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GP researchers develop DVT prediction tool

Researchers have used UK general practice data to develop a new risk score to identity patients at high risk of perioperative blood clots, and flag up those potentially at risk from the contraceptive pill or long-haul flights.

The new clinical risk prediction model, QThrombosis, can be used to identify those in need of preventative treatment, say the researchers, and is the first risk prevention algorithm to be validated for use in primary care. Click here to access QThrombosis.

The tool is likely to help implement NICE guidance on the prevention of venous thromboembolism issued last year.

Researchers collected data from 564 general practices in England and Wales from patients aged 25-84 years, with no record of pregnancy in the preceding 12 months, previous VTE, and no oral anticoagulation.

They collected data on simple clinical variables routinely recorded in general practice records, such as smoking status, BMI, previous hospital admission, and current prescriptions.

The algorithm calculated cut-offs to define the top 0.5%, 1%, 5%, and 10% for absolute risk of VTE based on the estimated risks at one and five years in a cohort of men and women combined, and the total number of patients that would fall into each group based on the one and five year risk.

For example, the 90th centile defined a high risk group with a five year risk score of more than 15 per 1,000. There were 2441 new cases of VTE within this group over five years, which accounted for 35% of all new cases of VTE.

The 99th centile defined a high risk group with a five year risk score of more than 38 per 1,000, and there were 350 new cases of VTE in this group over five years.

Lead author Professor Julia Hippisley-Cox, a GP in Nottingham and professor of clinical epidemiology and general practice at the University of Nottingham, said the algorithm could be easily integrated into general practice clinical computer systems.

She said: ‘It could be used to identify patients at increased risk of VTE on or before hospital admission or before long haul flights, so that prophylaxis can be considered in a more systematic way.'

‘The algorithm could be used when considering medication which might increase VTE risk. For example, a woman might be interested to know her absolute level of risk and how it might change with medication, and this risk can be assessed against the expected benefits of the medication.'

‘Thirdly, the algorithm could be used to identify high risk groups of patients suitable for further testing, closer monitoring, or preventative treatment.'

She told Pulse: ‘QThrombosis provides a systematic risk assessment using routinely collected data which can then be used to identify patients at risk of thrombosis. It's too early to say what the impact might be but the intention is to better identify at-risk patients for intervention.'

BMJ 2011, published online 16 August


Clinical example

A 39 year old woman, who is a heavy smoker, has a body mass index of 36.7 and a history of varicose veins, and is currently taking the oral contraceptive pill. She has a one year thrombosis risk of 0.2% and a five year risk of 1.1%. A similar woman not currently prescribed the oral contraceptive pill has a one year risk of 0.15% and a five year risk of 0.9%.

Click here to access QThrombosis.