• Baseline fibrin clot lag time, maximal turbidity, fibrinogen, and CRP levels predicted patency 1 year after iliofemoral DVT.

  • CDT reduced the risk of PTS by fivefold only in patients with high baseline fibrinogen levels.

Abstract

Ultrasound-accelerated catheter–directed thrombolysis (UA-CDT) to improve patency after deep vein thrombosis (DVT) has not conclusively been shown to prevent postthrombotic syndrome (PTS) but might benefit patients who are unlikely to obtain patency with standard treatment. We hypothesized that these patients could be selected based on their fibrin clot properties. To study this, patients with acute iliofemoral DVT from the CAVA (Ultrasound-Accelerated Catheter-Directed Thrombolysis Versus Anticoagulation for the Prevention of Post-thrombotic Syndrome) trial had blood samples taken at inclusion. Fibrin clot properties in plasma were determined by turbidimetric clotting (lag time and maximal turbidity) and lysis assays (time to 50% lysis and lysis rate), permeation assay, and confocal microscopy (fiber density), as well as levels of fibrin clot modifiers fibrinogen and C-reactive protein (CRP). Patency was defined as >90% iliofemoral vein compressibility at 12-month ultrasound. PTS was defined as ≥5 Villalta score at 6 or 12 months. In total, 91 of 152 patients were included, including 43 with additional UA-CDT and 48 with standard treatment. Patients with additional UA-CDT more often obtained patency (55.8 vs 27.1%) Patients who obtained patency had longer lag times and lower maximal turbidity, fibrinogen, and CRP; only maximal turbidity and fibrinogen remained associated when adjusting for treatment, thrombus load, and body mass index. Fibrinogen levels had an optimal cutoff at 4.85 g/L. Low fibrinogen levels best predicted patency. Additional UA-CDT decreased the risk of PTS only in patients with high fibrinogen. Therefore, additional UA-CDT might prevent PTS in selected patients based on routinely measured fibrinogen levels. This study was registered at www.ClinicalTrials.gov as #NCT00970619.

Postthrombotic syndrome (PTS) is the most common complication of deep vein thrombosis (DVT), occurring in 40% to 60% of patients despite adequate anticoagulant and compression-based therapy.1 PTS has an adverse impact on quality of life and productivity.2-4 Patients with iliofemoral DVT are known to have the highest risk of PTS.1 Because absence of venous patency is considered to be a major pathogenic driver of PTS,5 early DVT removal might prevent the onset of PTS.6 However, trials with catheter-directed thrombolysis (CDT) in addition to standard treatment have yielded inconclusive results, because the reduction of PTS was found to be limited and offset by a considerable bleeding risk.7 

In the CaVenT trial, additional CDT in patients with femoral or iliofemoral DVT resulted in a significant reduction of PTS.8,9 Over the years, however, standard treatment for DVT has improved considerably,10 which might have affected the outcome of more recent trials. The Acute Venous Thrombosis: Thrombus Removal with Adjunctive Catheter-Directed Thrombolysis trial in patients with proximal DVT observed no effect of additional CDT on PTS.11 Furthermore, the CAVA trial (Ultrasound-Accelerated Catheter-Directed Thrombolysis Versus Anticoagulation for the Prevention of Post-thrombotic Syndrome) in selected patients with iliofemoral DVT did not find a reduced incidence of PTS after 1 year,12 but there was a 22% absolute risk reduction after a median follow-up of 39 months.13 Moreover, symptom severity was reduced in patients with successfully restored patency by CDT,14 and successful CDT could be predicted by assessing thrombus age using magnetic resonance venography.15 Notably, the CAVA trial used an ultrasound-accelerated (UA) method for CDT (UA-CDT), which was shown ex vivo to improve fibrinolytic agent binding and penetration into the clot,16,17 potentially enhancing CDT.

Altogether, these findings suggest that additional UA-CDT may provide benefits within a certain time window for a selection of patients only. In addition to thrombus age and clinical characteristics, research has revealed that individual patients’ fibrin clot properties are associated with venous patency 18 and PTS.19,20 These associations likely stem from a more lysis-resistant clot composition or reduced endogenous fibrinolysis potential in patients, leading to lower rates of patency and, consequently, increased risk of developing PTS by obstruction-driven factors and its influence on the endothelial and inflammatory environment.20 Because UA-CDT aims to restore patency, we hypothesized this intervention would be most effective in patients with a low potential to obtain clot resolution, independent of administered lytic agents.

In this substudy of the CAVA trial, we assessed how fibrin clot properties at the time of study inclusion related to venous patency after 1 year and can help identify patients who are likely to benefit from additional UA-CDT.

Study design and participants

The CAVA trial was a multicenter, randomized, single-blind, allocation-concealed, parallel-group, superiority trial designed to assess the impact of additional UA-CDT compared with standard treatment on the development of PTS after acute iliofemoral DVT. The primary outcome of this trial was the proportion of patients with PTS at 1 year after DVT diagnosis. PTS was reported 12 using both the original definition21 and the consensus definition of the International Society on Thrombosis and Haemostasis.22 Of the 15 participating Dutch hospital centers, 6 were designated as interventional centers to perform UA-CDT. Patients aged 18 to 85 years with an objectified first-time iliofemoral DVT, maximum symptom duration of 14 days, and life expectancy of >6 months were eligible for participation. Exclusion criteria were preexistent signs of venous insufficiency (clinical etiological anatomical and pathophysiological classification ≥clinical score of 3), history of gastrointestinal bleeding, cerebrovascular accident or central nervous system diseases within 1 year, severe hypertension, active malignancy, increased alanine transaminase levels, renal failure, major surgery within 6 weeks, pregnancy, or impaired mobility as defined in the primary publication.12 All participants gave written informed consent. Details about eligibility criteria and procedures can be found in the study protocol as published previously.12 In this prespecified substudy of clot formation and lysis properties, patients who had baseline blood samples and completed the follow-up period of 1 year were selected.

Blood collection

Venous blood was collected at baseline (ie, study inclusion) and 1 year of follow-up from free-flowing blood of the antecubital vein using citrate (3.2% w/v) polypropylene tubes (Becton Dickinson Vacutainer). Within 30 minutes after collection, blood was processed to acquire platelet-poor plasma. Centrifugation was done for 5 minutes at 2500g (room temperature) and 10 minutes at 10 000g (18°C). Plasma samples were stored at –80°C and measured in 1 batch after study completion.

Laboratory assays

Assays were performed by researchers blinded for clinical data corresponding to the samples.

Turbidity assays

The fibrin clot formation and lysis assays were performed in 384-well plates (Greiner Bio-One, Stroud, United Kingdom) using a Powerwave microplate reader (Bio-Tek, Swindon, United Kingdom), as previously described.23,24 In brief, plasma was diluted to a final concentration of 1:6 in Tris-buffered saline (TBS; 50 mM Tris-base, 150 mM NaCl, and pH 7.4). Clotting was triggered by adding thrombin (final concentration, 0.1 U/mL) and CaCl2 (final concentration, 10 mM) in both assays. Tissue-type plasminogen activator (tPA) was added in the lysis assay at start of the experiment (final concentration, 75 ng/mL). Optical density was measured at a wavelength of 340 nm every 12 seconds for 2 hours in the clot formation assay and for 4 hours in the lysis assay. All samples were analyzed in duplicate. Clot formation was characterized as lag time and maximal turbidity, whereas lysis properties were analyzed using time to 50% lysis and lysis rate.

Confocal microscopy

Fibrin fiber counts as a measure of fibrin clot density was determined using laser scanning confocal microscopy as previously described.25 Plasma dilution and clotting initiation were done as for the turbidity assay but spiked with 50 μg/mL AlexaFluor488-labeled fibrinogen (Thermo Fisher Scientific). Mixtures were immediately transferred to the channel of an uncoated μ-Slide VI 0.4 mm ibidi slide (Thistle Scientific, Uddingston, United Kingdom) and left to clot in a dark humidity chamber for 2 hours. Fibrin clots were imaged using a Zeiss LSM880 inverted microscope with 40× oil immersion objective lens (Carl Zeiss, Oberkochen, Germany). All samples were analyzed in duplicate, and 3 images were taken per clot. Z-stacks (15.75 μM, 21 slices) were combined using maximum intensity projection. Images were analyzed using ImageJ/Fiji software (National Institutes of Health, Bethesda, MD) using an in-house macro.

Permeation assay

Clot permeability was assessed by calculating the permeation coefficient (permeation assay, Darcy constant), which reflects average pore size, as previously described.26,27 In brief, plasma dilution and clotting initiation were done as for the turbidity assay but with a TBS dilution of 1:12. This was immediately transferred to a μ-Slide channel and left to clot, as with confocal microscopy. Next, a plastic syringe was connected to each channel and filled with TBS to a set height of 4 cm. Clots were washed for 30 minutes, after which flow-through of buffer was measured every 15 minutes over 45 minutes and used to calculate the permeation assay. All samples were analyzed in duplicate.

Fibrinogen and CRP levels

Fibrinogen and C-reactive protein (CRP) levels were measured, because these are important fibrin clot modifiers.28 Fibrinogen levels were measured using the Clauss method. CRP levels were measured using nephelometry (Siemens), which was corrected for citrate dilution.

Thrombus load

At baseline, magnetic resonance venography was performed based on a master protocol of the principal trial site, to which other participating hospitals adapted local scanning protocols. Further methodological details can be found in a previous publication.15 Iliac, common femoral, femoral, and popliteal vein segments were examined by compression in the transverse plane. For this analysis, thrombus load was represented by the modified Marder score (ie, <50% patency) with a maximum of 24 points based on the imaging of iliac, common femoral, femoral, and popliteal vein segments.29 Venous angiograms at baseline were used for patients in the additional UA-CDT group who did not receive magnetic resonance venography.14 

Venous patency

After 1 year of follow-up, extended venous duplex ultrasound assessment was performed by trained vascular technologists using a protocol as published previously.12,30 Venous patency was defined as ≥90% compressibility and the presence of blood flow at the iliac, common femoral, and femoral vein segments. For the iliac vein, patency was based on the presence of blood flow alone when compressibility could not be assessed.

PTS

For this analysis, the consensus definition of the International Society on Thrombosis and Haemostasis was used,22 that is, Villalta score ≥5 or venous ulceration at the 6- or 12-month visit, and considered moderate-severe when score ≥10 to allow for comparability with other studies. To provide transparent reporting of the score distribution, mean Villalta scores were also given.

Statistical analysis

First, descriptive statistics were used to summarize clinical characteristics, outcomes, and levels of baseline clot properties and modifiers in both treatment groups. Correlations of properties and modifiers were calculated by Pearson correlation coefficient. Next, levels of baseline clot properties and modifiers were compared between patients with and without patency or (moderate-severe) PTS. All associations were then adjusted by logistic regression for treatment group, thrombus load, and backward selected clinical characteristics; adjusting for clot modifiers was explored. The variability of clot properties explained by clot modifiers was expressed as R2. Subsequently, baseline clot properties and modifiers were evaluated as predictors of patency based on area under the receiver operator curve (AUC), as well as odds ratio (OR) with confidence interval (CI) after applying a cutoff value using Youden index. Finally, the best predictor was selected, and patients were separated into 2 groups based on this predictor, that is, patients with low or high potential to obtain patency. In both groups, proportions of (moderate-severe) PTS were compared by treatment group to evaluate the possible benefit of additional UA-CDT. Furthermore, differences in levels of clot properties from baseline to 1 year follow-up were compared by paired t test or Wilcoxon signed-rank test, as appropriate. Categorical variables were given as number, and continuous variables as median (interquartile range) or mean (standard deviation); differences were compared by χ2 test or Fisher exact test and t test or Mann-Whitney U test, as appropriate. A 2-sided significance level ≤.05 without multiple testing correction was used. Correlation and AUCs were calculated in R (version 4.2.0) using the packages ggcorrplot and pROC.31,32 All other analyses were done in SPSS (version 28).

The CAVA trial was approved by the medical ethics committee of Maastricht University Medical Center (Maastricht, The Netherlands) and is registered at www.ClinicalTrials.gov (identifier: NCT00970619).

Study population

In total, 152 of the 184 enrolled patients started their assigned treatment. Of these patients, 145 completed the 1-year follow-up period, of whom 108 had blood samples available at baseline. Ultrasound assessment of venous patency was unavailable for 17 patients (15.7%). Thus, the study population consisted of 91 patients (Figure 1), including 43 in the additional UA-CDT group and 48 in the standard treatment group. Clinical characteristics, including the baseline thrombus load, were not different between the treatment groups (Table 1).

Figure 1.

Flowchart of study design.

Figure 1.

Flowchart of study design.

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Table 1.

Clinical characteristics at inclusion in both treatment groups

Additional UA-CDT (n = 43)Standard treatment (n = 48)
Age, y   
Median 52.0 (38.0-68.0) 50.5 (38.5-63.5) 
<40 13 (30.2%) 13 (27.1%) 
40-65 17 (39.5%) 26 (54.2%) 
>65 13 (30.2%) 9 (18.8%) 
Sex   
Female 19 (44.2%) 23 (47.8%) 
Male 24 (55.8%) 25 (52.1%) 
Body mass index   
Mean, kg/m2 28.3 (±5.9) 26.6 (±3.9) 
<25.0 kg/m2 12 (27.9%) 20 (41.7%) 
25.0-30.0 kg/m2 21 (48.8%) 19 (39.6%) 
≥30.0 kg/m2 10 (23.3%) 7 (14.6%) 
Unknown 0 (0.0%) 2 (4.2%) 
Unprovoked DVT 22 (51.2%) 27 (56.3%) 
Thrombus location   
Left 26 (60.5%) 33 (68.8%) 
Right 15 (34.9%) 13 (27.1%) 
Bilateral  2 (4.7%) 2 (4.2%) 
Thrombus load, score  18 (8-20) 18 (10-24) 
Symptom duration at inclusion, d 7.0 (3.0-13.0) 7.0 (3.0-10.0) 
Known thrombophilia  1 (2.3%) 4 (8.3%) 
Chronic inflammatory diseases 2 (4.7%) 1 (2.1%) 
Additional UA-CDT (n = 43)Standard treatment (n = 48)
Age, y   
Median 52.0 (38.0-68.0) 50.5 (38.5-63.5) 
<40 13 (30.2%) 13 (27.1%) 
40-65 17 (39.5%) 26 (54.2%) 
>65 13 (30.2%) 9 (18.8%) 
Sex   
Female 19 (44.2%) 23 (47.8%) 
Male 24 (55.8%) 25 (52.1%) 
Body mass index   
Mean, kg/m2 28.3 (±5.9) 26.6 (±3.9) 
<25.0 kg/m2 12 (27.9%) 20 (41.7%) 
25.0-30.0 kg/m2 21 (48.8%) 19 (39.6%) 
≥30.0 kg/m2 10 (23.3%) 7 (14.6%) 
Unknown 0 (0.0%) 2 (4.2%) 
Unprovoked DVT 22 (51.2%) 27 (56.3%) 
Thrombus location   
Left 26 (60.5%) 33 (68.8%) 
Right 15 (34.9%) 13 (27.1%) 
Bilateral  2 (4.7%) 2 (4.2%) 
Thrombus load, score  18 (8-20) 18 (10-24) 
Symptom duration at inclusion, d 7.0 (3.0-13.0) 7.0 (3.0-10.0) 
Known thrombophilia  1 (2.3%) 4 (8.3%) 
Chronic inflammatory diseases 2 (4.7%) 1 (2.1%) 

Values are given as n (%), mean (standard deviation), or median (interquartile range).

Leg with most proximal thrombus localization was considered as the index leg.

Based on venous angiogram for 14 patients of additional UA-CDT group without magnetic resonance venography; missing in 4 of standard treatment group.

All heterozygous factor V Leiden.

Clinical outcomes

After 1 year, the proportion of PTS was 41.9% (18/43) in the additional UA-CDT group and 54.2% (26/48) in the standard treatment group (OR [95% CI], 0.61 [0.27-1.40]); the proportions of moderate-severe PTS were 18.6% vs 33.3% (OR [95% CI], 0.46 [0.17-1.21]), and the mean Villalta scores were 4.0 (±3.0) vs 5.7 (±4.4). Patency was obtained in 40.7% (37/91) of patients, including 55.8% (24/43) in the additional UA-CDT group and 27.1% (13/48) in the standard treatment group (P = .005). Although patency was not significantly associated with PTS (OR [95% CI], 0.71 [0.31-1.64]) or moderate-severe PTS (OR [95% CI], 0.39 [0.14-1.10]), the Villalta score after 1 year was lower in patients who had obtained patency than in those without patency (3.8 [±3.0] vs 5.6 [±4.2]; P = .029).

Baseline clot properties and modifiers

Fibrin clots were not measurable in 12 patients (13.2%), due to concomitant presence of low molecular-weight heparins (LMWH) in the samples of these patients and the relatively low thrombin trigger for the clot structure assays. In the remaining patients (n = 79), no differences were found for turbidimetric clotting and lysis assay properties between the treatment groups (supplemental Table 1). Permeation and fiber density was similar between the groups and was only measured in patients who had blood samples available after 1-year follow-up (67/79 [84.8%]). Baseline fibrinogen and CRP levels also did not differ between the treatment groups (supplemental Table 1).

Lag time showed moderate to weak correlations with maximal turbidity, fibrinogen, and CRP levels (Figure 2). In contrast, maximal turbidity correlated strongly with fibrinogen and CRP levels, which also strongly correlated among each other. Time to 50% lysis showed strong correlation with lysis rate, whereas fiber density moderately correlated with time to 50% lysis and maximal turbidity. Notably, permeation correlated with none of the other properties. Patient reported symptom duration at baseline showed weak correlations with maximal turbidity and lysis rate.

Figure 2.

Correlations between baseline fibrin clot properties. Pearson correlation coefficients are shown and are crossed when statistically insignificant (ie, P > .05). Pairwise complete observations were used for fiber density and permeation.

Figure 2.

Correlations between baseline fibrin clot properties. Pearson correlation coefficients are shown and are crossed when statistically insignificant (ie, P > .05). Pairwise complete observations were used for fiber density and permeation.

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Predictors of patency

Patients who went on to obtain patency on ultrasound assessment after 1 year had longer lag times and lower maximal turbidity at baseline, as well as lower levels of fibrinogen and CRP (Table 2). Levels of lysis properties, permeation, or fiber density did not differ in relation to patency. After associations were adjusted for treatment group, thrombus load, and body mass index, only maximal turbidity and fibrinogen levels remained independently associated with patency (Table 2). Because the last-named variables were highly correlated, maximal turbidity was not adjusted for fibrinogen levels, which was found to explain 58% of its variability (R2 = 0.582), and vice versa.

Table 2.

Baseline fibrin clot properties and modifiers in relation to patency

Patency (n = 29)No patency (n = 50)P valueAdjusted P value
Turbidimetric clotting assay     
Lag time, s 462 (402-513) 384 (335-456) .001 .090 
Maximal turbidity (OD) 0.52 (±0.26) 0.69 (±0.25) .006 .013 
Turbidimetric lysis assay     
Time to 50% lysis, s 1038 (879-1395) 1041 (915-1388) .854 .162 
Lysis rate (% per min) 3.90 (±1.45) 4.07 (±1.75) .658 .801 
Other fibrin clot properties      
Permeation (10–9 cm23.74 (1.66-6.83) 2.75 (1.46-5.55) .289 .172 
Fiber density (n per 100 μm) 11.9 (±2.6) 13.0 (±3.0) .132 .083 
Fibrin clot modifiers     
Fibrinogen, g/L 4.43 (±1.49) 5.50 (±1.51) .003 .011 
CRP, mg/L 10.57 (3.71-24.19) 24.21 (8.34-68.59) .015 .087 
Patency (n = 29)No patency (n = 50)P valueAdjusted P value
Turbidimetric clotting assay     
Lag time, s 462 (402-513) 384 (335-456) .001 .090 
Maximal turbidity (OD) 0.52 (±0.26) 0.69 (±0.25) .006 .013 
Turbidimetric lysis assay     
Time to 50% lysis, s 1038 (879-1395) 1041 (915-1388) .854 .162 
Lysis rate (% per min) 3.90 (±1.45) 4.07 (±1.75) .658 .801 
Other fibrin clot properties      
Permeation (10–9 cm23.74 (1.66-6.83) 2.75 (1.46-5.55) .289 .172 
Fiber density (n per 100 μm) 11.9 (±2.6) 13.0 (±3.0) .132 .083 
Fibrin clot modifiers     
Fibrinogen, g/L 4.43 (±1.49) 5.50 (±1.51) .003 .011 
CRP, mg/L 10.57 (3.71-24.19) 24.21 (8.34-68.59) .015 .087 

Of 91 patients, 12 had unmeasurable fibrin clots, which left 79 patients for analysis. Levels were given as mean (standard deviation) or median (interquartile range). Adjusted P values calculated in multivariable logistic regression model including treatment group, thrombus load, and body mass index. There were no significant interactions with treatment group.

OD, optical density.

Measured in selection of patients (n = 67).

To identify the most suitable predictor of patency, preference was given to clot properties and modifiers with an independent association, that is, maximal turbidity and fibrinogen. Both variables were found to have moderate accuracy to predict patency based on their AUC but a substantially higher OR was observed for low fibrinogen than low maximal turbidity (Figure 3).

Figure 3.

Baseline maximal turbidity and fibrinogen as predictors of patency. Visualizes receiver operator curves with cutoff values determined by Youden index and their corresponding ORs (95% confidence interval). OD, optimal density.

Figure 3.

Baseline maximal turbidity and fibrinogen as predictors of patency. Visualizes receiver operator curves with cutoff values determined by Youden index and their corresponding ORs (95% confidence interval). OD, optimal density.

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Relevance for PTS

Baseline clot properties were not different when directly compared between patients who did or did not develop (moderate-severe) PTS (supplemental Tables 2-3). However, when patients with low potential to obtain patency were selected based on their higher fibrinogen levels, substantially less PTS was observed in the additional UA-CDT group (Table 3). Accordingly, the additional UA-CDT group had numerically less moderate-severe PTS (OR [95% CI], 5.39 [0.99-29.34]) and a significantly lower 1-year Villalta score (3.1 [±2.9]) than the standard treatment group (6.8 [±4.5]; P = .006); no differences were found in the selection of patients with lower fibrinogen levels (supplemental Table 4).

Table 3.

PTS per treatment group separated for baseline fibrinogen level

Fibrinogen levelAdditional UA-CDT (n = 36)Standard treatment (n = 43)OR (95% CI)
<4.85 g/L 50.0% (10/20) 45.0% (9/20) 0.82 (0.24-2.84) 
≥4.85 g/L 25.0% (4/16) 60.9% (14/23) 4.67 (1.14-19.07) 
Fibrinogen levelAdditional UA-CDT (n = 36)Standard treatment (n = 43)OR (95% CI)
<4.85 g/L 50.0% (10/20) 45.0% (9/20) 0.82 (0.24-2.84) 
≥4.85 g/L 25.0% (4/16) 60.9% (14/23) 4.67 (1.14-19.07) 

Proportions were compared using χ2 testing.

CI, confidence interval.

Clot properties after 1 year

Fibrin clot properties in patients after 1 year compared with baseline values showed a pairwise decrease of maximal turbidity (optical density, 0.43 [±0.14] vs 0.63 [±0.26]; P < .001) and a numerical increase of lag time (462 seconds [range, 408-516] vs 408 seconds [range, 354-498]; P = .096), as well as an increase of lysis rate (4.54 [±2.07] vs 4.00 [±1.64] % per minute; P = .014) and a numerical decrease of time to 50% lysis (870 seconds [range, 768-1248] vs 1038 seconds [range, 903-1371]; P = .186). None of these properties after 1 year were associated with either patency or (moderate-severe) PTS (supplemental Tables 5-7).

In this study, we aimed to relate baseline fibrin clot properties with venous patency 1 year after DVT to identify patients who might benefit from additional UA-CDT. Our findings showed that patients who went on to obtain patency had longer lag time and lower maximal turbidity, as well as reduced levels of fibrinogen and CRP. Notably, maximal turbidity emerged as an independent predictor of patency, although 58% of its variability was explained by fibrinogen levels, which proved to be an even better predictor of patency. Subsequently, we showed that additional UA-CDT reduced the incidence of PTS only in patients with a low potential to obtain venous patency, as indicated by elevated fibrinogen levels. Collectively, our results suggest that baseline fibrinogen levels might be used to identify suitable patients for additional UA-CDT.

Our observation regarding lower maximal turbidity in relation to venous patency represents the formation of less dense fibrin clot structures, which are known to be more susceptible to lysis due to their increased accessibility for fibrinolytic proteins and abundant binding sites for tPA and plasminogen.28 Although we did not observe different lysis properties in relation to patency, differences cannot be excluded with certainty because the turbidity assay used may not fully reflect in vivo conditions (eg, role of added tPA concentrations and absence of blood flow).

In the acute-phase setting of our study, maximal turbidity seemed to be largely determined by fibrinogen levels, which were also highly correlated with CRP levels. After 1 year, maximal turbidity had undergone a substantial decrease compared with baseline levels, and it was no longer associated with patency. This transition suggests that its prognostic value is overt in the acute phase but is then lost in the chronic phase because clot formation normalizes at least to some extent.

Associations of fibrin clot properties in relation to patency have previously been reported in a case-control study.18 Using other assays than ours, this study found that patients with patency had an increased clot permeability and lysis rate. Although we did not observe differences in comparable properties, this can be explained by differences in study design, most importantly the chronic setting of blood withdrawal but also the use of different criteria and timing to assess patency. Nevertheless, our findings still point in a similar direction, namely that patients with venous patency form fibrin clots with certain properties that could make them less resistant to lysis. Interestingly, we did not observe direct associations between baseline fibrin clot properties and the onset of PTS. This could be expected because PTS is a heterogenous entity that can develop not only due to obstruction-driven factors but also other mechanisms such as venous reflux and inflammatory processes.5 Accordingly, a cohort study found reduced thrombin generation in relation to patency but not in relation to PTS, despite these outcomes being associated earlier.33 Another cohort study20 as well as a case-control study19 did observe associations of lysis-resistant fibrin clot properties with PTS, which could again be explained by differences in study design, including a chronic setting, more strict definition of PTS, and several exclusion criteria.

Extensive research by others has revealed numerous determinants of fibrin clot formation and lysis, including genetic and acquired factors (reviewed in Zabczyk et al).34 Recently, neutrophil extracellular traps, in particular, have emerged as key players in the acute phase of DVT and were shown to affect clot structure and lysis, making them potential determinant of our turbidity parameters.34 The focus in this study, however, was not on causes of fibrin clot formation and lysis but on its potential diagnostic impact. We recognize the need for further and more extensive studies addressing both mechanistic and diagnostic elements to improve selection of patients who benefit the most from reperfusion therapy.

Our study has some limitations that need to be mentioned. First, this is a substudy, and therefore, it might not have been sufficiently powered for these additional analyses. Second, a substantial number of patients had to be excluded from analysis because of the absence of either the ultrasound assessment or the blood samples, which might have introduced bias because it further deceased our sample size, and we cannot be sure if these missing procedures were selective. Third, fibrin clots could not be formed in some of the blood samples at baseline, due to LMWH use, which is known to affect this assay whereas other anticoagulants do not.26 Most patient in the CAVA trial used vitamin K antagonists (ie, 82%),12 which was always initiated together with LMWH until adequate anticoagulation was reached, and some patients had not yet stopped LMWH at the time of blood withdrawal. Moreover, we did not adjust for multiple testing, which could have resulted in false positive results due to random chance (eg, by within-subgroup comparisons in a small study population), implying that our results require further confirmation. Finally, our study did not register various comorbidities or comedications that might influence fibrin clot properties.

Despite these issues, this substudy’s primary strength lies in its ability to promptly address the clinical relevance of gained pathophysiologic insights, because it uses data of a randomized therapeutic trial. Although these findings require further validation, it provides a promising direction for future research regarding patient selection for additional UA-CDT.

In conclusion, our study suggests that by selecting patients at higher risk of PTS based on their baseline fibrinogen levels, we might be able to have an almost 5 times better outcome with additional UA-CDT. Because fibrinogen is routinely measured in clinical care, its implementation as a criterium to guide treatment in iliofemoral DVT is highly feasible. We encourage future research to validate the use of baseline fibrinogen as a predictor to select patients for additional UA-CDT.

The CAVA trial was funded by a grant from ZonMw (The Netherlands Organisation for Health Research and Development, project number 171101001) and additional funding was provided by the board of the Maastricht University Medical Center. The Robert A.S. Ariens laboratory is funded by the British Heart Foundation (RG/18/11/34036 and PG/23/11184), the Wellcome Trust (204951/B/16/Z), and the Biotechnology and Biological Sciences Research Council (BB/W000237/1). G.A. is supported by a PhD Studentship from the Saudi Arabian Government.

The funders of this study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. Authors involved in analyzing the data (A.F.J.I. and A.J.t.C.-H.) had full access to all of the study data.

Contribution: G.A. performed the laboratory analyses, supervised by R.A.S.A.; A.F.J.I. performed data analysis, supervised by A.J.t.C.-H.; A.J.t.C.-H. and H.t.C. contributed to the trial design, funding, recruitment of patients, and data collection; A.J.t.C.-H., R.A.S.A., and H.t.C. conceived the substudy concept; A.F.J.I. wrote the manuscript, supervised by A.J.t.C.-H.; all other authors contributed equally to review of the manuscript and approved the final manuscript; and A.J.t.C.-H had final responsibility for the decision to submit the manuscript for publication.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

A complete list of the CAVA trial investigators appears in “Appendix.”

Correspondence: Aaron F. J. Iding, Thrombosis Expertise Center, Heart + Vascular Center, Maastricht University Medical Center, P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands; email: a.iding@maastrichtuniversity.nl.

The list of the CAVA (Ultrasound-Accelerated Catheter-Directed Thrombolysis Versus Anticoagulation for the Prevention of Post-thrombotic Syndrome) trial investigators and their affiliations are:

  • André A. E. A. de Smet, Maasstad Hospital, Rotterdam, The Netherlands

  • Lidwine W. Tick, Maxima Medical Centre, Eindhoven, The Netherlands

  • Marlène H. W. van de Poel, Laurentius Hospital, Roermond, The Netherlands

  • Otmar R. M. Wikkeling, Nij Smellinghe Hospital, Drachten, The Netherlands

  • Louis-Jean Vleming, Haga Hospital, The Hague, The Netherlands

  • Ad Koster, VieCuri Medical Centre, Venlo, The Netherlands

  • Kon-Siong G. Jie, Zuyderland Medical Centre, Sittard, The Netherlands

  • Esther M. G. Jacobs, Elkerliek Hospital, Helmond, The Netherlands

  • Harm P. Ebben, Amsterdam University Medical Centre, Amsterdam, The Netherlands

  • Michiel Coppens, Amsterdam University Medical Center, Amsterdam, The Netherlands

  • Cees H. A. Wittens, Maastricht University Medical Centre, Maastricht, The Netherlands and Aachen University Medical Centre, Aachen, Germany; Emeritus professor, retired in September 2019.

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Author notes

A.F.J.I. and G.A. contributed equally to this study.

A.F.J.I. and G.A. are joint first authors.

Deidentified individual participant data are available on request from the corresponding author, Aaron F. J. Iding (a.iding@maastrichtuniversity.nl). The study protocol can be found in the primary publication.

The full-text version of this article contains a data supplement.

Supplemental data