Background:
In patients with a superficial venous thrombosis (SVT) a blood clot is present in a superficial vein. Patients with this condition experience pain, swelling and redness of the affected vein. Often, SVT only leads to a short period of inconvenience as it resolves naturally with the application of cold bandages and pain killers. The condition is often managed in primary care. In a subset of patients however, the SVT blood clot can grow and spread loose towards the deeper venous system, leading to deep vein thrombosis (DVT) or even embolize leading to pulmonary embolism (PE). Other patients may experience prolonged painful symptoms or recurrent SVT. It is important to treat these subgroups of SVT patients in time as notably DVT and PE can lead to serious complications, including death by PE. Unfortunately, doctors currently do not know precisely which patients are at high risk of developing these complications.
Purpose of the study:
The aim of this study is to predict which primary care patients with SVT are at risk of developing deep venous thrombosis and/or pulmonary embolism, prolonged painful symptoms or recurrent SVT.
Potential importance of the findings:
A simple tool will be developed for the primary care physician and their patients to estimate the risk of complications in primary care SVT patients. This will improve tailored treatment decision making and will better prevent severe SVT complications.
Aim and objectives:
Superficial venous thrombosis (SVT) is considered a benign thrombotic condition in most patients. However, it also can cause serious complications, such as clot progression to deep venous thrombosis (DVT) and pulmonary embolism (PE). This study aims to predict the risk of serious complications for SVT patients presenting in primary care settings.
Primary exposures:
Adult patients diagnosed with SVT presenting in primary care will be included for this study. Selection of SVT cases will be based on a combination of Read and/or Snowmed coding.
Outcomes:
Three prognostic prediction models will be developed and externally validated for relevant SVT clinical outcomes: (i) for prolonged (painful) symptoms within 14 days since SVT diagnosis, (ii) for clot progression to DVT or PE within 45 days, and (iii) for clot recurrence within 12 months.
Study design:
This is a prognostic cohort study using routinely collected primary care data.
Methods:
Data will be used from four primary care routine healthcare registries from both the Netherlands and the UK; the UK CPRD Aurum database will be used for the development of the prediction models and the remaining three will be used as external validation cohorts. Predictors considered are sex, age, Body Mass Index, clinical SVT characteristics, and co-morbidities including: (history of any) cardiovascular disease, diabetes, autoimmune disease, malignancy, thrombophilia, pregnancy or puerperium and presence of varicose veins. Linking to Hospital Episode Statistics (HES),and Pregnancy Register, will be used to collect relevant information on outcomes and pregnancy. The prediction models will be developed using multivariable logistic regression analysis techniques for model i and ii and for model iii a Cox proportional hazards model will be used. They will be validated by internal-external cross-validation as well as external validation.
This study focusses on complicated disease trajectories of SVT in primary care, including:
- Prolonged symptoms within 14 days after SVT diagnosis: prolonged painful symptoms and/or extension of the SVT clot to the saphenofemoral junction (SFJ)
- Clot progression to DVT and/or PE within 45 days
- Recurrent SVT within 12 months
Patrick Souverein - Chief Investigator - Utrecht University
Patrick Souverein - Corresponding Applicant - Utrecht University
Florien van Royen - Collaborator - University Medical Centre Utrecht
Frans Rutten - Collaborator - University Medical Centre Utrecht
Geert-Jan Geersing - Collaborator - University Medical Centre Utrecht
Karel Moons - Collaborator - University Medical Centre Utrecht
Maarten van Smeden - Collaborator - University Medical Centre Utrecht
Sander van Doorn - Collaborator - University Medical Centre Utrecht
HES Admitted Patient Care;HES Outpatient;CPRD Aurum Pregnancy Register