A new risk prediction tool can identify patients at high risk of serious blood clots who might need preventive treatment, says a study published on bmj.com.
The tool is based on simple variables which the patient is likely to know and could be easily integrated into GP computer systems to assess patients' risk before hospital admission, long-haul flights, or starting medications that carry an increased clotting risk.
Venous thromboembolism is a common, potentially lethal disease which can be prevented. In England alone, it claims over 25,000 lives each year and, of those who survive, almost a third experience long-term effects.
In 2010, the National Institute for Health and Clinical Excellence (NICE) issued guidance to encourage the identification of high-risk patients and effective use of preventive measures. Yet there are no validated risk prevention algorithms suitable for use in primary care.
The data show that the risk of venous thromboembolism in both men and women increased with increasing age, body mass index and quantity of cigarettes smoked each day. Risks were also elevated among those with varicose veins, congestive heart failure, chronic kidney disease, chronic lung disease, inflammatory bowel disease, and any cancer.
Admission to hospital in the last six months also conferred a greater risk, as did taking antipsychotic drugs, oral contraceptives, HRT or tamoxifen.
The authors conclude: "We have developed and validated a new risk prediction model which identifies patients at high risk of venous thromboembolism. The algorithm is based on simple clinical variables which the patient is likely to know or which are routinely recorded in GP computer systems.
"The algorithm could be integrated into GP computer systems and used to risk assess patients prior to hospital admission or before the initiation of medication which might increase risk of venous thromboembolism."