Development of a clinical prediction model for the postthrombotic syndrome in a prospective cohort of patients with proximal deep vein thrombosis

Construction of a Prediction Model for Post-thrombotic Syndrome after Deep Vein Thrombosis Incorporating Novel Inflammatory Response Parameter Scoring

OBJECTIVE

To investigate the independent predictive factors for post-thrombotic syndrome (PTS) and to construct a risk prediction model for PTS by incorporating a novel inflammatory response parameter (NPM score) scoring.

METHODS

A retrospective study analyzed patients diagnosed with lower extremity deep vein thrombosis (LEDVTs at the Affiliated Hospital of Chengde Medical College from January 2018 to January 2022. The Villalta scale was used to assess the occurrence of PTS 6-24 months after discharge. Patients were randomly divided into a training set and a validation set at a ratio of 7:3. In the training set, univariate analysis was performed on meaningful continuous variables, and those with differences were converted into dichotomous variables based on optimal cutoff values. Variable selection was performed using Log Lambda and Least Absolute Shrinkage and Selection Operator 10-fold cross-validation, followed by multivariable logistic regression analysis on selected variables for model construction. The model underwent internal validation in the validation set and external validation in an independent external cohort, including discriminative analysis, calibration analysis, and clinical decision curve analysis (DCA), with the model's rationale being evaluated lastly.

RESULTS

A total of 356 patients with lower extremity DVT were included, with 249 in the training set for model construction and 107 in the validation set for internal validation, along with 37 external patients for external validation. A composite score of inflammatory response parameters, including the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to high-density lipoprotein cholesterol ratio (MHR) (NLR-PLR-MHR score, NPM score), was developed, showing a significantly higher NPM score in the PTS group compared to the non-PTS group (P < 0.05). Predictive factors related to the risk of PTS occurrence included staging (OR = 6.83, 95% CI: 2.74-18.04), varicose veins (OR = 7.30, 95% CI: 2.29-25.75), homocysteine (Hcy) (OR = 1.12, 95% CI: 1.04-1.22), NPM score (OR = 3.13, 95% CI: 1.94-5.36), standardized anticoagulant therapy (OR = 5.77, 95% CI: 1.25-27.62), and one-stop treatment (OR = 0.04, 95% CI: 0.00-0.35) were incorporated into the Nomogram model. The model showed good discrimination with a concordance index of 0.918 (95% CI: 0.876-0.959) for model construction, 0.843 (95% CI: 0.741-0.945) for internal validation, and 0.823 (95% CI: 0.667-0.903) for external validation. In the Nomogram model, internal and external validation calibration curves showed good agreement between observed and predicted values. DCA indicated that the Nomogram model predicted PTS risk probability thresholds ranging from 3% to 98% for model construction, 5%-97% for internal validation, and 10%-80% for external validation, demonstrating better net benefit for predicting PTS risk in the model, internal, and external validation. Rationality analysis showed the model and internal validation had higher discrimination and clinical net benefit than other clinical indices.

CONCLUSIONS

The NPM score combined with stage, varicose veins, Hcy, standardized anticoagulant therapy, and one-stop treatment in the Nomogram model provides a practical tool for health care professionals to assess the risk of PTS in DVT patients, enabling early identification of high-risk patients for effective PTS prevention.

Scanning optoacoustic angiography for assessing structural and functional alterations in superficial vasculature of patients with post-thrombotic syndrome: A pilot study

This study highlights the potential of scanning optoacoustic angiography (OA) in identifying alterations of superficial vasculature in patients with post-thrombotic syndrome (PTS) of the foot, a venous stress disorder associated with significant morbidity developing from long-term effects of deep venous thrombosis. The traditional angiography methods available in the clinics are not capable of reliably assessing the state of peripheral veins that provide blood outflow from the skin, a key hallmark of personalized risks of PTS formation after venous thrombosis. Our findings indicate that OA can detect an increase in blood volume, diameter, and tortuosity of superficial blood vessels. The inability to spatially separate vascular plexuses of the dermis and subcutaneous adipose tissue serves as a crucial criterion for distinguishing PTS from normal vasculature. Furthermore, our study demonstrates the ability of scanning optoacoustic angiography to detect blood filling decrease in an elevated limb position versus increase in a lowered position.

Acute phase determinant of post-thrombotic syndrome: A review of the literature

BACKGROUND

Post-thrombotic syndrome (PTS) is the main long-term complication of deep vein thrombosis (DVT). Several therapies are being evaluated to prevent or to treat PTS. Identifying the patients most likely to benefit from these therapies presents a significant challenge.

OBJECTIVES

The objective of this review was to identify risk factors for PTS during the acute phase of DVT.

ELIGIBILITY CRITERIA

We searched the PubMed and Cochrane databases for studies published between January 2000 and January 2021, including randomized clinical trials, meta-analyses, systematic reviews and observational studies.

RESULTS

Risk factors for PTS such as proximal location of DVT, obesity, chronic venous disease, history of DVT are associated with higher risk of PTS. On the initial ultrasound-Doppler, a high thrombotic burden appears to be a predictor of PTS. Among the evaluated biomarkers, some inflammatory markers such as ICAM-1, MMP-1 and MMP-8 appear to be associated with a higher risk of developing PTS. Coagulation disorders are not associated with risk of developing PTS. Role of endothelial biomarkers in predicting PTS has been poorly explored. Lastly, vitamin K antagonist was associated with a higher risk of developing PTS when compared to direct oral anticoagulants and low molecular weight heparin.

CONCLUSIONS

Several risk factors during the acute phase of VTE are associated with an increased risk of developing PTS. There is a high-unmet medical need to identify potential biomarkers for early detection of patients at risk of developing PTS after VTE. Inflammatory and endothelial biomarkers should be explored in larger prospective studies to identify populations that could benefit from new therapies.

Prediction model of deep vein thrombosis risk after lower extremity orthopedic surgery

Purpose

This investigation was conceived to engineer and appraise a pioneering clinical nomogram, crafted to bridge the extant chasm in literature regarding the postoperative risk stratification for deep vein thrombosis (DVT) in the aftermath of lower extremity orthopedic procedures. This novel tool offers a sophisticated and discerning algorithm for risk prediction, heretofore unmet by existing methodologies.

Methods

In this retrospective observational study, clinical records of hospitalized patients who underwent lower extremity orthopedic surgery were collected at the Wuxi TCM Hospital Affiliated to the Nanjing University of Chinese Medicine between Jan 2017 and Oct 2019. The univariate and multivariate analysis with the backward stepwise method was applied to select features for the predictive nomogram. The performance of the nomogram was evaluated with respect to its discriminant capability, calibration ability, and clinical utility.

Result

A total of 5773 in-hospital patients were eligible for the study, with the incidence of deep vein thrombosis being approximately 1 % in this population. Among 31 variables included, 5 of them were identified to be the predictive features in the nomogram, including age, mean corpuscular hemoglobin concentration (MCHC), D-dimer, platelet distribution width (PDW), and thrombin time (TT). The area under the receiver operating characteristic (ROC) curve in the training and validation cohort was 85.9 % (95%CI: 79.96 %-90.04 %) and 85.7 % (95%CI: 78.96 %-90.69 %), respectively. Both the calibration curves and decision curve analysis demonstrated the overall satisfactory performance of the model.

Conclusion

Our groundbreaking nomogram is distinguished by its unparalleled accuracy in discriminative and calibrating functions, complemented by its tangible clinical applicability. This innovative instrument is set to empower clinicians with a robust framework for the accurate forecasting of postoperative DVT, thus facilitating the crafting of bespoke and prompt therapeutic strategies, aligning with the rigorous standards upheld by the most esteemed biomedical journals.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The background and role of catheter-directed thrombolysis evolving procedures for acute iliofemoral deep venous thrombosis

Minimal invasive treatment such as early endovenous thrombus removal for iliofemoral deep venous thrombosis (DVT) emerged in the end of last century. The principle is catheter-directed thrombolysis (CDT) using either plasminogen activating agents alone, as ultrasound-assisted CDT, or in combination with mechanical devices as pharmaco-mechanical CDT. The interest for this treatment modality is the high rate of post-thrombotic syndrome (PTS) with anticoagulation (AC) alone, especially after iliofemoral DVT. Recently published randomized controlled trials (RCTs) comparing early thrombus removal with AC alone, as well as non-randomized studies, have demonstrated favorable rates, or at least a decrease of moderate and severe PTS, in favor of these procedures. This article will summarize the background and evolution of the procedures in the last three decades and discuss fundamental criteria for inclusion and exclusion, focusing on the procedures regarding thrombus age and location, technical issues, complications and results including different outcome measures for PTS, for which iliac DVT involvement is a massive risk factor to be prevented.

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.

Three-Year Outcomes, Risk Factors for Restenosis After Stenting for DVT Combined with Iliac Vein Compression Syndrome

This study aimed to evaluate the safety and efficacy of pharmacomechanical catheter-directed thrombolysis (PCDT) and stenting for treating acute iliofemoral deep venous thrombosis (DVT) combined with iliac vein compression syndrome (IVCS), and to identify the predictors of stent restenosis. Patients with acute proximal DVT combined with IVCS underwent PCDT and stenting from January 2017 to December 2022 were enrolled. Primary and secondary patency were assessed by duplex ultrasound (DUS). The morbidity of postthrombotic syndrome (PTS) was assessed by the Villalta score. Risk factors for stent restenosis were assessed using univariate and multivariate Cox regression models. Total of 254 patients were included. The mean follow-up time was 36.06 ± 17.66 months. The primary patency rates at 1 year, 3 years, and 5 years were 92.5%±1.7%, 85.4%±2.4%, and 82.4%±2.9%, respectively. The incidence of stent restenosis was 14.2%. Discontinuation of anticoagulants within one year [hazard ratio (HR) = 5.03; P = .048] was the factor associated with acute in-stent thrombosis. Previous DVT history (HR =2.29; P = .037) and stent placement across the inguinal ligament (HR =6.70; P < .001) were identified as independent risk factors significantly associated with stent restenosis. The overall PTS rate was 19.3%. PCDT with stenting is safe and effective for patients with iliofemoral DVT secondary to IVCS, leading to low rates of PTS. Previous DVT history and stents placed across the inguinal ligament may be predictors of stent restenosis. Furthermore, stent restenosis typically occurs within one year and is mainly caused by acute thrombosis due to discontinuation of anticoagulants.

Current challenges in the prevention and management of post-thrombotic syndrome-towards improved prevention

Post-thrombotic syndrome (PTS) is a common and potentially debilitating complication of deep vein thrombosis (DVT), affecting up to 50% of DVT patients. The consequence of this chronic condition includes reduced quality of life, increased use of the healthcare system and decreased productivity. The societal impact of this condition is projected to increase, given our ageing population and increased burden of thrombotic diseases. Despite significant recent advances in our understanding of PTS, many unanswered questions remain. Currently, there are few effective and proven options for established PTS; hence, the emphasis should be on instituting effective prevention to reduce the progression to PTS. Effective anticoagulation lowers the risk of PTS, with direct oral anticoagulants appearing to outperform vitamin-K antagonists. However, the evidence for elastic compression stockings and endovascular thrombolysis or thrombectomy techniques remains unclear. Accurate identification of individuals at high risk of developing PTS may also improve the targeting of preventative interventions. This review will examine the current body of evidence regarding PTS, with a focus on preventative strategies as well as novel biomarkers.

A systematic review and meta-analysis of risk prediction models for post-thrombotic syndrome in patients with deep vein thrombosis

Objective

This systematic review and meta-analysis aimed to systematically evaluate the prediction models for the risk of post-thrombotic syndrome (PTS) in deep vein thrombosis (DVT) patients.

Methods

This systematic review and meta-analysis was guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). A systematic search on the following electronic database: PubMed/MEDLINE, EMBASE, and Cochrane Library, and Chinese databases such as WANFANG and CNKI was conducted to look for relevant articles based on the research question. The risk of bias for each studies included was carried out based on Prediction Model Risk of Bias Assessment Tool (PROBAST).

Results

We identified 10 studies that developed a total of 13 clinical prediction models for PTS risk in DVT patients, 3 models were externally validated, 2 models were temporally validated. The top 5 predictors were: BMI (N = 9), Varicose vein (N = 6), Baseline Villalta Score (N = 6), Iliofemoral thrombosis (N = 5), and Age (N = 4). The high risk of bias was from the analysis domain, which the number of participants and selection of predictors often did not meet the requirements of PROBAST. A random-effects meta-analysis of C-statistics was conducted, the pooled discrimination was C-statistic 0.75, 95%CI (0.69, 0.81).

Conclusion

Among the 13 PTS risk prediction models reported in this study, no prediction model has been applied to clinical practice due to the lack of external validation. In the development of prediction models, most models were not standardized in data analysis. It is recommended that future studies on the design and implementation of prediction models refer to Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) and PROBAST.

A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome

Objective

Post-thrombotic syndrome (PTS) is the most common long-term complication in patients with deep venous thrombosis, and the prevention of PTS remains a major challenge in clinical practice. Some studies have explored early predictors and constructed corresponding prediction models, whereas their specific application and predictive value are controversial. Therefore, we conducted this systematic evaluation and meta-analysis to investigate the incidence of PTS and the feasibility of early prediction.

Methods

We systematically searched databases of PubMed, Embase, Cochrane and Web of Science up to April 7, 2023. Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included articles, and the OR values of the predictors in multi-factor logistic regression were pooled to assess whether they could be used as effective independent predictors.

Results

We systematically included 20 articles involving 8,512 subjects, with a predominant onset of PTS between 6 and 72 months, with a 2-year incidence of 37.5% (95% CI: 27.8-47.7%). The results for the early predictors were as follows: old age OR = 1.840 (95% CI: 1.410-2.402), obesity or overweight OR = 1.721 (95% CI: 1.245-2.378), proximal deep vein thrombosis OR = 2.335 (95% CI: 1.855-2.938), history of venous thromboembolism OR = 3.593 (95% CI: 1.738-7.240), history of smoking OR = 2.051 (95% CI: 1.305-3.224), varicose veins OR = 2.405 (95% CI: 1.344-4.304), and baseline Villalta score OR = 1.095(95% CI: 1.056-1.135). Meanwhile, gender, unprovoked DVT and insufficient anticoagulation were not independent predictors. Seven studies constructed risk prediction models. In the training set, the c-index of the prediction models was 0.77 (95% CI: 0.74-0.80) with a sensitivity of 0.75 (95% CI: 0.68-0.81) and specificity of 0.69 (95% CI: 0.60-0.77). In the validation set, the c-index, sensitivity and specificity of the prediction models were 0.74(95% CI: 0.69-0.79), 0.71(95% CI: 0.64-0.78) and 0.72(95% CI: 0.67-0.76), respectively.

Conclusions

With a high incidence after venous thrombosis, PTS is a complication that cannot be ignored in patients with venous thrombosis. Risk prediction scoring based on early model construction is a feasible option, which helps to identify the patient's condition and develop an individualized prevention program to reduce the risk of PTS.

Performance and Head-to-Head Comparison of Three Clinical Models to Predict Occurrence of Postthrombotic Syndrome: A Validation Study

OBJECTIVE

 The SOX-PTS, Amin, and Méan models are three different clinical prediction scores stratifying the risk for postthrombotic syndrome (PTS) development in patients with acute deep vein thrombosis (DVT) of the lower limbs. Herein, we aimed to assess and compare these scores in the same cohort of patients.

METHODS

 We retrospectively applied the three scores in a cohort of 181 patients (196 limbs) who participated in the SAVER pilot trial for an acute DVT. Patients were stratified into PTS risk groups using positivity thresholds for high-risk patients as proposed in the derivation studies. All patients were assessed for PTS 6 months after index DVT using the Villalta scale. We calculated the predictive accuracy for PTS and area under receiver operating characteristic (AUROC) curve for each model.

RESULTS

 The Méan model was the most sensitive (sensitivity 87.7%; 95% confidence interval [CI]: 77.2-94.5) with the highest negative predictive value (87.5%; 95% CI: 76.8-94.4) for PTS. The SOX-PTS was the most specific score (specificity 97.5%; 95% CI: 92.7-99.5) with the highest positive predictive value (72.7%; 95% CI: 39.0-94.0). The SOX-PTS and Méan models performed well for PTS prediction (AUROC: 0.72; 95% CI: 0.65-0.80 and 0.74; 95% CI: 0.67-0.82), whereas the Amin model did not (AUROC: 0.58; 95% CI: 0.49-0.67).

CONCLUSION

 Our data support that the SOX-PTS and Méan models have good accuracy to stratify the risk for PTS.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Developing and optimizing a machine learning predictive model for post-thrombotic syndrome in a longitudinal cohort of patients with proximal deep venous thrombosis

BACKGROUND

Post-thrombotic syndrome (PTS) is the most common chronic complication of deep venous thrombosis (DVT). Risk measurement and stratification of PTS are crucial for patients with DVT. This study aimed to develop predictive models of PTS using machine learning for patients with proximal DVT.

METHODS

Herein, hospital inpatients from a DVT registry electronic health record database were randomly divided into a derivation and a validation set, and four predictive models were constructed using logistic regression, simple decision tree, eXtreme Gradient Boosting (XGBoost), and random forest (RF) algorithms. The presence of PTS was defined according to the Villalta scale. The areas under the receiver operating characteristic curves, decision-curve analysis, and calibration curves were applied to evaluate the performance of these models. The Shapley Additive exPlanations analysis was performed to explain the predictive models.

RESULTS

Among the 300 patients, 126 developed a PTS at 6 months after DVT. The RF model exhibited the best performance among the four models, with an area under the receiver operating characteristic curves of 0.891. The RF model demonstrated that Villalta score at admission, age, body mass index, and pain on calf compression were significant predictors for PTS, with accurate prediction at the individual level. The Shapley Additive exPlanations analysis suggested a nonlinear correlation between age and PTS, with two peak ages of onset at 50 and 70 years.

CONCLUSIONS

The current predictive model identified significant predictors and accurately predicted PTS for patients with proximal DVT. Moreover, the model demonstrated a nonlinear correlation between age and PTS, which might be valuable in risk measurement and stratification of PTS in patients with proximal DVT.

Overall Hemostatic Potential Assay Detects Risk of Progression to Post-Thrombotic Syndrome in Anticoagulated Patients following Deep Vein Thrombosis

Deep vein thrombosis (DVT) frequently leads to post-thrombotic syndrome (PTS) which is challenging to predict and prevent. Identifying those at high risk of developing PTS may help to focus preventative strategies. Adults were recruited within 3 months of DVT diagnosis. Blood was sampled during the therapeutic anticoagulation phase. Overall hemostatic potential (OHP) assay, a spectrophotometric assay, was performed on platelet-poor plasma (PPP). In this assay, fibrin formation is triggered by small amounts of thrombin and termed the overall coagulation potential (OCP). Simultaneously, thrombin and tissue plasminogen activator are added to PPP and the resulting fibrin aggregation curve is the overall hemostatic potential (OHP). Fibrinolysis is expressed by the parameter overall fibrinolytic potential (OFP%). Patients were followed up at regular intervals. PTS was diagnosed if the Villalta score was ≥5 at least 3 months after the DVT diagnosis. Results were obtained from 190 patients (53.7% male, mean age 56.9 years). PTS developed in 62 (32.6%) patients. Patients with PTS displayed significantly higher median OCP (45.8 vs. 38.8 units, p = 0.010), OHP (12.8 vs. 9.2 units, p = 0.005) and significantly lower OFP (74.1 vs. 75.6%, p = 0.050). PTS patients had higher neutrophil/lymphocyte ratios (NLR) (2.3 vs. 1.9, p = 0.007). After multivariate analysis, proximal DVT location, history of varicose veins, NLR ≥ 2.6, OHP > 13.0 units and weight >108 kg were independent predictors for PTS. The c-statistic of the multivariate model was 0.77. This pilot study suggests that OHP testing while patients are still anticoagulated may assist in the prediction of PTS development and could assist in prognostication and targeting of preventative measures. However, larger prospective studies are needed to confirm these findings.

Development and internal validation of a clinical prediction model for the diagnosis of immune thrombocytopenia

BACKGROUND

Immune thrombocytopenia (ITP) is a diagnosis of exclusion that can resemble other thrombocytopenic disorders.

OBJECTIVES

To develop a clinical prediction model (CPM) for the diagnosis of ITP to aid hematogists in investigating patients presenting with undifferentiated thrombocytopenia.

METHODS

We designed a CPM for ITP diagnosis at the time of the initial hematology consultation using penalized logistic regression based on data from patients with thrombocytopenia enrolled in the McMaster ITP registry (n = 523) called the Predict-ITP Tool. The case definition for ITP was a platelet count less than 100 × 109 /L and a platelet count response after high-dose corticosteroids or intravenous immune globulin, defined as the achievement of a platelet count above 50 × 109 /L and at least a doubling of baseline. Internal validation was done using bootstrap resampling. Model discrimination was assessed by the c-statistic, and calibration was assessed by the calibration slope, calibration-in-the-large, and calibration plot.

RESULTS

The final model included the following variables: (1) platelet count variability (based on three or more platelet count values), (2) lowest platelet count value, (3) maximum mean platelet volume, and (4) history of major bleeding (defined by the ITP bleeding scale). The optimism-corrected c-statistic was 0.83, the calibration slope was 0.88, and calibration-in-the-large for all performance measures was <0.001 with standard error <0.001, indicating good discrimination and excellent calibration.

CONCLUSIONS

The Predict-ITP Tool can estimate the likelihood of ITP for a given patient with thrombocytopenia at the time of the initial hematology consultation. The tool had high predictive accuracy for the diagnosis of ITP.

Machine learning-based prediction of the post-thrombotic syndrome: Model development and validation study

Background

Prevention is highly involved in reducing the incidence of post-thrombotic syndrome (PTS). We aimed to develop accurate models with machine learning (ML) algorithms to predict whether PTS would occur within 24 months.

Materials and methods

The clinical data used for model building were obtained from the Acute Venous Thrombosis: Thrombus Removal with Adjunctive Catheter-Directed Thrombolysis study and the external validation cohort was acquired from the Sun Yat-sen Memorial Hospital in China. The main outcome was defined as the occurrence of PTS events (Villalta score ≥5). Twenty-three clinical variables were included, and four ML algorithms were applied to build the models. For discrimination and calibration, F scores were used to evaluate the prediction ability of the models. The external validation cohort was divided into ten groups based on the risk estimate deciles to identify the hazard threshold.

Results

In total, 555 patients with deep vein thrombosis (DVT) were included to build models using ML algorithms, and the models were further validated in a Chinese cohort comprising 117 patients. When predicting PTS within 2 years after acute DVT, logistic regression based on gradient descent and L1 regularization got the highest area under the curve (AUC) of 0.83 (95% CI:0.76–0.89) in external validation. When considering model performance in both the derivation and external validation cohorts, the eXtreme gradient boosting and gradient boosting decision tree models had similar results and presented better stability and generalization. The external validation cohort was divided into low, intermediate, and high-risk groups with the prediction probability of 0.3 and 0.4 as critical points.

Conclusion

Machine learning models built for PTS had accurate prediction ability and stable generalization, which can further facilitate clinical decision-making, with potentially important implications for selecting patients who will benefit from endovascular surgery.

A Prediction Model Based on Blood Biomarker for Mortality Risk in Patients with Acute Venous Thromboembolism

Background

Most studies to date have focused on predicting the risk of venous thromboembolism (VTE), but prediction models about mortality risk in VTE are rarely reported. We sought to develop and validate a multivariable model to predict the all-cause mortality risk in patients with acute VTE in emergency settings.

Methods

A total of 700 patients were included from Qilu Hospital of Shandong University and were randomly assigned into training set (n=490) and validation set (n=210) in an 7:3 ratio. Multivariate logistics regression analysis was performed to identify independent variables and develop a prediction model, which was validated internally using bootstrap method. The discrimination, calibration and clinical utility were evaluated by receiver operating characteristic curve (ROC) analysis, Hosmer-Lemeshow (HL) test, Kaplan-meier (KM) analysis and decision curve analysis (DCA).

Results

There were 52 patients (10.6%) dying and 437 (89.4%) surviving in training set. Age (odds ratio [OR]: 4.158, 95% confidence interval [CI]: 2.426–7.127), pulmonary embolism (OR: 1.779, 95% CI: 1.124–2.814), platelet count (OR: 0.507, 95% CI: 0.310–0.830), D-dimer (OR: 1.826, 95% CI: 1.133–2.942) and platelet/lymphocyte ratio (OR: 2.166, 95% CI: 1.259–3.727) were independent risk variables associated with all-cause mortality. The model had good predictive capability with an AUC of 0.746 (95% CI: 0.668,0.825), a sensitivity of 0.769 (95% CI: 0.607,0.889), a specificity of 0.672 (95% CI: 0.634,0.707). The validation model had an AUC of 0.739 (95% CI: 0.685,0.793), a sensitivity of 0.690 (95% CI: 0.580,0.787), a specificity of 0.693 (95% CI: 0.655,0.729). The model is well calibrated and the HL test showed a good fit (χ²=5.291, p=0.726, Nagelkerke R²=0.137). KM analysis and DCA showed a good clinical utility of the nomogram.

Conclusion

This study identified independent variables affecting all-cause mortality in patients with acute VTE, and developed a prediction model and provided a nomogram with good prediction capability and clinical utility.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Prevention of the post thrombotic syndrome with anticoagulation: a narrative review

The post thrombotic syndrome (PTS) is chronic venous insufficiency secondary to a prior deep vein thrombosis (DVT). It is the most common complication of VTE and, while not fatal, it can lead to chronic, unremitting symptoms as well as societal and economic consequences. The cornerstone of PTS treatment lies in its prevention after DVT. Specific PTS preventative measures include the use of elastic compression stockings (ECS) and pharmacomechanical catheter directed thrombolysis (PCDT). However, the efficacy of these treatments has been questioned by large RCTs. So far, anticoagulation, primarily prescribed to prevent DVT extension and recurrence, appears to be the only unquestionably effective treatment for the prevention of PTS. In this literature review we present pathophysiological, biological, radiological and clinical data supporting the efficacy of anticoagulants to prevent PTS and the possible differential efficacy among available classes of anticoagulants (vitamin K antagonists (VKA), low molecular weight heparins (LMWHs) and direct oral anticoagulants (DOACs)). Data suggest that LMWHs and DOACs are superior to VKAs, but no head-to-head comparison is available between DOACs and LMWHs. Owing to their potentially greater anti-inflammatory properties, LMWHs could be superior to DOACs. This finding may be of interest particularly in patients with extensive DVT at high risk of moderate to severe PTS, but needs to be confirmed by a dedicated RCT.

Second consensus document on diagnosis and management of acute deep vein thrombosis: updated document elaborated by the ESC Working Group on aorta and peripheral vascular diseases and the ESC Working Group on pulmonary circulation and right ventricular function

This consensus document is proposed to clinicians to provide the whole spectrum of deep vein thrombosis management as an update to the 2017 consensus document. New data guiding clinicians in indicating extended anticoagulation, management of patients with cancer, and prevention and management of post-thrombotic syndrome are presented. More data on benefit and safety of non-vitamin K antagonists oral anticoagulants are highlighted, along with the arrival of new antidotes for severe bleeding management.

A predictive model for postthrombotic syndrome in proximal deep vein thrombosis patients

Background

Postthrombotic syndrome (PTS) is the most common long-term complication of deep vein thrombosis (DVT). Predictive models for PTS after hospitalized DVT patients, especially those with proximal DVT for whom preventative intervention decisions need to be made, are rare. We aimed to develop and externally validate a clinical predictive model for PTS in patients with proximal DVT.

Methods

This study was a retrospective, single-center, case-control study. The data used in our model were retrospectively collected from a prospective registry database in which 210 (derivation) and 90 (validation) consecutive patients were first diagnosed with proximal DVT. We developed a nomogram using the multivariate logistic regression model. External validation of our predictive model and previous predictive models in our validation set was assessed by discrimination, calibration, and clinical utility.

Results

Of the 30 candidate predictors, 5 were significantly associated with PTS in our final multivariable model, including the number of signs and symptoms (OR 1.33, 95% CI: 1.17 to 1.53, P<0.001), male sex (OR 1.79, 95% CI: 1.07 to 3.06, P=0.028), varicose vein history (OR 3.02, 95% CI: 1.04 to 7.60, P<0.001), BMI (OR 1.06, 95% CI: 1.00 to 1.12, P=0.052), and chronic DVT (OR 2.66, 95% CI: 1.49 to 4.79, P<0.001). The area under the curve was 0.724 in our predictive model, indicating suitable external performance.

Conclusions

A simple-to-use nomogram effectively predicts the risk of PTS in patients with proximal DVT. This predictive model may be considered for use in clinical care.

Post-thrombotic syndrome

Post-thrombotic syndrome (PTS) is a chronic venous insufficiency manifestation following an episode of deep-vein thrombosis (DVT). It is an important and frequent long-term adverse event of proximal DVT affecting 20-50% of patients. This position paper integrates data guiding clinicians in deciding PTS diagnosis, treatment and follow-up.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Can we predict and prevent the postthrombotic syndrome?

Postthrombotic syndrome (PTS) remains one of the major late complications of deep vein thrombosis (DVT) with a reported prevalence from 10 to 50%. Many factors were found to be related with the development and severity of PTS such as ipsilateral recurrent DVT, advanced age, obesity, ilio-femoral DVT and primary chronic venous disease presence. Some PTS prediction models have been proposed based on risk factor weight. However, it is still difficult to predict which patient with DVT will develop PTS and thus, the clinical application of these models remains limited. Among the identified problems the heterogeneity of the DVT patient population together with the variety of PTS clinical presentations and difficulties concerning PTS severity assessment should be mentioned. Difficulties on the implementation of the specific and objective PTS identification method have also the significant influence on the research focusing on PTS prevention modalities including risk factor modification, compression treatment, anticoagulation and invasive DVT treatment. In this review, the current approach and knowledge on PTS prediction and prevention are presented, including the conservative and invasive DVT treatment possibilities.

Predictors of long-term post-thrombotic syndrome following high proximal deep vein thrombosis: a cross-sectional study

Background

Post-thrombotic syndrome (PTS) is a frequent chronic complication of proximal deep vein thrombosis (DVT) of the lower limb, but predictors of PTS are not well established. We aimed to examine predictors of PTS in patients with long-term PTS following proximal DVT.

Methods

During 2006–09, 209 patients with a first time acute upper femoral or iliofemoral DVT were randomized to receive either additional catheter-directed thrombolysis or conventional therapy alone. In 2017, the 170 still-living participants were invited to participate in a cross-sectional follow-up study. In the absence of a gold standard diagnostic test, PTS was defined in line with clinical practice by four mandatory, predefined clinical criteria: 1. An objectively verified DVT; 2. Chronic complaints (> 1 month) in the DVT leg; 3. Complaints appeared after the DVT; and 4. An alternative diagnosis was unlikely. Possible predictors of PTS were identified with multivariate logistic regression.

Results

Eighty-eight patients (52%) were included 8–10 years following the index DVT, and 44 patients (50%) were diagnosed with PTS by the predefined clinical criteria. Younger age and higher baseline Villalta score were found to be independent predictors of PTS, i.e., OR 0.96 (95% CI, 0.93–0.99), and 1.23 (95% CI, 1.02–1.49), respectively. Lack of iliofemoral patency at six months follow-up was significant in the bivariate analysis, but did not prove to be significant after the multivariate adjustments.

Conclusions

In long-term follow up after high proximal DVT, younger age and higher Villalta score at DVT diagnosis were independent predictors of PTS.

Incidence and severity of postthrombotic syndrome after iliofemoral thrombosis – results of the Iliaca-PTS – Registry

Summary: Background: Deep venous thrombosis (DVT) and in particular, iliofemoral thrombosis (IFT) can lead to recurrent thrombosis and postthrombotic syndrome (PTS). Data on the prevalence, predictors and outcome of IFT are scarce. Patients and methods: We retrospectively searched our database of outpatients who had presented with DVT and IFT including the iliac veins from 2014 until 2017. In addition, we performed a prospective registry in a subgroup of patients with IFT. These patients received duplex ultrasound, magnetic resonance venography and measurement of symptom-free walking distance using a standardized treadmill ergometry. The severity of PTS was analyzed using the Villalta-Scale (VS) and quality of life was assessed using the VEINES-QOL/Sym Questionnaire. Results: 847 patients were retrospectively identified with DVT and 19.7% (167/847) of these presented with IFT. 50.9% (85/167) of the IFT-patients agreed to participate in the prospective registry. The majority of these patients (76.5%: 65/85) presented with left-sided IFT. In 53.8% (35/65) May-Thurner syndrome was suspected. 27.1% (23/85) underwent invasive therapy. Moderate or severe PTS (VS ≥ 10) occurred in 10.6% (9/85). The severity of PTS is correlated with a reduced quality of life (ρ (CI 95%) = −0.63 (−0.76; −0.46); p < 0.01). None of the patients presented with a venous ulcer at any time. A high body mass index was a significant predictor (OR (CI 95%) = 1.18 (1.05; 1.33), p = 0.007) for the development of clinically relevant PTS (VS ≥ 10) and venous claudication. Conclusions: Every fifth patient with DVT presented with an IFT. The majority developed left sided IFT. Every 10th patient developed moderate or severe PTS (VS ≥ 10). A high body mass index was predictive for the development of PTS and venous claudication.

Post-thrombotic Syndrome: Preventative and Risk Reduction Strategies Following Deep Vein Thrombosis

Venous disease is common in the general population, with chronic venous disorders affecting 50–85% of the western population and consuming 2–3% of healthcare funding. It, therefore, represents a significant socioeconomic, physical and psychological burden. Acute deep vein thrombosis, although a well-recognised cause of death through pulmonary embolism, can more commonly lead to post-thrombotic syndrome (PTS). This article summarises the pathophysiology and risk factor profile of PTS, and highlights various strategies that may reduce the risk of PTS, and the endovenous management of iliofemoral deep vein thrombosis. The authors summarise the advances in PTS risk reduction strategies and present the latest evidence for discussion.

Thrombolytic therapy in acute venous thromboembolism

Although anticoagulation remains the mainstay of treatment of acute venous thromboembolism (VTE), the use of thrombolytic agents or thrombectomy is required to immediately restore blood flow to thrombosed vessels. Nevertheless, systemic thrombolysis has not clearly been shown to improve outcomes in patients with large clot burdens in the lung or legs as compared with anticoagulation alone; this is in part due to the occurrence of intracranial hemorrhage in a small percentage of patients to whom therapeutic doses of a thrombolytic drug are administered. Algorithms have been developed to identify patients at high risk for poor outcomes resulting from large clot burdens and at low risk for major bleeding in an effort to improve outcomes in those receiving thrombolytic therapy. In acute pulmonary embolism (PE), hemodynamic instability is the key determinant of short-term survival and should prompt consideration of immediate thrombolysis. In hemodynamically stable PE, systemic thrombolysis is not recommended and should be used as rescue therapy if clinical deterioration occurs. Evidence is accumulating regarding the efficacy of administering reduced doses of thrombolytic agents systemically or via catheters directly into thrombi in an effort to lower bleed rates. In acute deep venous thrombosis, catheter-directed thrombolysis with thrombectomy can be used in severe or limb-threatening thrombosis but has not been shown to prevent postthrombotic syndrome. Because the management of acute VTE can be complex, having a rapid-response team (ie, PE response team) composed of physicians from different specialties may aid in the management of severely affected patients.

External validation of the SOX-PTS score in a prospective multicenter trial of patients with proximal deep vein thrombosis

BACKGROUND

Using data from the SOX Trial, we recently developed a clinical prediction model for occurrence of the postthrombotic syndrome (PTS) after proximal deep vein thrombosis (DVT), termed the SOX-PTS score. The score includes anatomical extent of DVT; body mass index; and baseline Villalta score.

OBJECTIVE

To externally validate the SOX-PTS score.

METHODS

Logistic regression analysis of data from the ATTRACT Trial that evaluated pharmacomechanical catheter directed thrombolysis in patients with proximal DVT. The primary outcome was the occurrence of PTS (defined as Villalta score ≥ 5) from 6 to 24 months after DVT. Secondary outcomes included moderate-severe PTS (Villalta scale ≥ 10) and severe PTS (Villalta scale ≥ 14). Predictive performance was assessed by discrimination and calibration. An updated score was evaluated in an exploratory analysis.

RESULTS

Six hundred and ninety-one ATTRACT patients were included, of whom 328 (47%) developed PTS. The c-statistic was 0.63; 95% confidence interval (CI) 0.59-0.67 for PTS. The model's performance appeared to be better for the outcomes moderate to severe PTS and severe PTS (c-statistic 0.67; 95% CI 0.62-0.72 for moderate-severe PTS and 0.70; 0.64-0.77 for severe PTS). An updated model with age as an additional variable performed similarly to the original model.

CONCLUSION

We externally validated the SOX-PTS score for estimating the risk of developing PTS, moderate to severe PTS, and severe PTS, in patients with proximal DVT. The score may be useful to predict PTS at the time of DVT diagnosis. Further external validation in different patient cohorts is required.

Prevention and Management of the Post-Thrombotic Syndrome

The post-thrombotic syndrome (PTS) is a form of chronic venous insufficiency secondary to prior deep vein thrombosis (DVT). It affects up to 50% of patients after proximal DVT. There is no effective treatment of established PTS and its management lies in its prevention after DVT. Optimal anticoagulation is key for PTS prevention. Among anticoagulants, low-molecular-weight heparins have anti-inflammatory properties, and have a particularly attractive profile. Elastic compression stockings (ECS) may be helpful for treating acute DVT symptoms but their benefits for PTS prevention are debated. Catheter-directed techniques reduce acute DVT symptoms and might reduce the risk of moderate-severe PTS in the long term in patients with ilio-femoral DVT at low risk of bleeding. Statins may decrease the risk of PTS, but current evidence is lacking. Treatment of PTS is based on the use of ECS and lifestyle measures such as leg elevation, weight loss and exercise. Venoactive medications may be helpful and research is ongoing. Interventional techniques to treat PTS should be reserved for highly selected patients with chronic iliac obstruction or greater saphenous vein reflux, but have not yet been assessed by robust clinical trials.

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Reciprocal enhancement of thrombosis by endothelial-to-mesenchymal transition induced by iliac vein compression

AIMS

Endothelial-to-mesenchymal transition (EndMT) is a pathophysiological change of vascular endothelium commonly seen in the cardiovascular system. Iliac vein compression syndrome (IVCS) is known to be often associated with intimal hyperplasia and thrombosis. However, whether EndMT exists in IVCS has not yet been reported. The purpose of this study was to investigate the relationship between EndMT and thrombosis in IVCS.

MAIN METHODS

Using IVCS models in pig and mouse, we detected intimal changes and thrombus in stenotic iliac vein by immunofluorescence staining. Primary human umbilical vein endothelial cells (HUVEC) were stimulated by transforming growth factor β1 (TGF-β1) and thrombin, and cell phenotypic transition and antithrombotic function of HUVEC were examined through q-PCR, western blot and ELISA. In the end, by immunofluorescence staining, we observed the effect of anticoagulant on interstitial changes of venous endothelial cells in IVCS models.

KEY FINDINGS

We showed that iliac vein compression induced EndMT, of which its inhibition reduced thrombus formation. Further studies showed that HUVECs undergoing EndMT lost their anticoagulation and thrombolytic function. Interestingly, thrombin aggravated EndMT through TGF-β/Smad3 signaling. Moreover, compared with wild type (WT) mice, EndMT in stenotic iliac vein was reduced in WT mice fed with rivaroxaban or factor VII knockout mice, implying that anticoagulation alleviated EndMT in IVCS models.

SIGNIFICANCE

Our findings indicate that EndMT and thrombosis reinforce reciprocally in IVCS, implying that targeting EndMT could be a potential strategy in prevention and treatment of thrombosis in IVCS.

Measuring functional limitations after venous thromboembolism: A call to action

The main objectives of therapeutic trials in venous thromboembolism (VTE) are to prevent recurrent VTE, major bleeding and death. While these outcomes are indeed highly relevant, they are also rare and do not fully capture the overall functional outcome of VTE patients. Importantly, functional limitations after VTE are prevalent after both deep vein thrombosis and pulmonary embolism occurring in up to 50% of patients. These post-VTE syndromes are associated with a decreased quality of life, higher risk of depressive disorders, unemployment and increased utilization of healthcare resources. Because of the major impact of functional limitations on individual patients and society as a whole, development of tools able to capture functional outcomes in clinical trials are urgently needed. We anticipate that a standardized post-VTE functional status scale will aid in demarcating effective and ineffective VTE therapies on functional outcomes in trials with appropriately powered sample sizes, as well as pave the road for value-based healthcare. The scale that we have in mind covers the entire spectrum of functional outcomes ranging from no symptoms to death. Moreover, it focuses on both limitations in usual activity as well as changes in lifestyle. The scale is not meant to replace current diagnostic or prognostic scores for post-VTE syndromes, but to be used as an outcome measure to evaluate the overall consequences of VTE on functional status. This review is a call for action to the VTE community to join forces and support further development of the proposed scale, a process of which we summarize the necessary steps.

How I treat the postthrombotic syndrome

The postthrombotic syndrome (PTS) is a chronic complication of deep vein thrombosis (DVT) that imposes significant morbidity, reduces quality of life, and is costly. After DVT, 20% to 50% of patients will develop PTS, and up to 5% will develop severe PTS. The principal risk factors for PTS are anatomically extensive DVT, recurrent ipsilateral DVT, obesity, and older age. By preventing the initial DVT and DVT recurrence, primary and secondary prophylaxis of DVT will reduce occurrence of PTS. The effectiveness of elastic compression stockings (ECSs) for PTS prevention is controversial. Catheter-directed thrombolysis is not effective to prevent PTS overall but may prevent more severe forms of PTS and should be reserved for select patients with extensive thrombosis, recent symptoms onset, and low bleeding risk. For patients with established PTS, the cornerstone of management is ECS, exercise, and lifestyle modifications. Surgical or endovascular interventions may be considered in refractory cases. Because of a lack of effective therapies, new approaches to preventing and treating PTS are needed. This article uses a case-based approach to discuss risk factors for PTS after DVT, how to diagnose PTS, and available means to prevent and treat PTS, with a focus on new information in the field.

Prevention and treatment of the post-thrombotic syndrome

Post thrombotic syndrome (PTS) is a common chronic complication of deep vein thrombosis of the leg (DVT). Treatment options are limited therefore emphasis is placed on its prevention. Several risk factors have been recognized, but were so far not used for risk stratification or translation into prediction models. Early interventions did not yet result in more successful preventive treatment strategies; for the acute phase of DVT there is equipoise on the value of elastic compression, as well as on catheter directed thrombolysis. There are no drugs specifically targeted at PTS prevention. The use of anticoagulant medication such as direct oral anticoagulants (DOACs) might decrease PTS incidence, but this needs to be corroborated. Both research into more effective treatment options as well as future PTS management may benefit from a uniform diagnostic strategy and the use of prediction rules to better allocate treatment and thereby increase treatment efficacy.