title: Diagnostic algorithm for familial chylomicronemia syndrome.
abstract: BACKGROUND
  Familial chylomicronemia syndrome (FCS) is a rare genetic disease that leads to severe hypertriglyceridemia often associated with recurrent episodes of pancreatitis. The recognition and correct diagnosis of the disease is challenging due to its rarity, and to the lack of specificity of signs and symptoms. Lipid experts, endocrinologists, gastroenterologists, pancreatologists, and general practitioners may encounter patients who potentially have FCS. Therefore, cooperation between experts and improved knowledge of FCS is essential in improving the diagnosis. Currently, a consensus on best practice for the diagnosis of FCS is lacking.
  
  
  METHODS
  Aiming to define a diagnostic algorithm for FCS, a board of European experts was instituted. Such an algorithm for FCS is important to guide practitioners in the diagnosis of suspected FCS and to optimize therapeutic strategies.
  
  
  RESULTS
  The multidisciplinary views were merged, leading to a diagnostic algorithm, proposed here.
  
  
  CONCLUSIONS
  This diagnostic algorithm represents a potentially useful tool to support primary and secondary care practitioners in the recognition of signs and clinical manifestations in individuals potentially affected by FCS.
authors.affiliation: Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands.
authors.forename: Erik
authors.initials: E
authors.lastname: Stroes
authors.affiliation: Fédération d'Endocrinologie Diabétologie Maladies Métaboliques, Nutrition, Hôpital Cardiovasculaire Louis Pradel, Lyon, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Moulin
authors.affiliation: Medizinische Klinik II - Grosshadern, Klinikum der Universität München, Munich, Germany.
authors.forename: Klaus G
authors.initials: KG
authors.lastname: Parhofer
authors.affiliation: Pancreatology Department, INSERM UMR1149, DHU UNITY, Beaujon Hospital, Clichy, France.
authors.forename: Vinciane
authors.initials: V
authors.lastname: Rebours
authors.affiliation: CLINTEC, Karolinska Institutet and Department of Digestive Diseases, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: J-Matthias
authors.initials: JM
authors.lastname: Löhr
authors.affiliation: Centro regionale delle malattie rare del metabolismo dell'adulto (CERMMET) Policlinico "P. Giaccone", Palermo, Italy; Department of Biomedicine, Internal Medicine and Medical Specialties, DI.BI.MIS School of Medicine, University of Palermo, Palermo, Italy. Electronic address: maurizio.averna@unipa.it.
authors.forename: Maurizio
authors.initials: M
authors.lastname: Averna
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D019091:Critical Pathways; D004252:DNA Mutational Analysis; D003661:Decision Support Techniques; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006801:Humans; D008072:Hyperlipoproteinemia Type I / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000628:therapy; D008055:Lipids / Q000097:blood*; D008071:Lipoprotein Lipase / Q000235:genetics*; D009154:Mutation; D010641:Phenotype; D017410:Practice Guidelines as Topic; D011237:Predictive Value of Tests; D011379:Prognosis
chemical_list: D015415:Biomarkers; D005819:Genetic Markers; D008055:Lipids; C548261:LPL protein, human; D008071:Lipoprotein Lipase
keywords: Chylomicrons; Familial chylomicronemia syndrome; Hyperlipoproteinemia; Lipoprotein lipase deficiency; Pancreatitis