Manuela Casula1, Elena Olmastroni1, Angela Pirillo2, Alberico Luigi Catapano3. 1. Epidemiology and Preventive Pharmacology Centre (SEFAP), Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy; Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy. 2. Center for the Study of Atherosclerosis, E. Bassini Hospital, Cinisello Balsamo, Milan, Italy; IRCCS MultiMedica, Sesto S. Giovanni, Milan, Italy. 3. Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy; IRCCS MultiMedica, Sesto S. Giovanni, Milan, Italy. Electronic address: alberico.catapano@unimi.it.
Abstract
BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is an inherited disorder characterized by high levels of blood cholesterol from birth and premature coronary heart disease. Thus, the identification of FH patients is crucial to prevent or delay the onset of cardiovascular events, and the availability of a tool helping with the diagnosis in the setting of general medicine is essential to improve FH patient identification. METHODS: This study evaluated the performance of the Dutch Lipid Clinic Network (DLCN) score in FH patients enrolled in the LIPIGEN study, an Italian integrated network aimed at improving the identification of patients with genetic dyslipidaemias, including FH. RESULTS: The DLCN score was applied on a sample of 1377 adults (mean age 42.9 ± 14.2 years) with genetic diagnosis of FH, resulting in 28.5% of the sample classified as probable FH and 37.9% as classified definite FH. Among these subjects, 43.4% had at least one missing data out of 8, and about 10.0% had 4 missing data or more. When analyzed based on the type of missing data, a higher percentage of subjects with at least 1 missing data in the clinical history or physical examination was classified as possible FH (DLCN score 3-5). We also found that using real or estimated pre-treatment LDL-C levels may significantly modify the DLCN score. CONCLUSIONS: Although the DLCN score is a useful tool for physicians in the diagnosis of FH, it may be limited by the complexity to retrieve all the essential information, suggesting a crucial role of the clinical judgement in the identification of FH subjects.
BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is an inherited disorder characterized by high levels of blood cholesterol from birth and premature coronary heart disease. Thus, the identification of FHpatients is crucial to prevent or delay the onset of cardiovascular events, and the availability of a tool helping with the diagnosis in the setting of general medicine is essential to improve FHpatient identification. METHODS: This study evaluated the performance of the Dutch Lipid Clinic Network (DLCN) score in FHpatients enrolled in the LIPIGEN study, an Italian integrated network aimed at improving the identification of patients with genetic dyslipidaemias, including FH. RESULTS: The DLCN score was applied on a sample of 1377 adults (mean age 42.9 ± 14.2 years) with genetic diagnosis of FH, resulting in 28.5% of the sample classified as probable FH and 37.9% as classified definite FH. Among these subjects, 43.4% had at least one missing data out of 8, and about 10.0% had 4 missing data or more. When analyzed based on the type of missing data, a higher percentage of subjects with at least 1 missing data in the clinical history or physical examination was classified as possible FH (DLCN score 3-5). We also found that using real or estimated pre-treatment LDL-C levels may significantly modify the DLCN score. CONCLUSIONS: Although the DLCN score is a useful tool for physicians in the diagnosis of FH, it may be limited by the complexity to retrieve all the essential information, suggesting a crucial role of the clinical judgement in the identification of FH subjects.
Authors: Francesco Baratta; Daniele Pastori; Domenico Ferro; Giovanna Carluccio; Giulia Tozzi; Francesco Angelico; Francesco Violi; Maria Del Ben Journal: World J Gastroenterol Date: 2019-08-14 Impact factor: 5.742
Authors: Cristina Pederiva; Maria Elena Capra; Claudia Viggiano; Valentina Rovelli; Giuseppe Banderali; Giacomo Biasucci Journal: Life (Basel) Date: 2021-04-14
Authors: Roberto Scicali; Giorgio Ivan Russo; Marina Di Mauro; Flavia Manuele; Grazia Di Marco; Antonino Di Pino; Viviana Ferrara; Agata Maria Rabuazzo; Salvatore Piro; Giuseppe Morgia; Francesco Purrello Journal: J Clin Med Date: 2020-11-08 Impact factor: 4.241