Lipids module 3: clinical diagnosis of dyslipidaemia

Released 14 June 2024     Expires: 14 June 2026      Programme: Lipids 1 CPD/CME credit

Sponsorship Statement: Novartis Pharmaceuticals UK Ltd has provided OmniaMed Communications Ltd with an arm’s length sponsorship towards the update of the BJC e-learning programme in lipids

Designed to give healthcare professionals an understanding of the diagnosis of dyslipidaemias and lipid profiling in cardiovascular risk assessment.

Module first published 9 July 2015
Module first revised 17 March 2021
Second revision June 2024

Learning objectives

After completing this module, participants should be better able to:

  • Review key genetic and secondary causes of dyslipidaemia
  • Use clinical findings and abnormalities of the lipid profile to identify and diagnose patients with dyslipidaemia
  • Understand components of the lipid profile and how they are measured and calculated
  • Recognise the role of lipid profiling in cardiovascular risk assessment including measurement of lipoprotein(a).

Faculty

2024 revision:
Dr Saleem Ansari, Specialist Registrar in Chemical Pathology and Metabolic Medicine; and Lipids and Cardiovascular Risk Service, Department of Cardiology, Hammersmith Hospital, Imperial College Healthcare NHS Trust
Dr Jaimini Cegla, Consultant in Chemical Pathology and Metabolic Medicine; and Lipids and Cardiovascular Risk Service, Department of Cardiology, Hammersmith Hospital, Imperial College Healthcare NHS Trust
Programme editor: Dr Dermot Neely, Heart UK Trustee and Adviser

2021 revision:
Dr Mariana Abdel Malek, Specialist Registrar, Imperial College Healthcare NHS Trust
Dr Jaimini Cegla, Consultant in Chemical Pathology and Metabolic Medicine, Imperial College Healthcare NHS Trust
Programme editor: Dr Dermot Neely

Original module:
Dr Dermot Neely
Dr David Thompson, Clinical Research Fellow, International Centre for Circulatory Health, Imperial College London

Accreditation

1 CPD/CME credit, 1.0 hour
BJC Learning has assigned one hour of CPD/CME credit to this module

Endorsed by:

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