London, United Kingdom (CU)_ Queen Mary University researchers from London used an innovative algorithm on 700,000 patient records in east London to check whether the data collected regularly by the general practitioners can uncover incidences of Familial Hypercholesterolemia, which is a key reason for heart attack in young people.
Familial hypercholesterolemia (FH) is a hereditary disorder that causes abnormally high cholesterol levels in the blood and is handed down via families. It can result in a heart attack at an early age if not treated on time. The report says that approximately 320,000 individuals in the United Kingdom are affected by FH and most of whom are completely unaware of their condition.
The FAMCAT – Familial Hypercholesterolemia Case Assertation Tool is one technique of detecting FH, which evaluates data from GP records, such as blood test results and family history, to estimate who is more prone to have FH. The outcome of the test was a large list of patients, whom the GPs can call in for additional inquiry. It was the first time that FAMCAT has been applied to data from a large, ethnically diverse population in an inner-city setting.
Reader in Primary Care at Queen Mary University of London, Dr John Robson, explained about the benefits of using the FAMCAT algorithm. He said, “There is an urgent need for better methods to detect people who might have FH. We have demonstrated the FAMCAT algorithm can be applied to whole boroughs or cities, using the data we already have in the system to help find those undiagnosed cases. But FAMCAT generates a very long list of possible candidates, and this needs to be assessed for cost-effectiveness. For every confirmed case of FH, FAMCAT found 119 likely candidates all needing investigation – first by the GP, with a detailed family history and examination, then in secondary care for genetic testing and advice. It is also unclear whether the algorithm performs equally well at detecting FH in different ethnic groups. We are now planning further research with east London data to investigate this.”
