Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model.

BACKGROUND: Portal vein thrombosis (PVT) is a significant issue in cirrhotic patients, necessitating early detection. This study aims to develop a data-driven predictive model for PVT diagnosis in chronic hepatitis liver cirrhosis patients. METHODS: We employed data from a total of 816 chronic cirrhosis patients with PVT, divided into the Lanzhou cohort (n = 468) for training and the Jilin cohort (n = 348) for validation. This dataset encompassed a wide range of variables, including general characteristics, blood parameters, ultrasonography findings and cirrhosis grading. To build our predictive model, we employed a sophisticated stacking approach, which included Support Vector Machine (SVM), Naïve Bayes and Quadratic Discriminant Analysis (QDA). RESULTS: In the Lanzhou cohort, SVM and Naïve Bayes classifiers effectively classified PVT cases from non-PVT cases, among the top features of which seven were shared: Portal Velocity (PV), Prothrombin Time (PT), Portal Vein Diameter (PVD), Prothrombin Time Activity (PTA), Activated Partial Thromboplastin Time (APTT), age and Child-Pugh score (CPS). The QDA model, trained based on the seven shared features on the Lanzhou cohort and validated on the Jilin cohort, demonstrated significant differentiation between PVT and non-PVT cases (AUROC = 0.73 and AUROC = 0.86, respectively). Subsequently, comparative analysis showed that our QDA model outperformed several other machine learning methods. CONCLUSION: Our study presents a comprehensive data-driven model for PVT diagnosis in cirrhotic patients, enhancing clinical decision-making. The SVM-Naïve Bayes-QDA model offers a precise approach to managing PVT in this population.

Novel Strategy for Human Deep Vein Thrombosis Diagnosis Based on Metabolomics and Stacking Machine Learning.

Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learning methods has led to high diagnostic and prognostic accuracy for various pathological conditions. This study explored the synergistic potential of dual-platform metabolomics (specifically, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS)) to expand the detection of metabolites and improve the precision of DVT diagnosis. Sixty-one differential metabolites were identified in serum from DVT patients: 22 from GC-MS and 39 from LC-MS. Among these, five key metabolites were highlighted by SHapley Additive exPlanations (SHAP)-guided feature engineering and then used to develop a stacking diagnostic model. Additionally, a user-friendly interface application system was developed to streamline and automate the application of the diagnostic model, enhancing its practicality and accessibility for clinical use. This work showed that the integration of dual-platform metabolomics with a stacking machine learning model enables faster and more accurate diagnosis of DVT in clinical environments.

2023 ACR/EULAR classification criteria in existing research cohorts: an international study.

OBJECTIVE: To assess the impact of the updated ACR/EULAR APS classification criteria on two large research cohorts. METHODS: Consecutive patients who tested persistently positive for at least one aPL in the last three years were enrolled. The first APS Sydney index event was considered and computed for the comparison between Sydney and 2023 APS criteria. When computing the 2023 APS criteria, additional manifestations were also considered. RESULTS: The cohort comprised 249 patients (185 with APS and 64 aPL carriers according to Sydney criteria). The 185 patients had as first index event venous thrombosis in 55 cases (29.8%), arterial thrombosis in 63 (34%) and pregnancy morbidity in 67 (36.2%). When applying the updated criteria, 90 subjects (48.7%) failed to reach the composite score of the new criteria. The percentage of thrombotic APS per Sydney criteria decreased from 47.3% to 34.9% because of high cardiovascular risk in 23 cases, IgM aPL profile in six cases and in two patients for both reasons. Patients with pregnancy morbidity decreased from 26.9% to 3.2% (39 cases of recurrent early pregnancy loss and 20 of fetal losses). Consequently, the percentage of aPL carriers increased from 26% to 61%. When looking at the disease evolution at follow-up, 32 additional patients out of 90 (35.6%) fulfilled the new APS criteria, after developing additional clinical manifestation following index event. CONCLUSION: When applying the new APS criteria to our research cohorts, not-negligible differences exist in patients' classification. A multidisciplinary approach will be mandatory to assess the impact of the new criteria on research and, ultimately, patients' care.

An international survey of venous thromboembolic events and current practices of peri-operative VTE prophylaxis after living donor hepatectomy.

BACKGROUND: Venous thromboembolic complications are an uncommon but significant cause of morbidity & mortality after live donor hepatectomy . The precise incidence of these events and the current practices of centers performing living donor liver transplantation worldwide are unknown. METHODS: An online survey was shared amongst living donor liver transplantation centers containing questions regarding center activity, center protocols for donor screening, peri-operative thromboembolic prophylaxis and an audit of -perioperative venous thromboembolic events after live donor hepatectomy in the previous five years (2016-2020). RESULTS: Fifty-one centers from twenty countries completed the survey. These centers had cumulatively performed 11500 living donor liver transplants between 2016-2020. All centers included pre-operative l assessment for thromboembolic risk amongst potential liver donors in their protocols. Testing for inherited prothrombotic conditions was performed by 58% of centers. Dual-mode prophylaxis was the most common practice (65%), while eight and four centers used single mode or no routine prophylaxis respectively. Twenty (39%) and 15 (29%) centers reported atleast one perioperative deep venous thrmobosis or pulmonary embolism event respectively. There was one donor mortality directly related to post-operative pulmonary embolism. Overall incidence of deep venous thrombosis and pulmonary embolism events was 3.65 and 1.74 per 1000 live donor hepatectomies respectively. Significant variations in center practices and incidence of thromboembolic events was identified in the survey primarily divided along world regions. 75% of participating centers agreed on the need for clear international guidelines. CONCLUSION: Venous thromboembolic events after live donor hepatectomy are an uncommon but important cause of donor morbidity. There is significant variation in practice among centers. Evidence-based guidelines regarding risk assessment, and peri-operative prophylaxis are needed.

Deep vein thrombosis in patients with stroke or transient ischemic attack presenting with patent foramen ovale: a retrospective observational study.

OBJECTIVE: Deep vein thrombosis (DVT) is discussed as a source of embolism for cerebral ischemia in the presence of patent foramen ovale (PFO). However, previous studies reported varying rates of DVT in stroke patients, and recommendations for screening are lacking. This study aimed to characterize patients with stroke or transient ischemic attack (TIA) and concomitant PFO and explore the rate of DVT and associated parameters. METHODS: Medical records were screened for patients with stroke or TIA and echocardiographic evidence of PFO. Concomitant DVT was identified according to compression ultrasonography of the lower limbs. A variety of demographic, clinical, and laboratory parameters, the RoPE and Wells scores were compared between patients with and without DVT. RESULTS: Three-hundred-thirty-nine patients (mean age 61.2 ± 15.4 years, 61.1% male) with stroke or TIA and PFO, treated between 01/2015 and 12/2020, were identified. Stroke and TIA patients did not differ for demographic and vascular risk factors. DVT was found in 17 cases out of 217 (7.8%) with compression ultrasonography. DVT was associated with a history of DVT, cancer, previous immobilization, calf compression pain, calf circumference difference, and a few laboratory abnormalities, e.g., increased D-dimer. A multivariate regression model with stepwise backward selection identified the Wells score (odds ratio 35.46, 95%-confidence interval 4.71-519.92) as a significant predictor for DVT. CONCLUSION: DVT is present in a relevant proportion of patients with cerebral ischemia and PFO, which needs to be considered for the individual diagnostic workup. The Wells score seems suitable for guiding additional examinations, i.e., compression ultrasonography.

Factor XI/XIa inhibitors for the prevention and treatment of venous and arterial thromboembolism: A narrative review.

During the past decade, direct oral anticoagulants (DOACs) have advanced and simplified the prevention and treatment of venous thromboembolism (VTE). However, there remains a high incidence of bleeds, which calls for agents that have a reduced risk of bleeding. Factor XI (FXI) deficiency is associated with lower rates of venous thrombosis and stroke compared to the general population with a lower risk of bleeding. In conjunction with this, phase 2 studies have demonstrated safety and the potential for reduced thrombotic events with FXI inhibitors as compared to currently available medications. The aim of this review is to summarize key data on the clinical pharmacology of FXI, the latest developments in clinical trials of FXI inhibitors, and to describe the efficacy and safety profiles of FXI inhibitors for the prevention of venous and arterial thromboembolism.

Independent association between IVC filter placement and VTE risk in patients with upper gastrointestinal bleeding and isolated distal DVT: A retrospective cohort study.

BACKGROUND: The placement of inferior vena cava (IVC) filters often emerges as an alternative preventative measure against pulmonary embolism in patients with upper gastrointestinal (GI) bleeding and isolated distal deep vein thrombosis (DVT). We aimed to investigate the association of IVC filter placement and the incidence of venous thromboembolism (VTE) recurrence in this patient population. METHODS: We performed a retrospective cohort study including 450 patients with upper GI bleeding and isolated distal DVT. Propensity score matching using logistic regression was conducted to mitigate potential selection bias. Logistic regression models and additional sensitivity analyses were conducted to estimate the association between IVC filter implantation and VTE recurrence. Interaction and stratified analyses were also performed according to the background covariates. RESULTS: Patients who underwent IVC filter placement were significantly younger than patients in the surveillance group (55.8 ± 9.0 vs 58.4 ± 11.2 years, p = 0.034). Patients in the IVC filter group demonstrated a higher distal thrombus burden. The VTE recurrence composite was significantly higher in patients who underwent IVC filter placement (44.1% [45/102] vs 25% [87/348], p < 0.001). Unmatched crude logistic regression analysis identified a significant association between IVC filter placement and VTE recurrence composite (OR = 2.37; 95% CI, 1.50-3.75). Sensitivity analyses yielded congruent outcomes. CONCLUSION: This study revealed an increased risk of VTE recurrence among patients receiving IVC filter placement, suggesting that IVC filter placement may not be suitable as a primary treatment for patients with upper GI bleeding and isolated distal DVT.

Discovery of crucial cytokines associated with deep vein thrombus formation by protein array analysis.

BACKGROUND: Expanding the number of biomarkers is imperative for studying the etiology and improving venous thromboembolism prediction. In this study, we aimed to identify promising biomarkers or targeted therapies to improve the detection accuracy of early-stage deep vein thrombosis (DVT) or reduce complications. METHODS: Quantibody Human Cytokine Antibody Array 440 (QAH-CAA-440) was used to screen novel serum-based biomarkers for DVT/non-lower extremity DVT (NDVT). Differentially expressed proteins in DVT were analyzed using bioinformatics methods and validated using a customized array. Diagnostic accuracy was calculated using receiver operating characteristics, and machine learning was applied to establish a biomarker model for evaluating the identified targets. Twelve targets were selected for validation. RESULTS: Cytokine profiling was conducted using a QAH-CAA-440 (RayBiotech, USA) quantimeter array. Cross-tabulation analysis with Venn diagrams identified common differential factors, leading to the selection of 12 cytokines for validation based on their clinical significance. These 12 biomarkers were consistent with the results of previous array analysis: FGF-6 (AUC = 0.956), Galectin-3 (AUC = 0.942), EDA-A2 (AUC = 0.933), CHI3L1 (AUC = 0.911), IL-1 F9 (AUC = 0.898), Dkk-4 (AUC = 0.88), IG-H3 (AUC = 0.876), IGFBP (AUC = 0.858), Gas-1 (AUC = 0.858), Layilin (AUC = 0.849), ULBP-2 (AUC = 0.813)and FGF-9 (AUC = 0.773). These cytokines are expected to serve as biomarkers, targets, or therapeutic targets to differentiate DVT from NDVT. CONCLUSIONS: EDA-A2, FGF-6, Dkk-4, IL-1 F9, Galentin-3, Layilin, Big-h3, CHI3L1, ULBP-2, Gas-1, IGFBP-5, and FGF-9 are promising targets for DVT diagnosis and treatment.

The genetic effects of hormones modulated by the Pituitary-Thyroid/Adrenal/Gonadal axis on the risk of developing venous thromboembolism: a mendelian randomization study.

BACKGROUND: The aim of this study was to explore the genetic effects of hormones modulated through the pituitary-thyroid/adrenal/gonadal axis on the risk of developing venous thromboembolism (VTE) and to investigate the potentially causal relationships between them. METHODS: A two-sample Mendelian randomization (MR) design was used. The single-nucleotide polymorphisms (SNPs) used as instrumental variables for various hormones and hormone-mediated diseases were derived from published genome-wide association studies (GWASs). Summary statistics for the risk of developing VTE (including deep venous thrombosis [DVT] and pulmonary embolism [PE]) were obtained from the UK Biobank and the FinnGen consortium. Inverse-variance weighting (IVW) was applied as the primary method to analyse causal associations. Other MR methods were used for supplementary estimates and sensitivity analysis. RESULTS: A genetic predisposition to greater free thyroxine (FT4) concentrations was associated with a greater risk of developing DVT (OR = 1.0007, 95%CI [1.0001-1.0013], p = 0.0174) and VTE (OR = 1.0008, 95%CI [1.0002-1.0013], p = 0.0123). Genetically predicted hyperthyroidism was significantly associated with an increased risk of developing DVT (OR = 1.0685, 95%CI [1.0139-1.1261], p = 0.0134) and VTE (OR = 1.0740, 95%CI [1.0165-1.1348], p = 0.0110). According to the initial MR analysis, testosterone concentrations were positively associated with the risk of developing VTE (OR = 1.0038, 95%CI [1.004-1.0072], p = 0.0285). After sex stratification, estradiol concentrations were positively associated with the risk of developing DVT (OR = 1.0143, 95%CI [1.0020-1.0267], p = 0.0226) and VTE (OR = 1.0156, 95%CI [1.0029-1.0285], p = 0.0158) in females, while the significant relationship between testosterone and VTE did not persist. SHBG rs858518 was identified as the only SNP that was associated with an increased risk of developing VTE, mediated by estradiol, in females. CONCLUSIONS: Genetically predicted hyperthyroidism and increased FT4 concentrations were positively associated with the risk of developing VTE. The effects of genetically predicted sex hormones on the risk of developing VTE differed between males and females. Greater genetically predicted estradiol concentrations were associated with an increased risk of developing VTE in females, while the SHBG rs858518 variant may become a potential prevention and treatment target for female VTE.

Validity of Using Japanese Administrative Data to Identify Inpatients With Acute Pulmonary Embolism: Referencing the COMMAND VTE Registry.

BACKGROUND: Acute pulmonary embolism (PE) is a life-threatening in-hospital complication. Recently, several studies have reported the clinical characteristics of PE among Japanese patients using the diagnostic procedure combination (DPC)/per diem payment system database. However, the validity of PE identification algorithms for Japanese administrative data is not yet clear. The purpose of this study was to evaluate the validity of using DPC data to identify acute PE inpatients. METHODS: The reference standard was symptomatic/asymptomatic PE patients included in the COntemporary ManageMent AND outcomes in patients with Venous ThromboEmbolism (COMMAND VTE) registry, which is a cohort study of acute symptomatic venous thromboembolism (VTE) patients in Japan. The validation cohort included all patients discharged from the six hospitals included in both the registry and DPC database. The identification algorithms comprised diagnosis, anticoagulation therapy, thrombolysis therapy, and inferior vena cava filter placement. Each algorithm's sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were estimated. RESULTS: A total of 43.4% of the validation cohort was female, with a mean age of 67.3 years. The diagnosis-based algorithm showed a sensitivity of 90.2% (222/246; 95% confidence interval [CI], 85.8-93.6%), a specificity of 99.8% (228,485/229,027; 95% CI, 99.7-99.8%), a PPV of 29.1% (222/764; 95% CI, 25.9-32.4%) and an NPV of 99.9% (228,485/229,509; 95% CI, 99.9-99.9%) for identifying symptomatic/asymptomatic PE. Additionally, 94.6% (159/168; 95% CI, 90.1-97.5%) of symptomatic PE patients were identified using the diagnosis-based algorithm. CONCLUSION: The diagnosis-based algorithm may be a relatively sensitive method for identifying acute PE inpatients in the Japanese DPC database.

Venous Thrombosis in Acute Pancreatitis: What to and Not to Do?

Acute pancreatitis is an acute inflammatory condition of the pancreas that has not only local but systemic effects as well. Venous thrombosis is one such complication which can give rise to thrombosis of the peripheral vasculature in the form of deep vein thrombosis, pulmonary embolism, and splanchnic vein thrombosis. The prevalence of these complications increases with the severity of the disease and adds to the adverse outcomes profile. With better imaging and awareness, more cases are being detected, although many at times it can be an incidental finding. However, it remains understudied and strangely, most of the guidelines on the management of acute pancreatitis are silent on this aspect. This review offers an overview of the incidence, pathophysiology, symptomatology, diagnostic work-up, and management of venous thrombosis that develops in AP.

Association between serum uric acid and deep venous thrombosis in European populations: A two-sample Mendelian randomization study.

BACKGROUND AND AIM: Previous experimental and observational studies showed that serum uric acid (SUA) was associated with deep venous thrombosis (DVT), but the causal relationship is unclear. This study aimed to explore the potential causal association between SUA and DVT. METHODS AND RESULTS: We designed a two-sample Mendelian randomization (MR) analysis by using summary-level data from large genome-wide association studies performed in European individuals. A total of 14 SUA-related single-nucleotide polymorphisms (SNPs) (P value < 5 × 10-8) were identified as instrumental variables. The inverse variance weighted method was used as the primary method to compute the odds ratios (ORs) and 95 % confidence intervals (95 % CIs) for per standard deviation increase in SUA. MR Egger, weighted median, weighted mode, and simple mode were also applied to test the robustness of the results. We found no significant causal effects of serum uric acid on deep venous thrombosis (odds ratio [OR]: 1.000, 95 % confidence interval [CI]: 0.998-1.002, p = 0.78) by using inverse variance weighted. MR analyses based on other methods showed similar results. CONCLUSIONS: There was no potential causal associations between higher genetically predicted SUA levels and increased risk of deep venous thrombosis. Further, MR studies with more valid SNPs and more DVT cases are needed. Validation of the findings is also recommended.

Cerebral venous thrombosis and deep medullary vein thrombosis: Padua experience over the last two decades.

BACKGROUND: Cerebral venous thrombosis (CVT) is a cerebrovascular disorder that accounts for 20% of perinatal strokes. CVT incidence ranges from 0.67 to 1.12 per 100,000 newborns, while the incidence of "deep medullary vein thrombosis" (DMVT), a subtype of CVT, cannot be accurately estimated. This study aims to analyze the case history of CVT in the neonatal period, with a specific focus on DMVT. MATERIALS AND METHODS: Newborns diagnosed with CVT, with or without DMVT, between January 2002 and April 2023, were collected using the Italian Registry of Infantile Thrombosis (RITI). Cerebral MRIs were reviewed by an expert neuroradiologist following a standardized protocol. RESULTS: Forty-two newborns with CVT were identified, of which 27/42 (64%) had CVT, and the remaining 15/42 (36%) had DMVT (isolated DMVT in 9/15). Symptom onset occurred in the first week of life (median 8 days, IQR 4-14) with a male prevalence of 59%. The most common risk factors for CVT were complicated delivery (38%), prematurity (40%), congenital heart diseases (48%), and infections (40%). Seizures were the predominant presenting symptom in 52% of all cases. Hemorrhagic infarction was higher in cases with isolated DMVT (77%) compared to patients with CVT without DMVT (p = 0.013). Antithrombotic treatment was initiated in 36% of patients. Neurological impairment was observed in 48% of cases at discharge, while 18 out of 31 infants (58%) presented one or more neurological deficits at long term follow up.     Conclusion: DMVT occurs in over a third of neonates with CVT. Multicentric studies are essential to establish standardized protocols for therapy, neuroimaging, and follow-up in these patients.

Incidence and predictors of post-thrombotic syndrome in patients with proximal DVT in a real-world setting: findings from the GARFIELD-VTE registry.

Although substantial progress has been made in the pathophysiology and management of the post-thrombotic syndrome (PTS), several aspects still need clarification. Among them, the incidence and severity of PTS in the real world, the risk factors for its development, the value of patient's self-evaluation, and the ability to identify patients at risk for severe PTS. Eligible participants (n = 1107) with proximal deep-vein thrombosis (DVT) from the global GARFIELD-VTE registry underwent conventional physician's evaluation for PTS 36 months after diagnosis of their DVT using the Villalta score. In addition, 856 patients completed a Villalta questionnaire at 24 months. Variable selection was performed using stepwise algorithm, and predictors of severe PTS were incorporated into a multivariable risk model. The optimistic adjusted c-index was calculated using bootstrapping techniques. Over 36-months, 27.8% of patients developed incident PTS (mild in 18.7%, moderate in 5.7%, severe in 3.4%). Patients with incident PTS were older, had a lower prevalence of transient risk factors of DVT and a higher prevalence of persistent risk factors of DVT. Self-assessment of overall PTS at 24 months showed an agreement of 63.4% with respect to physician's evaluations at 36 months. The severe PTS multivariable model provided an optimistic adjusted c-index of 0.68 (95% CI 0.59-0.77). Approximately a quarter of DVT patients experienced PTS over 36 months after VTE diagnosis. Patient's self-assessment after 24 months provided added value for estimating incident PTS over 36 months. Multivariable risk analysis allowed good discrimination for severe PTS.

Superficial vein thrombosis and its relationship with malignancies: a prospective observational study.

BACKGROUND: The interrelation of cancer with venous thromboembolism is established, yet the specific impact on the incidence and progression of superficial vein thrombosis (SVT) remains unclear. OBJECTIVES: To investigate the association between SVT and malignancies, focusing on risk factors, presentation, course and complications. METHODS: A single-center prospective observational study of patients diagnosed with DVT or SVT referred to a venous thromboembolism clinic between January 2013 and April 2018. RESULTS: Of the 632 patients, 205 presented with SVT at referral, 16.6% having active cancer. Significant associations were found between active cancer and the risk of developing proximal SVT (RR 1.54 [1.18-2.03] p < 0.01), SVT within 3 cm from junction (RR 2.01 [1.13-3.72] p = 0.019), bilateral SVT (RR 8.38 [2.10-33.43] p < 0.01) and SVT affecting multiple veins (RR 2.42 [1.40-4.20] p < 0.01), with a higher risk of persistence (RR 1.51 [1.18-1.95] p < 0.01) and progression (RR 5.75 [2.23-14.79] p < 0.01) at initial assessment. Patients with SVT and no malignancy history demonstrated an elevated risk for new-onset cancer during follow-up (RR 1.43 [1.13-1.18] p = 0.022), especially in cases of proximal or bilateral SVT, initial progression or subsequent DVT or PE. No significant differences were observed in persistence, recurrence or complications during initial evaluation or follow-up across different pharmacological treatments. CONCLUSIONS: Research suggests a probable link between cancer history and the development of SVT. SVT presented more severely in cancer patients. SVT, especially in its more complex forms, could serve as a predictive marker for the future development of cancer. Treatment approaches varied, no significant differences in outcomes were noted.

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein thrombosis (DVT) based on patients' limb function, activities of daily living (ADL), clinical laboratory indicators, and DVT preventive measures. We retrospectively analyzed 620 stroke patients. Eight ML models-logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), neural network (NN), extreme gradient boosting (XGBoost), Bayesian (NB), and K-nearest neighbor (KNN)-were used to build the model. These models were extensively evaluated using ROC curves, AUC, PR curves, PRAUC, accuracy, sensitivity, specificity, and clinical decision curves (DCA). Shapley's additive explanation (SHAP) was used to determine feature importance. Finally, based on the optimal ML algorithm, different functional feature set models were compared with the Padua scale to select the best feature set model. Our results indicated that the RF algorithm demonstrated superior performance in various evaluation metrics, including AUC (0.74/0.73), PRAUC (0.58/0.58), accuracy (0.75/0.77), and sensitivity (0.78/0.80) in both the training set and test set. DCA analysis revealed that the RF model had the highest clinical net benefit. SHAP analysis showed that D-dimer had the most significant influence on DVT, followed by age, Brunnstrom stage (lower limb), prothrombin time (PT), and mobility ability. The RF algorithm can predict post-stroke DVT to guide clinical practice.

Haemostatic gene variations in cervical cancer-associated venous thrombosis: considerations for clinical strategies.

Venous thromboembolism (VTE) is a life-threatening haemostatic disease frequently diagnosed among the cancer population. The Khorana Score is currently the primal risk assessment model to stratify oncological patients according to their susceptibility to VTE, however, it displays a limited performance. Meanwhile, intensive research on VTE pathophysiology in the general population has uncovered a range of single-nucleotide polymorphisms (SNPs) associated with the condition. Nonetheless, their predictive ability concerning cancer-associated thrombosis (CAT) is controversial. Cervical cancer (CC) patients undergoing chemoradiotherapy often experience VTE, which negatively affects their survival. Thus, aiming for an improvement in thromboprophylaxis, new thrombotic biomarkers, including SNPs, are currently under investigation. In this study, the predictive capability of haemostatic gene SNPs on CC-related VTE and their prognostic value regardless of VTE were explored. Six SNPs in haemostatic genes were evaluated. A total of 401 CC patients undergoing chemoradiotherapy were enrolled in a retrospective cohort study. The implications for the time to VTE occurrence and overall survival (OS) were assessed. CAT considerably impacted the CC patients' OS (log-rank test, P < 0.001). SERPINE1 rs2070682 (T > C) showed a significant association with the risk of CC-related VTE (CC/CT vs. TT, log-rank test, P = 0.002; C allele, Cox model, hazard ratio (HR) = 6.99 and P = 0.009), while F2 rs1799963 (G > A) demonstrated an important prognostic value regardless of VTE (AA/AG vs. GG, log-rank test, P = 0.020; A allele, Cox model, HR = 2.76 and P = 0.026). For the remaining SNPs, no significant associations were detected. The polymorphisms SERPINE1 rs2070682 and F2 rs1799963 could be valuable tools in clinical decision-making, aiding in thromboprophylaxis and CC management, respectively.

Overall haemostatic potential assay for prediction of outcomes in venous and arterial thrombosis and thrombo-inflammatory diseases.

Thromboembolic diseases including arterial and venous thrombosis are common causes of morbidity and mortality globally. Thrombosis frequently recurs and can also complicate many inflammatory conditions through the process of 'thrombo-inflammation,' as evidenced during the COVID-19 pandemic. Current candidate biomarkers for thrombosis prediction, such as D-dimer, have poor predictive efficacy. This limits our capacity to tailor anticoagulation duration individually and may expose lower risk individuals to undue bleeding risk. Global coagulation assays, such as the Overall Haemostatic Potential (OHP) assay, that investigate fibrin generation and fibrinolysis, may provide a more accurate and functional assessment of hypercoagulability. We present a review of fibrin's critical role as a central modulator of thrombotic risk. The results of our studies demonstrating the OHP assay as a predictive biomarker in venous thromboembolism, chronic renal disease, diabetes mellitus, post-thrombotic syndrome, and COVID-19 are discussed. As a comprehensive and global measurement of fibrin generation and fibrinolytic capacity, the OHP assay may be a valuable addition to future multi-modal predictive tools in thrombosis.

Serum VEGF, P-Selectin, HDL-C, Platelet Index, and Coagulation Function Index in Deep Vein Thrombosis after Traumatic Fracture.

BACKGROUND: The goal was to investigate the relationship between serum vascular endothelial growth factor (VEGF), P-selectin, high-density lipoprotein cholesterol (HDL-C), platelet parameters, and coagulation function indexes and postoperative deep vein thrombosis (DVT) in patients with traumatic fracture. METHODS: A total of 150 patients with traumatic fractures after DVT were selected as the DVT group, and 150 patients with traumatic fractures without DVT during the same period were selected as the non-DVT group. Serum VEGF, P-selectin, HDL-C, platelet parameters including platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT), platelet large cell ratio (P-LCR), and plasma coagulation function indexes including thrombin time (TT), prothrombin time (PT), activated partial thrombin time (APTT), fibrinogen (FIB), and D-dimer (D-D) were measured. Pearson's correlation was performed to analyze the correlation between serum VEGF, P-selectin, and coagulation function indexes, and binary logistic regression was used to analyze the risk factors of DVT. RESULTS: Serum VEGF and P-selectin in the DVT group were higher while HDL-C was lower than those in the non-DVT group (p < 0.05). Serum VEGF and P-selectin were negatively correlated with plasma D-D and FIB (p < 0.05), and serum HDL-C was negatively correlated (p < 0.05). Compared with the non-DVT group, MPV, PDW, and P-LCR in the DVT group were decreased (p < 0.05). Multivariate logistic regression analysis showed that P-LCR was a risk factor for postoperative DVT in patients with traumatic fractures (p < 0.05). CONCLUSIONS: Serum VEGF and P-selectin are higher and HDL-C is lower in patients with DVT after postoperative traumatic fracture than in patients without DVT. Combined detection of serum VEGF, P-selectin, HDL-C, and coagulation function indexes may help to reduce the risk of DVT. Platelet parameters (MPV, PDW, P-LCR) have certain reference values for the clinical diagnosis and disease evaluation of DVT.

The Application Value of the D-Dimer Critical Value in Diagnosing Deep Vein Thrombosis in Patients with Bone Trauma.

BACKGROUND: D-dimer is used as a clinical indicator to predict venous thromboembolism, and some hospitals have included it in the critical value project. We aimed to evaluate whether the setting of a D-dimer critical value is helpful in the diagnosis of deep vein thrombosis in patients with bone trauma and to explore the rationality of setting a D-dimer critical value limit. METHODS: The clinical data of 4,897 bone trauma patients, hospitalized from April 1, 2022, to March 31, 2023, were retrospectively analyzed. Our hospital set the critical value limit for when the D-dimer value was greater than 15.0 mg/L, and Bayesian model was used to evaluate the relationship between deep vein thrombosis and the D-dimer limit. RESULTS: During this period, 199 times the D-dimer detection value was greater than 15.0 mg/L, and the critical value was reported and accounted for 4.06%. The predicted probability of lower limb venous thrombosis in patients who triggered the critical value of D-dimer was 40.21%, and the actual incidence was 34.67%. There were 376 patients with lower limb venous thrombosis during hospitalization, and 81.38% of the D-dimer value did not reach the critical value limit. CONCLUSIONS: The role of D-dimer as a critical value item in predicting DVT in patients with orthopedic trauma is small. Whether to list D-dimer as a critical value item can be comprehensively considered according to the own situation of medical institutions and the recommendations of clinicians. The same can be applied for the setting of critical value boundaries.