0132: Identifying familial hypercholesterolemia from registries of patients with acute myocardial infarction: an algorithm-based approach

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• 作者：Marianne Zeller ; ⁽¹⁾ ; ^{marianne.zeller@u-bourgogne.fr" class="auth_mail" title="E-mail the corresponding author} ; Claude Touzery⁽²⁾ ; Yves Cottin⁽²⁾ ; Michel Farnier⁽³⁾ ; Tabassome Simon⁽⁴⁾ ; Nicolas Danchin⁽⁵⁾
• 刊名：Archives of Cardiovascular Diseases Supplements
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：8
• 期：1
• 页码：19
• 全文大小：50 K

文摘

Familial hypercholesterolemia (FH) is at very high risk of early myocardial infarction (MI). The prevalence of FH, which is estimated to be at least 1:500 in the general population, remains unclear in patients with acute MI. From databases of 2 French regional and nationwide registries of acute MI (RICO and FAST-MI, respectively), we aimed to determine FH prevalence by developing a specific algorithm.

Methods and results

Consecutive patients with AMI ≤48 hours of onset included 1) in FAST-MI: during a one-month period in 213 institutions at the end of 2005 and 2) in RICO: from January 2001 December 2013 (≈13y), were considered in the 2 databases. The algorithm was adapted from Dutch lipid clinic network criteria and was build upon 4 variables (i.e. LDL level and previous use of lipid lowering medications, premature and family history) to identify FH probability. The LDL level was adjusted on each type of lipid lowering medications and the probability of FH was defined taking into account missing data rate. Among the 7484 patients included in the RICO registry, 29.1% had premature vascular disease, 29.7% had familial history, 19.9% were under lipid lowering medications and 9.7% had LDL ≥5mmol/L. FH prevalence was calculated as unlikely (72.6%), possible (24.6%) and probable /definite (2.8%).

Conclusion

Our 4-variables algorithm is relevant to determine FH probability in databases from MI registries. In this large population reflecting routine clinical practice in acute MI, a high prevalence of FH was found, suggesting the opportunity for prevention strategies.