRI.

CONCLUSION

The immuno-inflammatory index, which integrates comprehensive clinical characteristics, can predict the occurrence of PR. However, large-scale, multicenter studies are needed to confirm the generalizability of the predictive model.

Circulating, Extracellular Vesicle-Associated Tissue Factor in Cancer Patients with and without Venous Thromboembolism

Cancer is characterized by chronic inflammation and hypercoagulability, with an excess of venous thromboembolism (VTE). Tissue factor, the initiator of blood coagulation, circulates associated with extracellular vesicles (EV-TF). Studies investigating EV-TF between cancer-associated and non-cancer-associated VTE are lacking. We therefore compared EV-TF in unprovoked VTE (U-VTE), cancer-associated VTE (C-VTE), and cancer without VTE (C-w/o VTE). We also investigated interleukin-6 (IL-6) levels between the same groups. The final population included 68 patients (U-VTE: n = 15; C-VTE: n = 24; C-w/o VTE: n = 29). All patients with VTE were enrolled within 48 h of diagnosis; non-VTE patients were recruited in the oncologic outpatient services. EV were isolated by differential centrifugation from 4 mL of peripheral blood; the final EV pellet (16,000× g for 45 min) was resuspended in 100 μL saline and tested for TF using a one-step clotting assay. There was a statistically significant difference for higher EV-TF in C-VTE and C-w/o VTE compared to U-VTE (p = 0.024; Kruskal-Wallis test). There was no significant difference between C-VTE and C-w/o VTE. Moreover, we did not find any difference in IL-6 levels. These preliminary data suggest that cancer represents, per se, a strong driver of EV-TF generation.

Acetaminophen Overdose Reveals PAR4 as a Low-Expressing but Potent Receptor on the Hepatic Endothelium in Mice

BACKGROUND

The protease thrombin, which elicits multiple physiological and pathological effects on vascular endothelial cells (ECs), can signal through PARs (protease-activated receptors) 1 and 4. PAR1 is a high-affinity thrombin receptor known to signal on ECs, whereas PAR4 is a low-affinity thrombin receptor, and evidence for its expression and function on ECs is mixed. This study aims to exploit the high levels of thrombin generation and hepatic vascular dysfunction that occur during acetaminophen (APAP) overdose to determine (1) whether hepatic endothelial PAR4 is a functional receptor, and (2) the endothelial-specific functions for PAR1 and PAR4 in a high thrombin and pathological setting.

METHODS

We generated mice with conditional deletion of Par1/Par4 in ECs and overdosed them with APAP. Hepatic vascular permeability, erythrocyte accumulation in the liver, thrombin generation, and liver function were assessed following overdose. Additionally, we investigated the expression levels of endothelial PARs and how they influence transcription in APAP-overdosed liver ECs using endothelial translating ribosome affinity purification followed by next-generation sequencing.

RESULTS

We found that mice deficient in high-expressing endothelial Par1 or low-expressing Par4 had equivalent reductions in APAP-induced hepatic vascular instability, although mice deficient for both receptors had lower vascular permeability at an earlier timepoint after APAP overdose than either of the single mutants. Additionally, mice with loss of both endothelial Par1 and Par4 had reduced thrombin generation after APAP overdose, suggesting decreased hypercoagulability. Last, we found that endothelial PAR1-but not PAR4-can regulate transcription in hepatic ECs.

CONCLUSIONS

Low-expressing PAR4 can react similarly to high-expressing PAR1 in APAP-overdosed hepatic ECs, demonstrating that PAR4 is a potent thrombin receptor. Additionally, these receptors are functionally redundant but act divergently in their expression and ability to influence transcription in hepatic ECs.

Apelin-13 as a novel diagnostic laboratory biomarker in thromboembolic disorders: a review of literature with prospective insights

Thromboembolic disorders, including deep vein thrombosis (DVT) and pulmonary embolism (PE), are major global health concerns, causing significant morbidity and mortality. Early diagnosis is crucial for effective treatment and improved patient outcomes. Recent research has identified Apelin-13, a bioactive peptide in the apelin family, as a promising diagnostic biomarker for Thromboembolic disorders. Apelin-13 supports vascular health by regulating protease balance through plasminogen activator inhibitors and modulating endothelial cell function. Additionally, it plays a vital role in coagulation, with elevated levels associated with an increased risk of clot formation, suggesting its utility in predicting thrombosis risk, particularly in preoperative evaluations. Findings indicate that the Apelin-13 pathway shows significant promise as a biomarker for Thromboembolic disorders, underscoring its potential therapeutic applications and the need for further investigation. This review synthesizes current literature on thromboembolic disorders and associated laboratory biomarkers, with a particular focus on Apelin-13. It examines Apelin-13's role in disease mechanisms, its physiological functions, and its potential as a diagnostic biomarker in thromboembolic conditions.

Association between platelet-to-red cell distribution width ratio and all-cause mortality in critically ill patients with non-traumatic cerebral hemorrhage: a retrospective cohort study

Background

The purpose of this study was to investigate the relationship between platelet-to-red cell distribution width ratio (PRR) and all-cause mortality in critically ill patients with non-traumatic cerebral hemorrhage (NCH).

Methods

The Medical Information Mart for Intensive Care (MIMIC-IV) database was used to identify patients with NCH who needed to be admitted to intensive care unit (ICU). The outcomes of the study included both ICU and in-hospital mortality. Restricted cubic splines and Cox proportional hazards regression analysis were used to clarify the relationship between PRR and clinical outcomes in critically ill patients with NCH.

Results

A total of 3,094 patients (54.0% male) were included in the study, with in-hospital mortality and ICU mortality rates of 16.5 and 11.8%, respectively. A substantial correlation was found by multivariate Cox proportional hazards analysis between increased PRR and a lower risk of in-hospital and ICU mortality. Following adjustment for confounding factors, patients with elevated PRR exhibited a significantly decreased risk of in-hospital death (HR, 0.98; 95% CI, 0.96-0.99; p = 0.006) and ICU death (HR, 0.98; 95% CI, 0.96-0.99; p = 0.027). As PRR increased, restrictive cubic splines showed a progressive decrease in the probability of all-cause mortality. Stratified analyses indicated a consistent association between PRR and both in-hospital and ICU mortality.

Conclusion

Among critically ill patients with NCH, lower PRR was substantially correlated with the increased probability of all-cause mortality in both the ICU and hospital. According to this research, PRR might be a valuable indicator for identifying NCH patients at risk of all-cause mortality.

TO SHOw how we have been ENgaged in the APS FiELD (What we learned on APS collaborating with Professor Yehuda Shoenfeld)

The present review reports the history of our scientific collaboration with Professor Shoenfeld's group. The collaboration started at the end of the 80s and was mainly focused on studies on the pathogenetic mechanisms of the anti-phospholipid syndrome (APS). Following the initial collaborative studies on antibodies against endothelium in systemic autoimmune vasculitis, we were able to use a similar strategy in APS. This line of research has resulted in the characterization of beta 2 glycoprotein I (β2GPI)-dependent anti-phospholipid antibodies (aPL) as mechanisms capable of mediating an endothelial perturbation crucial for the pathogenesis of APS. Thanks to these studies, the collaboration has led to the characterization of the membrane receptors for β2GPI and the cellular signaling resulting from antibody binding. This mechanism has also been shown to mediate the aPL effect on other cell types involved in APS pathogenesis. Finally, the exchange of information made it possible to replicate and extend the setting of animal models of the syndrome, which proved to be valuable tools for understanding the pathogenesis of the syndrome. It has been a long story recently refueled by common studies on the similarity of pro-inflammatory and pro-coagulant endotheliopathy in APS and in COVID-19.

Pharmacological mechanisms by which baicalin ameliorates cardiovascular disease

Baicalin is a flavonoid glycoside obtained from the dried root of Scutellaria baicalensis Georgi, which belongs to the Labiatae family. Accumulating evidence indicates that baicalin has favorable therapeutic effects on cardiovascular diseases. Previous studies have revealed the therapeutic effects of baicalin on atherosclerosis, myocardial ischemia/reperfusion injury, hypertension, and heart failure through anti-inflammatory, antioxidant, and lipid metabolism mechanisms. In recent years, some new ideas related to baicalin in ferroptosis, coagulation and fibrinolytic systems have been proposed, and new progress has been made in understanding the mechanism by which baicalin protects cardiomyocytes. However, many relevant underlying mechanisms remain unexplained, and much experimental data is lacking. Therefore, further research is needed to determine these mechanisms. In this review, we summarize the mechanisms of baicalin, which include its anti-inflammatory and antioxidant effects; inhibition of endothelial cell apoptosis; modulation of innate immunity; suppression of vascular smooth muscle cells proliferation, migration, and contraction; regulation of coagulation and fibrinolytic systems; inhibition of myocardial hypertrophy; prevention of myocardial fibrosis; and anti-apoptotic effects on cardiomyocytes.