Hiding in plain sight: supporting primary care to find familial hypercholesterolaemia and save lives.

Familial hypercholesterolaemia (FH) is a relatively common genetic disorder, with affected individuals exhibiting a lifelong elevation of plasma low-density lipoprotein (LDL) cholesterol and a marked tendency to premature atherosclerosis and early-onset cardiovascular disease (CVD). However, unlike most genetic disorders, FH is wholly treatable, especially following the widespread availability of potent lipid-lowering agents such as statins. Indeed, early and sustained therapy to lower LDL cholesterol can normalise this risk and prevent premature CVD. With such enormous potential to prevent premature CVD, it is surprising then that only 7% of patients with FH are believed to have been identified in the UK. The picture is similar in many countries. In England, the NHS Long Term Plan has recently prioritised finding more of these undiagnosed patients and offering them treatment.1 Yet, the task of finding these people and their families, many of whom may be otherwise well, is enormously challenging for a multitude of reasons, one of which is lack of awareness of the diagnosis. The situation could be improved by supporting primary care to identify those with high cholesterol levels and clinical features of FH, offering them an evaluation to confirm diagnosis before moving on to find their relatives, half of whom may carry the same mutation. Brett et al in their study have shown that by simply using the current infrastructure of general practice, those affected by this condition can be successfully identified and treated.2 The primary care electronic health record (EHR) is of course the key game changer, enabling swift identification of people in whom the diagnosis may be likely. Several variations to the approach of using EHR to identify FH cases have been described as shown in figure 1. Options include systematically searching the records using established diagnostic criteria, such as Dutch Lipid Clinic Network (DLCN) …