Next Article in Journal
Recent Advancements in Hematology: Knowledge, Methods and Dissemination, Part 2
Previous Article in Journal
Impaired Hematopoiesis after Allogeneic Hematopoietic Stem Cell Transplantation: Its Pathogenesis and Potential Treatments

Individualised Risk Assessments for Recurrent Venous Thromboembolism: New Frontiers in the Era of Direct Oral Anticoagulants

by 1,2,3,*, 1,2,3 and 1,2,3
Northern Health, Epping, VIC 3076, Australia
Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC 3052, Australia
Australian Centre for Blood Disease, Monash University, Clayton, VIC 3004, Australia
Author to whom correspondence should be addressed.
Academic Editor: Leigh A. Madden
Received: 30 November 2020 / Revised: 6 January 2021 / Accepted: 12 January 2021 / Published: 15 January 2021
(This article belongs to the Special Issue Cancer Associated Coagulation)


Venous thromboembolism (VTE) is a leading cause of morbidity and mortality and is associated with high recurrence rates. The introduction of direct oral anticoagulants (DOACs) in the 2010s has changed the landscape of VTE management. DOACs have become the preferred anticoagulant therapy for their ease of use, predictable pharmacokinetics, and improved safety profile. Increasingly, guidelines have recommended long term anticoagulation for some indications such as following first unprovoked major VTE, although an objective individualised risk assessment for VTE recurrence remains elusive. The balance of preventing VTE recurrence needs to be weighed against the not insignificant bleeding risk, which is cumulative with prolonged use. Hence, there is a need for an individualised, targeted approach for assessing the risk of VTE recurrence, especially in those patients in whom the balance between benefit and risk of long-term anticoagulation is not clear. Clinical factors alone do not provide the level of discrimination required on an individual level. Laboratory data from global coagulation assays and biomarkers may provide enhanced risk assessment ability and are an active area of research. A review of the prediction models and biomarkers for assessing VTE recurrence risk is provided, with an emphasis on contemporary developments in the era of DOACs and global coagulation assays.
Keywords: venous thromboembolism; recurrent venous thromboembolism; clinical prediction models; global coagulation assays venous thromboembolism; recurrent venous thromboembolism; clinical prediction models; global coagulation assays

1. Introduction

Venous thromboembolism (VTE) is defined as thrombosis of the venous system and includes deep vein thrombosis (DVT) and pulmonary embolism (PE). The incidence of VTE is approximately 1 to 1.8 per 1000 person-years, similar to incidence rates for stroke, and rises exponentially with increasing age [1,2]. Worldwide, VTE is the leading cause of hospital-related disability-adjusted life years (DALYs) lost [3], and was estimated to cost AUD 117,000 per patient in 2008 [4].
One of the major challenges in managing VTE remains estimating the risk of VTE recurrence after withdrawal of anticoagulation. Identification of these at-risk individuals has historically relied on the presence of persistent or transient risk factors (see Table 1). Persistent risk factors are intrinsic to the individual and include known inherited and non-inherited thrombophilia [5], male gender [6], obesity [7], and the presence of malignancy [8]. Transient risk factors may include surgery, injuries, and long-distance flights, which temporarily increase the risk of VTE [9]. For those without an identifiable provoking factor, the estimated risk of recurrence approaches 30% at five years, and the risk is highest during the first year after anticoagulation cessation at around 10% [9,10]. On the other hand, the presence of strong transient risk factors such as surgery or physical injury is associated with the lowest risk of recurrence [9,11]. The long-term recurrence risk is intermediate following events provoked by minor transient risk factors including long-haul flights, hormonal therapy, and non-surgical transient immobility [11,12].
Evaluating the individual risk of VTE recurrence is important when deciding if long-term anticoagulation is justified and needs to be carefully balanced against the risk of major bleeding. Whilst long-term anticoagulation is clearly recommended for patients with recurrent unprovoked VTE, the optimal duration for patients with VTE not meeting this criterion is less clear. For example, the need for anticoagulation after the first episode of unprovoked major VTE is unclear, although a number of clinical trials have shown benefits in continuing anticoagulation with the risk of VTE reduced by 80% [19,20,21]. However, given that 70% of patients with their first episode of VTE do not have a recurrence during the first five years, it would mean that these patients have potentially received unnecessary anticoagulation treatment. Hence, most guidelines agree that in this situation of “clinical equipoise”, a personalised approach balancing the benefits of reduced VTE recurrence against the risks of major bleeding is required [22,23,24].
The introduction of direct oral anticoagulants (DOACs) has seen sizable shifts in the anticoagulation prescribing practices around the world [25,26,27,28]. Many VTE guidelines now suggest DOACs as the preferred anticoagulation therapy [22,23] due to their non-inferior efficacy compared with vitamin K antagonists (VKAs), improved safety, and ease of administration. Major bleeding events associated with DOACs have consistently been shown to be fewer compared to VKAs. A meta-analysis of randomised controlled trials involving DOACs for extended anticoagulation following VTE found an incidence of major bleeding of 0.48 per 100 patient years compared to 2.89 per 100 patient years for VKAs [21]. Real-life registry data in atrial fibrillation patients have also confirmed reduced bleeding on DOACs compared to VKAs [29,30]. There is also evidence that major bleeding associated with DOACs leads to reduced case-fatality rate (7.57% DOACs vs 11.04% VKAs) [31]. For all these reasons, DOACs have risen in popularity and VKA use has fallen as a consequence.
Surveys of prescribing activity since the introduction of DOACs have revealed an increase in total anticoagulation use [26,27]. This can partly be explained by the fact that ease of DOAC administration and relative long-term safety compared to VKAs have provided an attractive option for long-term anticoagulation in non-valvular atrial fibrillation as well as secondary VTE thromboprophylaxis [32]. Real-world data of major bleeding on long-term DOAC therapy following VTE are scarce. In the non-interventional XALIA [33] study, in which patients treated with rivaroxaban after DVT were followed for a median 239 days, the annualised major bleeding rate was 1.2%. In the Dresden NOAC registry [34], 575 VTE patients on rivaroxaban for a median of 274 days had a major bleeding rate of 4.1 per 100 patient-years. The age of this cohort was markedly higher than in XALIA (68 vs 59 years) and EINSTEIN [35] (68 vs. 57 years), which could explain the increased bleeding observed. More data are required in the long-term VTE setting, especially in those taking reduced dose DOACs. However, the cumulative clinically significant bleeding risk is not insignificant in VTE patients receiving long-term DOAC therapy, especially in older individuals who are at greater risk of both developing VTE and major bleeding. Adequately defining individuals at low risk for VTE recurrence should be a priority to minimise unnecessary over-medication as well as to reduce major bleeding complications.
An individualised, targeted approach for assessing VTE recurrence risk would be ideal, especially in those patients in whom the balance between benefit and risk is not clear. Clinical factors alone do not provide the level of discrimination required on an individual level, and single biomarkers alone may not be strong enough in their discriminatory power. Increasing evidence has suggested that global coagulation assays may better reflect the overall prothrombotic phenotype of an individual and could be a promising additional tool in the quest for truly individualised risk assessments for recurrent VTE [36]. This review aims to provide an overview of the current clinical risk prediction models and biomarkers for assessing VTE recurrence risk, with an emphasis on recent developments in the era of DOACs and future potential biomarkers, e.g., global coagulation assays.

2. Risk Factors and Clinical Risk Prediction Models

Risk factors for VTE recurrence have been well documented, and their estimated magnitudes are displayed in Table 1. It should be noted, however, that several risk factors may co-exist in the same individual, and that the combined effect of multiple risk factors together have not been clearly defined. In addition, factors such as age, malignancy and co-morbidities such as renal failure are concurrent risks for thrombosis and bleeding, making the risk–benefit assessment of long-term anticoagulation challenging. Existing models for predicting bleeding risk such as the HAS-BLED or RIETE score do not account for this complexity, and in addition, have been formulated in the warfarin era prior to the introduction of DOACs. The HAS-BLED [37] score for instance allocates one point for labile INRs, which would be of no relevance to patients receiving DOACs.
Clinical prediction models have been developed to aid in the identification of low-risk individuals in whom anticoagulation can be ceased. For the purposes of this review, we will be concentrating on the HERDOO2, DASH and Vienna prediction models, which are widely known, validated, and combine clinical parameters with laboratory biomarkers. Details of these models are displayed in Table 2. These models have been validated in separate studies and are elaborated below. In both the derivation and validation studies, patients were anticoagulated with VKAs except in the HERDOO2 validation study [38], which included a small number of patients treated with rivaroxaban.
The HERDOO2 rule has been prospectively validated in a study of 2785 patients, following a first unprovoked or minimally provoked VTE and followed up for a mean 11.6 months [38]. In this study, the HERDOO2 rule was able to distinguish females at low risk of recurrence (3% per patient year, 95% CI 1.8–4.8%) while high risk females had a similar recurrence risk to men (8.1% per patient year 95% CI 5.2–11.9%). Hence, the HERDOO2 may be useful in defining a low-risk group in women but is not subtle enough to identify a similar low risk group in men.
The DASH model was validated in a retrospective study of 827 patients [43] after the first episode of unprovoked major VTE (hormonally related events were included), with a median follow-up of 25.2 months. Those with DASH score of 1 or below had an annualised recurrence rate of 3.5% (95% CI 2.5–4.7%) and could represent a lower risk population where long-term anticoagulation can be ceased. However, the model was found to be less useful in elderly patients, where the recurrence rate in patients aged >65 years was found to be >5% regardless of their DASH score, which in part may be due to the increasing D-dimer with age.
The Vienna Prediction Model (VPM) is the only model to have been prospectively validated in a randomised controlled trial. Geersing et al. [44] used the VPM to guide treatment for 883 patients with unprovoked VTE. During 24 months of follow-up, there were no differences in the rates of recurrent major VTE between the two arms (10.4% in the intervention (model-assisted treatment recommendation) group; 11.3% in the control (at clinician discretion) group; p = 0.67). This was despite the model showing good discriminatory performance and being able to identify 47% of subjects as belonging to the low-risk group. The lack of difference seen between the intervention and control arms could have been explained by the fact that a significant number of patients in the study did not comply with the treatment recommendations of the VPM, and distal DVTs were not included in the definition of recurrent events. Nonetheless, given the good discriminatory performance, the use of a standardised model such as VPM may help to facilitate and standardise clinical judgment. Similarly, Tristchler et al. [45] prospectively applied the updated VPM to 156 elderly patients (>65 years old) after acute unprovoked VTE (subjects with prior VTE history were not excluded). In this cohort, the updated VPM was not able to discriminate VTE recurrence risk between low and high-risk patients (13% vs. 10%; p = 0.77 at 12 months). Compared to the updated VPM derivation study, however, the average age was significantly higher (74 vs. 53 years) and the participants had higher D-dimer levels (1022 vs. 356 ng/mL).
It is clear that although each of the discussed clinical prediction models show promise and merit, and in most cases can identify a low-risk population, they each have significant deficiencies, limiting applicability in clinical practice and consequently have not led to recommendations in guidelines [22]. Some of these limiting factors include differing definitions of unprovoked VTE as well as the use of D-dimers as biomarkers, which is confounded by increasing age, and contributes to the poor performance of these risk models in older populations [38,43,45,46]. However, defining a low VTE-recurrence risk group in elderly patients is clinically important, because they concurrently have a high risk of bleeding and clotting. Similarly, some models are not subtle enough to determine a low-risk group in men, which would subject a significant number of VTE patients to indefinite anticoagulation. Finally, all the model derivation and validation studies have been conducted prior to the widespread use of DOACs, and therefore direct application in the current era where anticoagulation use is convenient and potentially safer, is not fully understood. Nevertheless, these models were the first to combine clinical and laboratory markers, and remain the basis of how we can further individualise VTE treatment in the future.

3. Biomarkers

Clinical factors alone do not account for the entirety of VTE recurrence risk, and certain biological factors detectable as biomarkers may also contribute. In this section, some well-studied biomarkers associated with increased VTE recurrence risk are discussed.

3.1. D-Dimer

Perhaps the most well-studied biomarker is the D-dimer, which is a by-product of the lysis of cross-linked fibrin [47], and high levels following the withdrawal of anticoagulation after unprovoked major VTE have been repeatedly associated with increased risk of recurrent VTE [48,49,50,51]. A meta-analysis of 1818 patients [17] following unprovoked major VTE found the hazard ratio for recurrent VTE in those with abnormal D-dimers vs normal D-dimers to be 2.59 (95%CI 1.9–3.52). The evidence for D-dimer testing, however, in other VTE cohorts such as provoked VTE and distal DVT are conflicting and sparse [51,52]. In an analysis of 1655 VTE patients [53] from the RIETE registry, abnormal D-dimers after anticoagulation cessation was associated with a significantly increased risk for VTE recurrence (hazard ratio (HR) 1.74, 95% CI 1.51–3.63) in those with minimally provoked VTE but not surgically provoked VTE. In our centre, we performed a retrospective analysis of 173 VTE patients [54] and found that in those with IDDVT, an abnormal post-anticoagulation cessation D-dimer was significantly associated with an increased risk of recurrent VTE (HR 10.48, p = 0.003). Of the recurrent events, 30% were major VTE, suggesting that VTE recurrence following isolated distal DVTs may not be entirely low risk events. Travel-provoked VTE was also found to be associated with abnormal D-dimers in our cohort.
Although D-dimer tests can potentially identify higher risk populations, its applicability into clinical practice is not without challenges. One of the issues is that D-dimers are non-specific and increase naturally with age, during pregnancy, and can be attributed to malignancy or inflammation [47]. Similarly, post-anticoagulation cessation D-dimers may lack discriminatory ability in males [55], although this finding has been demonstrated in only one study so far. Age-adjustment of the D-dimer in the diagnostic setting has been a proven strategy to minimise false positives in elderly patients suspected for DVT and PE [56,57], however, a similar strategy has not been well studied to risk stratify for VTE recurrence. In the DULCIS study [49], altered D-dimer cut-off values according to patient age (single threshold of 70 years), gender, and type of D-dimer assay were adopted instead of the manufacturer’s recommended threshold values. The resulting performance, however, was not improved in those patients aged over 70 years old with negative D-dimers, in whom 8.9% developed recurrent major VTE compared with 2.1% in those younger than 70 years old, during two years of follow-up. The authors of the study concluded that more research is required before age-adjustment of the D-dimer can be employed in the post-anticoagulant, VTE recurrence risk assessment setting.
A lack of standardisation of D-dimer methods may affect the interpretation of results and affect predictive model performance in the clinical setting. Various different D-dimer assays have been used across studies including quantitative latex immunoturbidimetric, enzyme-linked immunofluorescence assay (ELFA), chemiluminescent enzyme immunometric assays, and various point-of-care (POC) tests. These differences may partly explain conflicting results and differing abnormal D-dimer thresholds across populations [52,55]. Quantitative tests using ELFAs and latex immunoturbidimetric technology have been shown to have higher negative predictive value with higher sensitivity (>95%) and lower specificity (50%) compared to POC tests (83% sensitivity and 71% specificity for DVT) [58]. An understanding of the performance qualities of local D-dimer assays in use would be crucial before adopting it into clinical practice.
Legnani et al. [59] found rates of abnormal D-dimers to be significantly higher after cessation of DOAC therapy compared to matched subjects who had received VKAs (18.8% vs. 11.8%, p = 0.02). This finding has not yet been replicated in other studies, and it remains to be seen if there may be any effect on the utility of D-dimers as a predictor of recurrent VTE.

3.2. Factor VIII

There is some evidence that high levels of factor VIII are associated with VTE recurrence following a first unprovoked event [60,61], although this association has not been consistently reported [5,62]. Persistently elevated factor VIII over time has been found to be a feature following VTE and can be independent of an acute phase reaction [60,61]. In a study of 2242 patients [63], following a first VTE (provoked and unprovoked), incorporating the factor VIII (measured three months post-anticoagulation cessation) into the DASH predictive model led to improvement of the model performance, including in patients assumed to have low risk of recurrence. Differing methods for quantifying factor VIII may also limit direct comparisons between studies and cohorts. The optimal timing of factor VIII measurement, however, requires further studies.

3.3. P-Selectin

P-selectin is a cell-adhesion molecule normally found in the alpha granules of platelets and expressed on the surface of activated endothelial cells [64]. P-selectin mediates the adhesion of leukocytes and platelets and has been found in mouse models to be important in the process of venous thrombosis formation [65]. Soluble P-selectin (sP-selectin) has been detected in the circulation of patients following VTE [66], and has been implicated as a risk factor for VTE recurrence [67,68]. sP-selectin has been found to be an independent predictor of VTE occurrence in patients with malignancy (11.9% in those with sP-selectin above the 75th percentile, and 3.7% below the 75th percentile) [69].

3.4. C-Reactive Protein (CRP)

Elevated CRP is a marker of inflammation and has been associated with increased risk of arterial thromboses [70]. CRP has also been studied in venous thrombosis. The HUNT2 study found CRP in the highest quintile was associated with a 1.6-fold odds ratio of subsequently developing venous thrombosis [71]. In patients following cancer-associated thrombosis, high CRP >4.5mg/L at 21 days after stopping anticoagulation could predict VTE recurrence, and in this cohort, 66% of patients could safely stop anticoagulation based on the 21-day CRP value [72].

3.5. Microparticles

Microparticles are small membrane vesicles measuring between 100 and 1000 nm in diameter that are released by cells in response to cell activation or apoptosis. Microparticles can display membrane phospholipids and tissue factor and can promote thrombin and fibrin formation via the tissue factor-dependent pathway [73]. Tissue factor positive microparticles have been found to be elevated in patients with recurrent DVT compared to normal individuals [74] and in patients following acute PE [75]. However, a study by Ay et al. did not find any association between microparticles and patients with a history of recurrent VTE [76]. Considerable heterogeneity of methods to enumerate microparticles has limited our ability to make direct comparisons between studies. The International Society of Thrombosis and Haemostasis (ISTH) has sought to standardise enumeration procedures across different platforms [77,78].
Individual biomarkers may be insufficiently able to discriminate VTE recurrence risk on their own, and therefore may be better utilised as part of a multivariate clinical prediction model in conjunction with clinical factors and other biomarkers. This approach has been most well studied for D-dimer but has also been explored for factor VIII [63]. Individual biomarkers often interrogate specific components of the coagulation system, and do not provide a global view of the complex interplay between the various components that contribute to pathological thrombosis. Hence, a comprehensive assessment of the various components of the coagulation system, as well as incorporating clinical information remains the future of individualised VTE risk assessments.

4. Future Directions and the Role of Global Coagulation Assays

One of the challenges with predicting VTE recurrence is the lack of a single reliable biomarker. Assays which can capture the interplay of multiple factors in the coagulation system may better reflect the in vivo conditions in an individual. Currently available clotting assays such as the prothrombin and active partial thromboplastin time only capture the start of the clotting process until the beginning of thrombin formation, leaving the majority of the coagulation and fibrinolytic process unexamined. Hence, assays evaluating the final product of the coagulation cascade (e.g., thrombin and fibrin) have been an active area of investigation and may provide a better assessment of the unique prothrombotic signature in each individual.

4.1. Thrombin Generation and VTE Recurrence

Thrombin has been recognised as a central component of the clotting system, with multiple functions including fibrin conversion, thrombomodulin activation, and thrombin activatable fibrinolysis inhibitor (TAFI) activation at high thrombin levels [79]. Advances in technique [80] have made thrombin generation assays more reliable and less labour-intensive, paving the way for clinical application. Several commercial thrombin generation assays are available. One of the most well-studied and widely available assays is the calibrated automated thrombogram (CAT), in which tissue factor and phospholipids are added to the test system and the generated thrombin is determined by its interaction with a fluorogenic substrate, detected by continuous measurement. The result is a thrombin generation curve from which several parameters can be determined: lag time (time until thrombin burst), peak thrombin (maximum level of thrombin generated), endogenous thrombin potential (ETP area under thrombin generation curve), time to peak thrombin, and velocity index (rate of thrombin generated).
Several studies have found positive associations between increased thrombin generation parameters and VTE recurrence [41,81,82,83,84]. Eichinger et al. followed 861 patients after the first unprovoked VTE, and using the Dade Behring ETP assay, found high ETP to be independently associated with increased risk of VTE recurrence (HR 1.6, 95% CI 1.0–2.4) even after adjustment for D-dimers [41]. Tripodi [82] et al., found ETP and peak thrombin as measured by the CAT to be associated with VTE recurrence following unprovoked VTE, and that addition of thrombomodulin into the test system resulted in more significant findings (HR for high peak thrombin of 4.57 in the presence of thrombomodulin, 2.65 in the absence of thrombomodulin). Addition of thrombomodulin to the test system is thought to better replicate in vivo conditions, because thrombomodulin is required to fully activate the protein C anticoagulant system. However, the optimal concentration of thrombomodulin may differ for each test system with a lack of standardisation across studies. Previous groups have determined their own in-house optimal concentrations of thrombomodulin needed to distinguish a population with prothrombotic phenotype [82,84,85]. Of note, several studies have investigated the use of an ETP-based activated protein C (APC) resistance test in the presence of thrombomodulin [86] in the setting of women using hormonal contraceptives [87]. This assay was able to detect APC resistance independently of the factor V Leiden mutation, suggesting that it may have a role in predicting hypercoagulability and VTE recurrence and warrants further investigation.
There have been two studies that have found no association between thrombin generation and VTE recurrence [85,88], however both studies had significant methodological issues. In the earlier study [85], due to insufficient plasma volume collected, CAT was performed on plasma diluted 1:4 with a buffer. Additionally, a much higher concentration of tissue factor (15 pM) was used to initiate coagulation and may have reduced the sensitivity of the test to hypercoagulability. In the latter study [88], blood samples were collected up to 25 months following anticoagulation cessation, which also diverges from other published studies.

4.2. Viscoelastic Tests and VTE Recurrence

Viscoelastic testing employs mechanical rotation to detect the kinetics of thrombus formation and lysis and is performed on whole blood (citrated or native), thus in theory is better reflecting of in vivo haemostasis, taking into account plasma clotting factors, platelets, leucocytes and red cells [89,90]. The two most commonly available commercial viscoelastic testing devices are thromboelastography (TEG®, Haemonetics, Braintree, MA, USA) and rotational thromboelastometry (ROTEM®, Haemoview Diagnostics, Brisbane, Australia). In the TEG® device, whole blood is placed in a cup with calcium and an activator (e.g., Kaolin) and warmed to 37 °C. The cup is then rotated around a pin, and, as the clot forms, fibrin strands increase the torsion around the pin, and decrease as fibrinolysis breaks down the fibrin strands. These changes in torque are then displayed graphically. In the ROTEM®, the pin itself oscillates within the cup, which remains stationary. Results from ROTEM® and TEG® are not interchangeable [91], and differences in blood used [92] (native whole blood vs citrated) as well as activators also introduce differences into results [93].
Viscoelastic testing has gained popularity and is widely used in guiding resuscitation during massive haemorrhages, especially in the settings of trauma-induced coagulopathy and post-partum haemorrhage [94,95,96]. However, although the evidence of assessing thrombotic risk is limited, growing research points to the ability of viscoelastic testing to detect a hypercoagulable state and an increased propensity to develop thrombosis. This has been found in cancer [97], trauma [98], and in the peri-operative setting [99]. Specifically, in VTE, TEG® was unable to detect a difference between 19 patients following cerebral venous thrombosis and sex- and age-matched controls [100]. In a study of portal vein thrombosis, ROTEM® detected no significant differences between cirrhotic patients who had developed portal vein thrombosis and those who had not [101]. To the best of our knowledge, there have not been any studies examining the association of a hypercoagulable state, as detected by viscoelastic testing with VTE recurrence. With current viscoelastic technology, the limitation of whole blood samples means large scale batch testing on stored samples is not feasible, and the current body of evidence examining VTE recurrence has focused on those assays which can utilize stored frozen plasma samples, such as the CAT.

4.3. Fibrin Generation, Fibrinolysis and VTE Recurrence

Abnormal fibrin clot structures such as reduced clot permeability, increased fibrin fibre density, and resistance to fibrinolysis have been linked to increased venous and arterial thromboembolism [102,103]. A complex system governs fibrinolysis and its regulatory mechanisms, and hypofibrinolysis has been postulated as a possible risk factor for VTE recurrence. However, studies interrogating individual components of the fibrinolytic pathway (plasminogen activator inhibitor-1 (PAI-1), tissue plasminogen activator (tPA), TAFI) have so far led to conflicting findings [104,105,106,107,108].
There have been efforts to develop assays to reflect the overall plasma fibrinolytic potential and the interplay of multiple parts of the fibrinolytic pathway. In the clot lysis time (CLT) test, plasma is activated with tissue factor, phospholipid, and calcium, and placed in a 96-well microtitre plate with exogenous tPA. The resulting changes in turbidity are detected by light absorbance at 405 nm, and the clot lysis time is defined by the time to 50% maximal turbidity to the time to half maximal lysis [109]. Meltzer [110] et al. have found that the CLT reflects levels of all fibrinolytic factors except t-PA, and after adjustment for acute-phase proteins TAFI and PAI-1 remained associated with thrombosis. Several studies have convincingly demonstrated that, compared to controls, subjects with VTE have evidence of hypofibrinolysis demonstrated by prolonged CLT [111,112,113]. Evidence linking CLT and VTE recurrence have been conflicting however [108,112,114,115,116], and may be due to heterogeneous study designs, inclusion criteria and assay methodologies.
The overall haemostatic potential (OHP) assay is a variant of the CLT and was devised by Blomback et al. in 1999 [117] and modified for laboratory use in 2001 [118]. Two parallel fibrin aggregation curves are made by running two samples in parallel: one with a small amount of thrombin or tissue factor to trigger fibrin generation (OCP), and the second curve by the addition of tPA resulting in fibrinolysis (OHP). The difference in the two curves results in the overall fibrinolytic potential (OFP), and is calculated using ((OCP-OHP)/OCP × 100%). The advantage of the OHP assay over CLT is the ability to interrogate both fibrin generation and lysis in one system. The most recent modification [119] of the OHP assay is also able to incorporate information about the speed of fibrin generation and lysis. This new assay is better able to correlate with changes in PAI-1 levels compared to the previously derived OFP [119]. Although there is limited evidence available suggesting that OHP can detect persistent hypercoagulable states and hypofibrinolysis following DVT and PE [120,121], there have been no studies exploring the link between increased OHP and VTE recurrence to our knowledge.

4.4. Limitations of Global Coagulation Assays

Research supporting the use of global coagulation assays as a predictor of VTE recurrence is promising but in its infancy. Standardisation of methodologies remains a major barrier to the reproducibility of results and must be improved before there can be widespread adoption in clinical practice. The ISTH has made recommendations to standardise thrombin generation measurements in haemophilia using CAT [122] as well as the CLT [123], in order to facilitate translation of results across different laboratories. New automated analysers such as the ST-Genesia analyser (Diagnostica Stago, France) have been commercialised, which will be crucial to facilitate mass throughput testing and ensure standardisation in clinical practice. Additionally, most research into global coagulation assays have been conducted in the bleeding disorder population and prior to the widespread adoption of DOACs, and further refinement is required in these areas.
A major practical issue limiting the widespread adoption of global coagulation assays, and indeed, most biomarkers, into clinical practice is the influence of concurrent anticoagulation therapy. Thrombin generation assays are affected by all anticoagulants and have been investigated as tools to monitor anticoagulant therapy [124,125,126]. Concurrent anticoagulants limit the ability of global assays and biomarkers to uncover the underlying hypercoagulable state. Consequently, the majority of studies examining biomarkers and global coagulation assays have been conducted on non-anticoagulated patients, usually around four weeks following anticoagulation cessation. However, the risk of VTE recurrence following anticoagulation cessation can be as high as 0.5–1.5% within the first month [17,127]. Hence, the decision to withhold anticoagulation to facilitate D-dimers or global coagulation testing, for instance, must be made cautiously in a patient in high clinical risk category of VTE recurrence.
Despite these limitations, global coagulation assays may more accurately reflect the balance between prothrombotic and bleeding states on an individual level and could become crucial diagnostic tools in the quest for individualised VTE recurrence risk assessment in the future.

5. Conclusions

Assessing the risk of VTE recurrence remains challenging and imperfect in the current era of DOACs, especially in the elderly, males, and those at a concurrent high risk of bleeding. Novel biomarkers and global coagulation assays may hold promise in improving the ability to risk-stratify patients following VTE and identify those low-risk individuals who can safely stop anticoagulation treatments. Future efforts should focus on developing new validated clinical prediction models and potentially incorporating multiple biomarkers and global coagulation assays that examine different parts of the coagulation system, which together may provide a more holistic picture of an individual’s prothrombotic state.

Author Contributions

Writing—original draft preparation, J.W.; writing—review and editing, H.Y.L. and P.H. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Heit, J.A. Epidemiology of Venous Thromboembolism. Nat. Rev. Cardiol. 2015, 12, 464–474. [Google Scholar] [CrossRef] [PubMed]
  2. Spencer, F.A.; Emery, C.; Joffe, S.W.; Pacifico, L.; Lessard, D.; Reed, G.; Gore, J.M.; Goldberg, R.J. Incidence Rates, Clinical Profile, and Outcomes of Patients with Venous Thromboembolism. The Worcester VTE Study. J. Thromb. Thrombolys. 2009, 28, 401–409. [Google Scholar] [CrossRef] [PubMed]
  3. Gary, E.R. Thrombosis: A Major Contributor to the Global Disease Burden. J. Thromb. Haemost. 2014, 12, 1580–1590. [Google Scholar] [CrossRef]
  4. Lim, H.Y.; Chua, C.C.; Tacey, M.; Sleeman, M.; Donnan, G.; Nandurkar, H.; Ho, P. Venous Thromboembolism Management in Northeast Melbourne: How Does It Compare to International Guidelines and Data? Intern. Med. J. 2017, 47, 1034–1042. [Google Scholar] [CrossRef]
  5. Christiansen, S.C.; Cannegieter, S.C.; Koster, T.; Vandenbroucke, J.P.; Rosendaal, F.R. Thrombophilia, Clinical Factors, and Recurrent Venous Thrombotic Events. JAMA 2005, 293, 2352–2361. [Google Scholar] [CrossRef]
  6. Douketis, J.; Tosetto, A.; Marcucci, M.; Baglin, T.; Cosmi, B.; Cushman, M.; Kyrle, P.; Poli, D.; Tait, R.C.; Iorio, A. Risk of Recurrence after Venous Thromboembolism in Men and Women: Patient Level Meta-Analysis. BMJ 2011, 342, d813. [Google Scholar] [CrossRef]
  7. Eichinger, S.; Hron, G.; Bialonczyk, C.; Hirschl, M.; Minar, E.; Wagner, O.; Heinze, G.; Kyrle, P.A. Overweight, Obesity, and the Risk of Recurrent Venous Thromboembolism. Arch. Intern. Med. 2008, 168, 1678–1683. [Google Scholar] [CrossRef]
  8. Chee, C.E.; Ashrani, A.A.; Marks, R.S.; Petterson, T.M.; Bailey, K.R.; Melton, L.J.; Heit, J.A. Predictors of Venous Thromboembolism Recurrence and Bleeding among Active Cancer Patients: A Population-Based Cohort Study. Blood 2014, 123, 3972–3978. [Google Scholar] [CrossRef]
  9. Khan, F.; Rahman, A.; Carrier, M.; Kearon, C.; Weitz, J.I.; Schulman, S.; Couturaud, F.; Eichinger, S.; Kyrle, P.A.; Becattini, C.; et al. Long Term Risk of Symptomatic Recurrent Venous Thromboembolism after Discontinuation of Anticoagulant Treatment for First Unprovoked Venous Thromboembolism Event: Systematic Review and Meta-Analysis. BMJ 2019, 366, l4363. [Google Scholar] [CrossRef]
  10. Kearon, C. Natural History of Venous Thromboembolism. Circulation 2003, 107, I-22–I-30. [Google Scholar] [CrossRef]
  11. Iorio, A.; Kearon, C.; Filippucci, E.; Marcucci, M.; Macura, A.; Pengo, V.; Siragusa, S.; Palareti, G. Risk of Recurrence After a First Episode of Symptomatic Venous Thromboembolism Provoked by a Transient Risk Factor: A Systematic ReviewRecurrence After VTE Provoked by Transient Risk Factor. JAMA Intern. Med. 2010, 170, 1710–1716. [Google Scholar] [CrossRef] [PubMed]
  12. Chua, C.C.; Lim, H.Y.; Tacey, M.; Nandurkar, H.; Ho, P. Retrospective Evaluation of Venous Thromboembolism: Are All Transient Provoking Events the Same? Eur. J. Haematol. 2017, 99, 18–26. [Google Scholar] [CrossRef] [PubMed]
  13. Kearon, C.; Kahn, S.R. Long-Term Treatment of Venous Thromboembolism. Blood 2020, 135, 317–325. [Google Scholar] [CrossRef] [PubMed]
  14. Prandoni, P.; Falanga, A.; Piccioli, A. Cancer and Venous Thromboembolism. Lancet Oncol. 2005, 6, 401–410. [Google Scholar] [CrossRef]
  15. Yang, G.; Staercke, C.D.; Hooper, W.C. The Effects of Obesity on Venous Thromboembolism: A Review. Open J. Prev. Med. 2012, 2012, 499–509. [Google Scholar] [CrossRef]
  16. Kearon, C.; Akl, E.A. Duration of Anticoagulant Therapy for Deep Vein Thrombosis and Pulmonary Embolism. Blood 2014, 123, 1794–1801. [Google Scholar] [CrossRef]
  17. Douketis, J.; Tosetto, A.; Marcucci, M.; Baglin, T.; Cushman, M.; Eichinger, S.; Palareti, G.; Poli, D.; Tait, R.C.; Iorio, A. Patient-Level Meta-Analysis: Effect of Measurement Timing, Threshold, and Patient Age on Ability of D-Dimer Testing to Assess Recurrence Risk after Unprovoked Venous Thromboembolism. Ann. Intern. Med. 2010, 153, 523–531. [Google Scholar] [CrossRef]
  18. Segal, J.B.; Brotman, D.J.; Necochea, A.J.; Emadi, A.; Samal, L.; Wilson, L.M.; Crim, M.T.; Bass, E.B. Predictive Value of Factor V Leiden and Prothrombin G20210A in Adults With Venous Thromboembolism and in Family Members of Those With a Mutation: A Systematic Review. JAMA 2009, 301, 2472–2485. [Google Scholar] [CrossRef]
  19. Weitz, J.I.; Lensing, A.W.A.; Prins, M.H.; Bauersachs, R.; Beyer-Westendorf, J.; Bounameaux, H.; Brighton, T.A.; Cohen, A.T.; Davidson, B.L.; Decousus, H.; et al. Rivaroxaban or Aspirin for Extended Treatment of Venous Thromboembolism. N. Engl. J. Med. 2017, 376, 1211–1222. [Google Scholar] [CrossRef]
  20. Agnelli, G.; Buller, H.R.; Cohen, A.; Curto, M.; Gallus, A.S.; Johnson, M.; Porcari, A.; Raskob, G.E.; Weitz, J.I.; Investigators, P.-E. Apixaban for Extended Treatment of Venous Thromboembolism. N. Engl. J. Med. 2013, 368, 699–708. [Google Scholar] [CrossRef]
  21. Mai, V.; Guay, C.-A.; Perreault, L.; Bonnet, S.; Bertoletti, L.; Lacasse, Y.; Jardel, S.; Lega, J.-C.; Provencher, S. Extended Anticoagulation for VTE A Systematic Review and Meta-Analysis. Chest 2019, 155, 1199–1216. [Google Scholar] [CrossRef] [PubMed]
  22. Ortel, T.L.; Neumann, I.; Ageno, W.; Beyth, R.; Clark, N.P.; Cuker, A.; Hutten, B.A.; Jaff, M.R.; Manja, V.; Schulman, S.; et al. American Society of Hematology 2020 Guidelines for Management of Venous Thromboembolism: Treatment of Deep Vein Thrombosis and Pulmonary Embolism. Blood Adv. 2020, 4, 4693–4738. [Google Scholar] [CrossRef] [PubMed]
  23. Kearon, C.; Akl, E.A.; Ornelas, J.; Blaivas, A.; Jimenez, D.; Bounameaux, H.; Huisman, M.; King, C.S.; Morris, T.A.; Sood, N.; et al. Antithrombotic Therapy for VTE Disease: CHEST Guideline and Expert Panel Report. Chest 2016, 149, 315–352. [Google Scholar] [CrossRef] [PubMed]
  24. Tran, H.A.; Gibbs, H.; Merriman, E.; Curnow, J.L.; Young, L.; Bennett, A.; Tan, C.W.; Chunilal, S.D.; Ward, C.M.; Baker, R.; et al. New Guidelines from the Thrombosis and Haemostasis Society of Australia and New Zealand for the Diagnosis and Management of Venous Thromboembolism. Med. J. Aust. 2019, 210, 227–235. [Google Scholar] [CrossRef]
  25. Schuh, T.; Reichardt, B.; Finsterer, J.; Stöllberger, C. Age-Dependency of Prescribing Patterns of Oral Anticoagulant Drugs in Austria during 2011–2014. J. Thromb. Thrombolys. 2016, 42, 447–451. [Google Scholar] [CrossRef]
  26. Loo, S.Y.; Dell’Aniello, S.; Huiart, L.; Renoux, C. Trends in the Prescription of Novel Oral Anticoagulants in UK Primary Care. Br. J. Clin. Pharmacol. 2017, 83, 2096–2106. [Google Scholar] [CrossRef]
  27. Ho, K.H.; van Hove, M.; Leng, G. Trends in Anticoagulant Prescribing: A Review of Local Policies in English Primary Care. BMC Health Ser. Res. 2020, 20, 279. [Google Scholar] [CrossRef]
  28. Pratt, N.L.; Ramsay, E.N.; Caughey, G.E.; Shakib, S.; Roughead, E.E. Uptake of Novel Oral Anticoagulants in Australia. Med. J. Aust. 2016, 204, 104–105. [Google Scholar] [CrossRef]
  29. Lip, G.Y.H.; Pan, X.; Kamble, S.; Kawabata, H.; Mardekian, J.; Masseria, C.; Bruno, A.; Phatak, H. Major Bleeding Risk among Non-Valvular Atrial Fibrillation Patients Initiated on Apixaban, Dabigatran, Rivaroxaban or Warfarin: A “Real-World” Observational Study in the United States. Int. J. Clin. Pract. 2016, 70, 752–763. [Google Scholar] [CrossRef]
  30. Yao, X.; Abraham, N.S.; Sangaralingham, L.R.; Bellolio, M.F.; McBane, R.D.; Shah, N.D.; Noseworthy, P.A. Effectiveness and Safety of Dabigatran, Rivaroxaban, and Apixaban Versus Warfarin in Nonvalvular Atrial Fibrillation. J. Am. Heart Assoc. 2016, 5, e003725. [Google Scholar] [CrossRef]
  31. Chai-Adisaksopha, C.; Hillis, C.; Isayama, T.; Lim, W.; Iorio, A.; Crowther, M. Mortality Outcomes in Patients Receiving Direct Oral Anticoagulants: A Systematic Review and Meta-analysis of Randomized Controlled Trials. J. Thromb. Haemost. 2015, 13, 2012–2020. [Google Scholar] [CrossRef] [PubMed]
  32. Huiart, L.; Ferdynus, C.; Renoux, C.; Beaugrand, A.; Lafarge, S.; Bruneau, L.; Suissa, S.; Maillard, O.; Ranouil, X. Trends in Initiation of Direct Oral Anticoagulant Therapies for Atrial Fibrillation in a National Population-Based Cross-Sectional Study in the French Health Insurance Databases. BMJ Open 2018, 8, e018180. [Google Scholar] [CrossRef] [PubMed]
  33. Ageno, W.; Mantovani, L.G.; Haas, S.; Kreutz, R.; Monje, D.; Schneider, J.; van Eickels, M.; Gebel, M.; Zell, E.; Turpie, A.G.G. Safety and Effectiveness of Oral Rivaroxaban versus Standard Anticoagulation for the Treatment of Symptomatic Deep-Vein Thrombosis (XALIA): An International, Prospective, Non-Interventional Study. Lancet Haematol. 2016, 3, e12–e21. [Google Scholar] [CrossRef]
  34. Beyer-Westendorf, J.; Förster, K.; Pannach, S.; Ebertz, F.; Gelbricht, V.; Thieme, C.; Michalski, F.; Köhler, C.; Werth, S.; Sahin, K.; et al. Rates, Management, and Outcome of Rivaroxaban Bleeding in Daily Care: Results from the Dresden NOAC Registry. Blood 2014, 124, 955–962. [Google Scholar] [CrossRef] [PubMed]
  35. Investigators, E.; Bauersachs, R.; Berkowitz, S.D.; Brenner, B.; Buller, H.R.; Decousus, H.; Gallus, A.S.; Lensing, A.W.; Misselwitz, F.; Prins, M.H.; et al. Oral Rivaroxaban for Symptomatic Venous Thromboembolism. N. Engl. J. Med. 2010, 363, 2499–2510. [Google Scholar] [CrossRef]
  36. Lim, H.Y.; O’Malley, C.; Donnan, G.; Nandurkar, H.; Ho, P. A Review of Global Coagulation Assays—Is There a Role in Thrombosis Risk Prediction? Thromb. Res. 2019, 179, 45–55. [Google Scholar] [CrossRef]
  37. Pisters, R.; Lane, D.A.; Nieuwlaat, R.; de Vos, C.B.; Crijns, H.J.G.M.; Lip, G.Y.H. A Novel User-Friendly Score (HAS-BLED) To Assess 1-Year Risk of Major Bleeding in Patients with Atrial Fibrillation the Euro Heart Survey. Chest 2010, 138, 1093–1100. [Google Scholar] [CrossRef]
  38. Rodger, M.A.; Gal, G.L.; Anderson, D.R.; Schmidt, J.; Pernod, G.; Kahn, S.R.; Righini, M.; Mismetti, P.; Kearon, C.; Meyer, G.; et al. Validating the HERDOO2 Rule to Guide Treatment Duration for Women with Unprovoked Venous Thrombosis: Multinational Prospective Cohort Management Study. BMJ 2017, 356, j1065. [Google Scholar] [CrossRef]
  39. Rodger, M.A.; Kahn, S.R.; Wells, P.S.; Anderson, D.A.; Chagnon, I.; le Gal, G.; Solymoss, S.; Crowther, M.; Perrier, A.; White, R.; et al. Identifying Unprovoked Thromboembolism Patients at Low Risk for Recurrence Who Can Discontinue Anticoagulant Therapy. Can. Med Assoc. J. 2008, 179, 417–426. [Google Scholar] [CrossRef]
  40. Tosetto, A.; Iorio, A.; Marcucci, M.; Baglin, T.; Cushman, M.; Eichinger, S.; Palareti, G.; Poli, D.; Tait, R.C.; Douketis, J. Predicting Disease Recurrence in Patients with Previous Unprovoked Venous Thromboembolism: A Proposed Prediction Score (DASH). J. Thromb. Haemost. 2012, 10, 1019–1025. [Google Scholar] [CrossRef]
  41. Eichinger, S.; Hron, G.; Kollars, M.; Kyrle, P.A. Prediction of Recurrent Venous Thromboembolism by Endogenous Thrombin Potential and D-Dimer. Clin. Chem. 2008, 54, 2042–2048. [Google Scholar] [CrossRef] [PubMed]
  42. Eichinger, S.; Heinze, G.; Kyrle, P.A. D-Dimer Levels Over Time and the Risk of Recurrent Venous Thromboembolism: An Update of the Vienna Prediction Model. J. Am. Heart Assoc. 2014, 3, e000467. [Google Scholar] [CrossRef] [PubMed]
  43. Tosetto, A.; Testa, S.; Martinelli, I.; Poli, D.; Cosmi, B.; Lodigiani, C.; Ageno, W.; Stefano, V.D.; Falanga, A.; Nichele, I.; et al. External Validation of the DASH Prediction Rule: A Retrospective Cohort Study. J. Thromb. Haemost. 2017, 15, 1963–1970. [Google Scholar] [CrossRef] [PubMed]
  44. Geersing, G.-J.; Hendriksen, J.M.T.; Zuithoff, N.P.A.; Roes, K.C.; Oudega, R.; Takada, T.; Schutgens, R.E.G.; Moons, K.G.M. Effect of Tailoring Anticoagulant Treatment Duration by Applying a Recurrence Risk Prediction Model in Patients with Venous Thromboembolism Compared to Usual Care: A Randomized Controlled Trial. PLoS Med. 2020, 17, e1003142. [Google Scholar] [CrossRef] [PubMed]
  45. Tritschler, T.; Méan, M.; Limacher, A.; Rodondi, N.; Aujesky, D. Predicting Recurrence after Unprovoked Venous Thromboembolism: Prospective Validation of the Updated Vienna Prediction Model. Blood 2015, 126, 1949–1951. [Google Scholar] [CrossRef]
  46. MacDonald, S.; Chengal, R.; Hanxhiu, A.; Symington, E.; Sheares, K.; Besser, M.; Thomas, W. Utility of the DASH Score after Unprovoked Venous Thromboembolism; a Single Centre Study. Br. J. Haematol. 2019, 185, 631–633. [Google Scholar] [CrossRef] [PubMed]
  47. Adam, S.S.; Key, N.S.; Greenberg, C.S. D-Dimer Antigen: Current Concepts and Future Prospects. Blood 2009, 113, 2878–2887. [Google Scholar] [CrossRef]
  48. Palareti, G.; Cosmi, B.; Legnani, C.; Tosetto, A.; Brusi, C.; Iorio, A.; Pengo, V.; Ghirarduzzi, A.; Pattacini, C.; Testa, S.; et al. D-Dimer Testing to Determine the Duration of Anticoagulation Therapy. N. Engl. J. Med. 2006, 355, 1780–1789. [Google Scholar] [CrossRef]
  49. Palareti, G.; Cosmi, B.; Legnani, C.; Antonucci, E.; Micheli, V.D.; Ghirarduzzi, A.; Poli, D.; Testa, S.; Tosetto, A.; Pengo, V.; et al. D-Dimer to Guide the Duration of Anticoagulation in Patients with Venous Thromboembolism: A Management Study. Blood 2014, 124, 196–203. [Google Scholar] [CrossRef]
  50. Cosmi, B.; Legnani, C.; Tosetto, A.; Pengo, V.; Ghirarduzzi, A.; Testa, S.; Prisco, D.; Poli, D.; Tripodi, A.; Marongiu, F.; et al. Usefulness of Repeated D-Dimer Testing after Stopping Anticoagulation for a First Episode of Unprovoked Venous Thromboembolism: The PROLONG II Prospective Study. Blood 2010, 115, 481–488. [Google Scholar] [CrossRef]
  51. Cosmi, B.; Legnani, C.; Cini, M.; Guazzaloca, G.; Palareti, G. D-Dimer and Residual Vein Obstruction as Risk Factors for Recurrence during and after Anticoagulation Withdrawal in Patients with a First Episode of Provoked Deep-Vein Thrombosis. Thromb. Haemost. 2011, 105, 837–845. [Google Scholar] [CrossRef] [PubMed]
  52. BAGLIN, T.; PALMER, C.R.; LUDDINGTON, R.; BAGLIN, C. Unprovoked Recurrent Venous Thrombosis: Prediction by D-Dimer and Clinical Risk Factors. J. Thromb. Haemost. 2008, 6, 577–582. [Google Scholar] [CrossRef] [PubMed]
  53. Avnery, O.; Martin, M.; Riviere, A.B.; Barillari, G.; Mazzolai, L.; Mahé, I.; Marchena, P.J.; Verhamme, P.; Monreal, M.; Ellis, M.H.; et al. D-dimer Levels and Risk of Recurrence Following Provoked Venous Thromboembolism: Findings from the RIETEregistry. J. Intern. Med. 2019, 287, 32–41. [Google Scholar] [CrossRef] [PubMed]
  54. Wang, J.; Tacey, M.; Ho, P. Retrospective Review of D-Dimer Testing for Venous Thrombosis Recurrence Risk Stratification: Is This a Useful Test in the Real World? J. Thromb. Thrombolys. 2020, 49, 562–571. [Google Scholar] [CrossRef]
  55. Kearon, C.; Spencer, F.A.; O’Keeffe, D.; Parpia, S.; Schulman, S.; Baglin, T.; Stevens, S.M.; Kaatz, S.; Bauer, K.A.; Douketis, J.D.; et al. D-Dimer Testing to Select Patients With a First Unprovoked Venous Thromboembolism Who Can Stop Anticoagulant Therapy. Ann. Intern. Med. 2015, 162, 27–34. [Google Scholar] [CrossRef]
  56. Douma, R.A.; le Gal, G.; Sohne, M.; Righini, M.; Kamphuisen, P.W.; Perrier, A.; Kruip, M.J.H.A.; Bounameaux, H.; Buller, H.R.; Roy, P.M. Potential of an Age Adjusted D-Dimer Cut-off Value to Improve the Exclusion of Pulmonary Embolism in Older Patients: A Retrospective Analysis of Three Large Cohorts. BMJ 2010, 340, c1475. [Google Scholar] [CrossRef]
  57. Mullier, F.; Vanpee, D.; Jamart, J.; Dubuc, E.; Bailly, N.; Douxfils, J.; Chatelain, C.; Dogné, J.-M.; Chatelain, B. Comparison of Five D-Dimer Reagents and Application of an Age-Adjusted Cut-off for the Diagnosis of Venous Thromboembolism in Emergency Department. Blood Coagul. Fibrin. 2014, 25, 309–315. [Google Scholar] [CrossRef]
  58. Riley, R.S.; Gilbert, A.R.; Dalton, J.B.; Pai, S.; McPherson, R.A. Widely Used Types and Clinical Applications of D-Dimer Assay. Lab Med. 2016, 47, 90–102. [Google Scholar] [CrossRef]
  59. Legnani, C.; Martinelli, I.; Palareti, G.; Ciavarella, A.; Poli, D.; Ageno, W.; Testa, S.; Mastroiacovo, D.; Ciammaichella, M.; Bucherini, E.; et al. D-Dimer Levels during and after Anticoagulation Withdrawal in Patients with Venous Thromboembolism Treated with Non-Vitamin K Anticoagulants. PLoS ONE 2019, 14, e0219751-9. [Google Scholar] [CrossRef]
  60. O’Donnell, J.; Mumford, A.; Manning, R.; Laffan, M. Elevation of FVIII: C in Venous Thromboembolism Is Persistent and Independent of the Acute Phase Response. Thromb. Haemost. 2000, 83, 10–13. [Google Scholar] [CrossRef]
  61. Tichelaar, V.; Mulder, A.; Kluin-Nelemans, H.; Meijer, K. The Acute Phase Reaction Explains Only a Part of Initially Elevated Factor VIII:C Levels: A Prospective Cohort Study in Patients with Venous Thrombosis. Thromb. Res. 2012, 129, 183–186. [Google Scholar] [CrossRef] [PubMed]
  62. LIJFERING, W.M.; CHRISTIANSEN, S.C.; ROSENDAAL, F.R.; CANNEGIETER, S.C. Contribution of High Factor VIII, IX and XI to the Risk of Recurrent Venous Thrombosis in Factor V Leiden Carriers. J. Thromb. Haemost. 2009, 7, 1944–1946. [Google Scholar] [CrossRef] [PubMed]
  63. Timp, J.F.; Lijfering, W.M.; Flinterman, L.E.; Vlieg, A.H.; Cessie, S.; Rosendaal, F.R.; Cannegieter, S.C. Predictive Value of Factor VIII Levels for Recurrent Venous Thrombosis: Results from the MEGA Follow-up Study. J. Thromb. Haemost. 2015, 13, 1823–1832. [Google Scholar] [CrossRef] [PubMed]
  64. Chen, M.; Geng, J.-G. P-Selectin Mediates Adhesion of Leukocytes, Platelets, and Cancer Cells in Inflammation, Thrombosis, and Cancer Growth and Metastasis. Arch. Immunol. Ther. Exp. 2006, 54, 75–84. [Google Scholar] [CrossRef] [PubMed]
  65. Palabrica, T.; Lobb, R.; Furie, B.C.; Aronovitz, M.; Benjamin, C.; Hsu, Y.-M.; Sajer, S.A.; Furie, B. Leukocyte Accumulation Promoting Fibrin Deposition Is Mediated in Vivo by P-Selectin on Adherent Platelets. Nature 1992, 359, 848–851. [Google Scholar] [CrossRef]
  66. Blann, A.D.; Noteboom, W.M.P.; Rosendaal, F.R. Increased Soluble P-selectin Levels Following Deep Venous Thrombosis: Cause or Effect? Br. J. Haematol. 2000, 108, 191–193. [Google Scholar] [CrossRef] [PubMed]
  67. Ay, C.; Pabinger, I.; Cohen, A.T. Cancer-Associated Venous Thromboembolism: Burden, Mechanisms, and Management. Thromb. Haemost. 2017, 117, 219–230. [Google Scholar] [CrossRef]
  68. Kyrle, P.; Hron, G.; Eichinger, S.; Wagner, O. Circulating P-Selectin and the Risk of Recurrent Venous Thromboembolism. Thromb. Haemost. 2007, 97, 880–883. [Google Scholar] [CrossRef]
  69. Ay, C.; Jungbauer, L.V.; Sailer, T.; Tengler, T.; Koder, S.; Kaider, A.; Panzer, S.; Quehenberger, P.; Pabinger, I.; Mannhalter, C. High Concentrations of Soluble P-Selectin Are Associated with Risk of Venous Thromboembolism and the P-Selectin Thr715 Variant. Clin. Chem. 2007, 53, 1235–1243. [Google Scholar] [CrossRef]
  70. Ridker, P.M.; Cushman, M.; Stampfer, M.J.; Tracy, R.P.; Hennekens, C.H. Inflammation, Aspirin, and the Risk of Cardiovascular Disease in Apparently Healthy Men. N. Engl. J. Med. 1997, 336, 973–979. [Google Scholar] [CrossRef]
  71. Quist-Paulsen, P.; Næss, I.A.; Cannegieter, S.C.; Romundstad, P.R.; Christiansen, S.C.; Rosendaal, F.R.; Hammerstrøm, J. Arterial Cardiovascular Risk Factors and Venous Thrombosis: Results from a Population-Based, Prospective Study (the HUNT 2). Haematologica 2010, 95, 119–125. [Google Scholar] [CrossRef] [PubMed]
  72. Jara-Palomares, L.; Solier-Lopez, A.; Elias-Hernandez, T.; Asensio-Cruz, M.I.; Blasco-Esquivias, I.; Sanchez-Lopez, V.; de la Borbolla, M.R.; Arellano-Orden, E.; Suarez-Valdivia, L.; Marin-Romero, S.; et al. D-Dimer and High-Sensitivity C-Reactive Protein Levels to Predict Venous Thromboembolism Recurrence after Discontinuation of Anticoagulation for Cancer-Associated Thrombosis. Br. J. Cancer 2018, 119, 915–921. [Google Scholar] [CrossRef] [PubMed]
  73. Lacroix, R.; Dubois, C.; Leroyer, A.S.; Sabatier, F.; Dignat-George, F. Revisited Role of Microparticles in Arterial and Venous Thrombosis. J. Thromb. Haemost. 2013, 11, 24–35. [Google Scholar] [CrossRef]
  74. Ye, R.; Ye, C.; Huang, Y.; Liu, L.; Wang, S. Circulating Tissue Factor Positive Microparticles in Patients with Acute Recurrent Deep Venous Thrombosis. Thromb. Res. 2012, 130, 253–258. [Google Scholar] [CrossRef]
  75. Bal, L.; Ederhy, S.; Angelantonio, E.D.; Toti, F.; Zobairi, F.; Dufaitre, G.; Meuleman, C.; Mallat, Z.; Boccara, F.; Tedgui, A.; et al. Factors Influencing the Level of Circulating Procoagulant Microparticles in Acute Pulmonary Embolism. Arch. Cardiovasc. Dis. 2010, 103, 394–403. [Google Scholar] [CrossRef] [PubMed]
  76. Ay, C.; Freyssinet, J.-M.; Sailer, T.; Vormittag, R.; Pabinger, I. Circulating Procoagulant Microparticles in Patients with Venous Thromboembolism. Thromb. Res. 2009, 123, 724–726. [Google Scholar] [CrossRef] [PubMed]
  77. Cointe, S.; Judicone, C.; Robert, S.; Mooberry, M.J.; Poncelet, P.; Wauben, M.; Nieuwland, R.; Key, N.S.; Dignat-George, F.; Lacroix, R. Standardization of Microparticle Enumeration across Different Flow Cytometry Platforms: Results of a Multicenter Collaborative Workshop. J. Thromb. Haemost. 2017, 15, 187–193. [Google Scholar] [CrossRef] [PubMed]
  78. Lacroix, R.; Judicone, C.; Mooberry, M.; Boucekine, M.; Key, N.S.; Dignat-George, F.; Workshop, T.I.S. Standardization of Pre-analytical Variables in Plasma Microparticle Determination: Results of the International Society on Thrombosis and Haemostasis SSC Collaborative Workshop. J. Thromb. Haemost. 2013, 11, 1190–1193. [Google Scholar] [CrossRef] [PubMed]
  79. Hemker Thrombin Generation: An Essential Step in Haemostasis and Thrombosis. In Haemostasis and Thrombosis; Forbes, C.D.; Bloom, A.L.; Thomas, D.P. (Eds.) Churchill Livingstone: London, UK, 1994; pp. 477–492. [Google Scholar]
  80. Hemker, H.C.; Giesen, P.; Dieri, R.A.; Regnault, V.; de Smedt, E.; Wagenvoord, R.; Lecompte, T.; Béguin, S. Calibrated Automated Thrombin Generation Measurement in Clotting Plasma. Pathophysiol. Haemost. Thromb. 2003, 33, 4–15. [Google Scholar] [CrossRef]
  81. Besser, M.; Baglin, C.; Luddington, R.; Vlieg, A.V.H.; Baglin, T. High Rate of Unprovoked Recurrent Venous Thrombosis Is Associated with High Thrombin-generating Potential in a Prospective Cohort Study. J. Thromb. Haemost. 2008, 6, 1720–1725. [Google Scholar] [CrossRef]
  82. Tripodi, A.; Legnani, C.; Chantarangkul, V.; Cosmi, B.; Palareti, G.; Mannucci, P.M. High Thrombin Generation Measured in the Presence of Thrombomodulin Is Associated with an Increased Risk of Recurrent Venous Thromboembolism. J. Thromb. Haemost. 2008, 6, 1327–1333. [Google Scholar] [CrossRef] [PubMed]
  83. Hron, G.; Kollars, M.; Binder, B.R.; Eichinger, S.; Kyrle, P.A. Identification of Patients at Low Risk for Recurrent Venous Thromboembolism by Measuring Thrombin Generation. JAMA 2006, 296, 397–402. [Google Scholar] [CrossRef] [PubMed]
  84. Dargaud, Y.; Trzeciak, M.; Bordet, J.; Ninet, J.; Negrier, C. Use of Calibrated Automated Thrombinography? Thrombomodulin to Recognise the Prothrombotic Phenotype. Thromb. Haemost. 2006, 96, 562–567. [Google Scholar] [CrossRef] [PubMed]
  85. Van Hylckama Vlieg, A.; Christiansen, S.C.; Luddington, R.; Cannegieter, S.C.; Rosendaal, F.R.; Baglin, T.P. Elevated Endogenous Thrombin Potential Is Associated with an Increased Risk of a First Deep Venous Thrombosis but Not with the Risk of Recurrence. Br. J. Haematol. 2007, 138, 769–774. [Google Scholar] [CrossRef]
  86. Tripodi, A.; Primignani, M.; Lemma, L.; Chantarangkul, V.; Dell’Era, A.; Iannuzzi, F.; Aghemo, A.; Mannucci, P.M. Detection of the Imbalance of Procoagulant versus Anticoagulant Factors in Cirrhosis by a Simple Laboratory Method. Hepatology 2010, 52, 249–255. [Google Scholar] [CrossRef]
  87. Douxfils, J.; Morimont, L.; Delvigne, A.-S.; Devel, P.; Masereel, B.; Haguet, H.; Bouvy, C.; Dogné, J.-M. Validation and Standardization of the ETP-Based Activated Protein C Resistance Test for the Clinical Investigation of Steroid Contraceptives in Women: An Unmet Clinical and Regulatory Need. Clin. Chem. Lab. Med. 2020, 58, 294–305. [Google Scholar] [CrossRef]
  88. Van Hylckama Vlieg, A.; Baglin, C.A.; LUDDINGTON, R.; MacDonald, S.; Rosendaal, F.R.; Baglin, T.P. The Risk of a First and a Recurrent Venous Thrombosis Associated with an Elevated D-Dimer Level and an Elevated Thrombin Potential: Results of the THE-VTE Study. J. Thromb. Haemost. 2015, 13, 1642–1652. [Google Scholar] [CrossRef]
  89. McCrath, D.J.; Cerboni, E.; Frumento, R.J.; Hirsh, A.L.; Bennett-Guerrero, E. Thromboelastography Maximum Amplitude Predicts Postoperative Thrombotic Complications Including Myocardial Infarction. Anesth. Analg. 2005, 100, 1576–1583. [Google Scholar] [CrossRef]
  90. Spiel, A.O.; Mayr, F.B.; Firbas, C.; Quehenberger, P.; Jilma, B. Validation of Rotation Thrombelastography in a Model of Systemic Activation of Fibrinolysis and Coagulation in Humans. J. Thromb. Haemost. 2006, 4, 411–416. [Google Scholar] [CrossRef]
  91. Venema, L.F.; Post, W.J.; Hendriks, H.G.; Huet, R.C.; de Wolf, J.T.W.; de Vries, A.J. An Assessment of Clinical Interchangeability of TEG® and RoTEM® Thromboelastographic Variables in Cardiac Surgical Patients. Anesth. Analg. 2010, 111, 339–344. [Google Scholar] [CrossRef]
  92. Zambruni, A.; Thalheimer, U.; Leandro, G.; Perry, D.; Burroughs, A.K. Thromboelastography with Citrated Blood. Blood Coagul. Fibrin. 2004, 15, 103–107. [Google Scholar] [CrossRef] [PubMed]
  93. Sørensen, B.; Johansen, P.; Christiansen, K.; Woelke, M.; Ingerslev, J. Whole Blood Coagulation Thrombelastographic Profiles Employing Minimal Tissue Factor Activation. J. Thromb. Haemost. 2003, 1, 551–558. [Google Scholar] [CrossRef] [PubMed]
  94. Levi, M.; Hunt, B.J. A Critical Appraisal of Point-of-care Coagulation Testing in Critically Ill Patients. J. Thromb. Haemost. 2015, 13, 1960–1967. [Google Scholar] [CrossRef]
  95. Curry, N.S.; Davenport, R. Transfusion Strategies for Major Haemorrhage in Trauma. Br. J. Haematol. 2019, 184, 508–523. [Google Scholar] [CrossRef]
  96. Schöchl, H.; Maegele, M.; Solomon, C.; Görlinger, K.; Voelckel, W. Early and Individualized Goal-Directed Therapy for Trauma-Induced Coagulopathy. Scand. J. Trauma Resusc. Emerg. Med. 2012, 20, 15. [Google Scholar] [CrossRef] [PubMed]
  97. Walsh, M.; Moore, E.E.; Moore, H.; Thomas, S.; Lune, S.V.; Zimmer, D.; Dynako, J.; Hake, D.; Crowell, Z.; McCauley, R.; et al. Use of Viscoelastography in Malignancy-Associated Coagulopathy and Thrombosis: A Review. Semin. Thromb. Hemost. 2019, 45, 354–372. [Google Scholar] [CrossRef] [PubMed]
  98. Harahsheh, Y.; Ho, K.M. Use of Viscoelastic Tests to Predict Clinical Thromboembolic Events: A Systematic Review and Meta-analysis. Eur. J. Haematol. 2018, 100, 113–123. [Google Scholar] [CrossRef]
  99. Brown, W.; Lunati, M.; Maceroli, M.; Ernst, A.; Staley, C.; Johnson, R.; Schenker, M. Ability of Thromboelastography to Detect Hypercoagulability: A Systematic Review and Meta-Analysis. J. Orthop. Trauma 2020, 34, 278–286. [Google Scholar] [CrossRef]
  100. Koopman, K.; Uyttenboogaart, M.; Hendriks, H.G.D.; Luijckx, G.-J.; Cramwinckel, I.R.; Vroomen, P.C.; Keyser, J.D.; van der Meer, J. Thromboelastography in Patients with Cerebral Venous Thrombosis. Thromb. Res. 2009, 124, 185–188. [Google Scholar] [CrossRef]
  101. Rossetto, V.; Spiezia, L.; Senzolo, M.; Rodriguez-Castro, K.I.; Maggiolo, S.; Simioni, P. Whole Blood Rotation Thromboelastometry (ROTEM®) Profiles in Subjects with Non-Neoplastic Portal Vein Thrombosis. Thromb. Res. 2013, 132, e131–e134. [Google Scholar] [CrossRef]
  102. Undas, A.; Natorska, J. Improving Fibrinolysis in Venous Thromboembolism: Impact of Fibrin Structure. Expert Rev. Hematol. 2019, 12, 597–607. [Google Scholar] [CrossRef] [PubMed]
  103. Undas, A. How to Assess Fibrinogen Levels and Fibrin Clot Properties in Clinical Practice? Semin. Thromb. Hemost. 2016, 42, 381–388. [Google Scholar] [CrossRef] [PubMed]
  104. Crowther, M.A.; Roberts, J.; Roberts, R.; Johnston, M.; Stevens, P.; Skingley, P.; Patrassi, G.M.; Sartori, M.T.; Hirsh, J.; Prandoni, P.; et al. Fibrinolytic Variables in Patients with Recurrent Venous Thrombosis: A Prospective Cohort Study. Thromb. Haemost. 2001, 85, 390–394. [Google Scholar] [PubMed]
  105. Folsom, A.R.; Cushman, M.; Heckbert, S.R.; Rosamond, W.D.; Aleksic, N. Prospective Study of Fibrinolytic Markers and Venous Thromboembolism. J. Clin. Epidemiol. 2003, 56, 598–603. [Google Scholar] [CrossRef]
  106. Schulman, S.; Wiman, B. The Significance of Hypofibrinolysis for the Risk of Recurrence of Venous Thromboembolism. Duration of Anticoagulation (DURAC) Trial Study Group. Thromb. Haemost. 1996, 75, 607–611. [Google Scholar]
  107. Eichinger, S.; Schönauer, V.; Weltermann, A.; Minar, E.; Bialonczyk, C.; Hirschl, M.; Schneider, B.; Quehenberger, P.; Kyrle, P.A. Thrombin-Activatable Fibrinolysis Inhibitor and the Risk for Recurrent Venous Thromboembolism. Blood 2004, 103, 3773–3776. [Google Scholar] [CrossRef]
  108. Meltzer, M.E.; Bol, L.; Rosendaal, F.R.; Lisman, T.; Cannegieter, S.C. Hypofibrinolysis as a Risk Factor for Recurrent Venous Thrombosis; Results of the LETS Follow-up Study. J. Thromb. Haemost. 2010, 8, 605–607. [Google Scholar] [CrossRef]
  109. Lisman, T. Decreased Plasma Fibrinolytic Potential as a Risk for Venous and Arterial Thrombosis. Semin. Thromb. Hemost. 2016, 43, 178–184. [Google Scholar] [CrossRef]
  110. Meltzer, M.E.; Lisman, T.; de Groot, P.G.; Meijers, J.C.M.; le Cessie, S.; Doggen, C.J.M.; Rosendaal, F.R. Venous Thrombosis Risk Associated with Plasma Hypofibrinolysis Is Explained by Elevated Plasma Levels of TAFI and PAI-1. Blood 2010, 116, 113–121. [Google Scholar] [CrossRef]
  111. Lisman, T.; de Groot, P.G.; Meijers, J.C.M.; Rosendaal, F.R. Reduced Plasma Fibrinolytic Potential Is a Risk Factor for Venous Thrombosis. Blood 2005, 105, 1102–1105. [Google Scholar] [CrossRef]
  112. Karasu, A.; Baglin, T.P.; Luddington, R.; Baglin, C.A.; Vlieg, A.H. Prolonged Clot Lysis Time Increases the Risk of a First but Not Recurrent Venous Thrombosis. Br. J. Haematol. 2016, 172, 947–953. [Google Scholar] [CrossRef]
  113. Meltzer, M.E.; Lisman, T.; Doggen, C.J.M.; de Groot, P.G.; Rosendaal, F.R. Synergistic Effects of Hypofibrinolysis and Genetic and Acquired Risk Factors on the Risk of a First Venous Thrombosis. PLoS Med. 2008, 5, e97. [Google Scholar] [CrossRef] [PubMed]
  114. Traby, L.; Kollars, M.; Eischer, L.; Eichinger, S.; Kyrle, P.A. Prediction of Recurrent Venous Thromboembolism by Clot Lysis Time: A Prospective Cohort Study. PLoS ONE 2012, 7, e51447. [Google Scholar] [CrossRef]
  115. Zabczyk, M.; Plens, K.; Wojtowicz, W.; Undas, A. Prothrombotic Fibrin Clot Phenotype Is Associated With Recurrent Pulmonary Embolism After Discontinuation of Anticoagulant Therapy. Arterioscler. Thromb. Vasc. Biol. 2018, 37, 365–373. [Google Scholar] [CrossRef]
  116. Cieslik, J.; Mrozinska, S.; Broniatowska, E.; Undas, A. Altered Plasma Clot Properties Increase the Risk of Recurrent Deep Vein Thrombosis: A Cohort Study. Blood 2018, 131, 797–807. [Google Scholar] [CrossRef] [PubMed]
  117. He, S.; Bremme, K.; Blombäck, M. A Laboratory Method for Determination of Overall Haemostatic Potential in Plasma. I. Method Design and Preliminary Results. Thromb. Res. 1999, 96, 145–156. [Google Scholar] [CrossRef]
  118. He, S.; Antovic, A.; Blombäck, M. A Simple and Rapid Laboratory Method for Determination of Haemostasis Potential in Plasma: II. Modifications for Use in Routine Laboratories and Research Work. Thromb. Res. 2001, 103, 355–361. [Google Scholar] [CrossRef]
  119. He, S.; Zhu, K.; Skeppholm, M.; Vedin, J.; Svensson, J.; Egberg, N.; Blombäck, M.; Wallen, H. A Global Assay of Haemostasis Which Uses Recombinant Tissue Factor and Tissue-Type Plasminogen Activator to Measure the Rate of Fibrin Formation and Fibrin Degradation in Plasma. Thromb. Haemost. 2007, 98, 871–882. [Google Scholar]
  120. Chow, V.; Reddel, C.; Pennings, G.; Chung, T.; Ng, A.C.C.; Curnow, J.; Kritharides, L. Persistent Global Hypercoagulability in Long-Term Survivors of Acute Pulmonary Embolism. Blood Coagul. Fibrin. 2015, 26, 537–544. [Google Scholar] [CrossRef]
  121. Antovic, A.; Blombäck, M.; Bremme, K.; Rooijen, M.V.; He, S. Increased Hemostasis Potential Persists in Women with Previous Thromboembolism with or without APC Resistance. J. Thromb. Haemost. 2003, 1, 2531–2535. [Google Scholar] [CrossRef]
  122. Dargaud, Y.; Wolberg, A.S.; Gray, E.; Negrier, C.; Hemker, H.C. Proposal for Standardized Preanalytical and Analytical Conditions for Measuring Thrombin Generation in Hemophilia: Communication from the SSC of the ISTH. J. Thromb. Haemost. 2017, 15, 1704–1707. [Google Scholar] [CrossRef] [PubMed]
  123. Pieters, M.; Philippou, H.; Undas, A.; de Lange, Z.; Rijken, D.C.; Mutch, N.J. Fibrinolysis, for the S. on F.X. and F., and the Subcommittee on An International Study on the Feasibility of a Standardized Combined Plasma Clot Turbidity and Lysis Assay: Communication from the SSC of the ISTH. J. Thromb. Haemost. 2018, 16, 1007–1012. [Google Scholar] [CrossRef] [PubMed]
  124. Rigano, J.; Ng, C.; Nandurkar, H.; Ho, P. Thrombin Generation Estimates the Anticoagulation Effect of Direct Oral Anticoagulants with Significant Interindividual Variability Observed. Blood Coagul. Fibrin. 2018, 29, 148–154. [Google Scholar] [CrossRef] [PubMed]
  125. Mueck, W.; Stampfuss, J.; Kubitza, D.; Becka, M. Clinical Pharmacokinetic and Pharmacodynamic Profile of Rivaroxaban. Clin. Pharmacokinet. 2014, 53, 1–16. [Google Scholar] [CrossRef] [PubMed]
  126. Park, S.H.; Seo, Y.; Park, P.; Kim, K.; Seo, J.Y.; Lee, H.T.; Kwoun, W.; Ahn, J. Evaluation of Global Laboratory Methods and Establishing On-therapy Ranges for Monitoring Apixaban and Rivaroxaban: Experience at a Single Institution. J. Clin. Lab. Anal. 2019, 33, e22869. [Google Scholar] [CrossRef]
  127. Cundiff, D.K. Clinical Evidence for Rebound Hypercoagulability after Discontinuing Oral Anticoagulants for Venous Thromboembolism. Medscape J. Med. 2008, 10, 258. [Google Scholar]
Table 1. Risk factors for recurrent venous thromboembolism (VTE) after stopping anticoagulants [13].
Table 1. Risk factors for recurrent venous thromboembolism (VTE) after stopping anticoagulants [13].
Risk FactorsRisk Ratio
Strong transient risk factor, e.g., surgery and injury vs unprovoked0.2 [9,11]
Minor transient risk factor vs unprovoked0.5 [9,11]
Malignancy vs unprovoked1.5–3 [8,14]
Obesity1.5–2.5 [7,15]
History of recurrent VTE (≥2 episodes)1.5 [16]
Male 1.75 [6,9]
Abnormal D-dimer after unprovoked VTE1.5–2.5 [17]
Hereditary thrombophilia1.2–2.0 [5,18]
Malignancy vs unprovoked1.5–3 [8,14]
Table 2. Clinical prediction models for recurrent VTE.
Table 2. Clinical prediction models for recurrent VTE.
ModelInclusion CriteriaVariablesFindings
HERDOO2 [39]1st unprovoked major VTE
Included provoked by:
  • hormonal therapy
  • long-haul flight,
  • immobility <3 days
  • Gender
  • Age ≥ 65 years
  • D-dimer ≥ 250 µg/L on anticoagulation
  • BMI ≥ 30 kg/m2
  • Features of post-thrombotic syndrome (hyperpigmentation, oedema, redness)
Annualised recurrence risk:
  • Females 0 or 1 factors—1.6%
  • Females ≥ 2 factors—14.1%
  • Males—no low-risk group identified
DASH [40]1st unprovoked major VTE
Included provoked by:
  • Oral hormonal therapy, e.g., OCP/HRT
  • Abnormal post-anticoagulation D-dimer (3–5 weeks post-anticoagulation cessation) (+2)
  • Age ≤ 50 years (+1)
  • Male (+1)
  • Oral hormone use (−2)
Annualised recurrence risk:
  • Score ≤ 1—3.1%
  • Score > 1—9.3%
Vienna [41]1st unprovoked VTE
Included isolated distal DVT
Excluded events provoked by hormonal therapy
  • Gender
  • VTE location: distal DVT, proximal DVT, PE
  • D-dimer value (3 weeks post-anticoagulation cessation)
Nomogram with continuous variables
Annualised recurrence risk:
  • Lowest quartile risk score—1.9%
Updated Vienna [42]1st unprovoked VTE
Included isolated distal DVT
Excluded events provoked by hormonal therapy
  • Gender
  • VTE location: distal DVT, proximal DVT, PE
  • D-dimer value—taken at 3 weeks, 3 months, 9 months, and 15 months after anticoagulation cessation
Nomograms with continuous variables
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Back to TopTop