Arrobas Velilla T, Bonet Estruch E, Roa Garrido J, Romero Jiménez M, Varo Sánchez GM, Vázquez Rico I. Incorporation of biochemical parameters and diagnostic algorithms in the laboratory computer system for the early detection of lipid abnormalities from the lipid units.
Clin Investig Arterioscler 2021;
33:273-281. [PMID:
33820672 DOI:
10.1016/j.arteri.2021.01.001]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 12/28/2020] [Accepted: 01/14/2021] [Indexed: 06/12/2023]
Abstract
INTRODUCTION
The combination of biochemical markers, together with the design and implementation of diagnostic algorithms in laboratory computer systems could become very powerful tools in the stratification of cardiovascular risk.
OBJECTIVES
To implement new biochemical markers and diagnostic algorithms not yet available, in order to provide an estimation of cardiovascular risk and the diagnostic orientation of lipid alterations.
MATERIAL AND METHODS
Study of the implementation of apolipoprotein B and lipoprotein (a), as well as the inclusion of different diagnostic algorithms. This was carried out jointly by the different Lipid Units of the Spanish Society of Atherosclerosis, Hospital Virgen Macarena in Seville, Hospital Juan Ramón Jiménez, Hospital Infanta Elena, and Hospital de Río Tinto during 2018 and 2019.
RESULTS
The 4diagnostic algorithms entered into the Laboratory Information System, showed a total of 9,985 patients with c-LDL>200mg/dl. The diagnostic algorithm was extended to include Apo B, with 8,182 determinations showing an apolipoprotein B>100mg/dl). A total of 747 lipoprotein (a) were determined, of which 30.65% were> 50mg/dl. More than 2/3 (71.80%) showed results compatible with small and dense LDL particles.
CONCLUSIONS
The implementation of new analytical parameters and algorithms in Primary Care laboratory results can identify a considerable number of patients with different alterations in lipid metabolism. This, together with the classic risk factors, could contribute to a correct risk stratification in preventing the progression of cardiovascular disease.
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