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Comparison of a Machine Learning Method and Various Equations for Estimating Low-Density Lipoprotein Cholesterol in Korean Populations

Authors
 Yu-Jin Kwon  ;  Hyangkyu Lee  ;  Su Jung Baik  ;  Hyuk-Jae Chang  ;  Ji-Won Lee 
Citation
 FRONTIERS IN CARDIOVASCULAR MEDICINE, Vol.9 : 824574, 2022-02 
Journal Title
FRONTIERS IN CARDIOVASCULAR MEDICINE
Issue Date
2022-02
Keywords
Korean ; cardiovascular disease ; deep neural network ; low-density lipoprotein ; pooled cohort equation
Abstract
Background: LDL-C is the primary target of lipid-lowering therapy and used to classify patients by cardiovascular disease risk. We aimed to develop a deep neural network (DNN) model to estimate LDL-C levels and compare its performance with that of previous LDL-C estimation equations using two large independent datasets of Korean populations.

Methods: The final analysis included participants from two independent population-based cohorts: 129,930 from the Gangnam Severance Health Check-up (GSHC) and 46,470 participants from the Korean Initiatives on Coronary Artery Calcification registry (KOICA). The DNN model was derived from the GSHC dataset and validated in the KOICA dataset. We measured our proposed model's performance according to bias, root mean-square error (RMSE), proportion (P)10-P20, and concordance. P was defined as the percentage of patients whose LDL was within ±10-20% of the measured LDL. We further determined the RMSE scores of each LDL equation according to Pooled cohort equation intervals.

Results: Our DNN method has lower bias and root mean-square error than Friedewald's, Martin's, and NIH equations, showing a high agreement with LDL-C measured by homogenous assay. The DNN method offers more precise LDL estimation in all pooled cohort equation strata.

Conclusion: This method may be particularly helpful for managing a patient's cholesterol levels based on their atherosclerotic cardiovascular disease risk.
Files in This Item:
T202200590.pdf Download
DOI
10.3389/fcvm.2022.824574
Appears in Collections:
6. Others (기타) > Gangnam Severance Hospital Health Promotion Center(강남세브란스병원 체크업) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Family Medicine (가정의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
3. College of Nursing (간호대학) > Dept. of Nursing (간호학과) > 1. Journal Papers
Yonsei Authors
Kwon, Yu-Jin(권유진) ORCID logo https://orcid.org/0000-0002-9021-3856
Baik, Su Jung(백수정) ORCID logo https://orcid.org/0000-0002-3790-7701
Lee, Ji Won(이지원) ORCID logo https://orcid.org/0000-0002-2666-4249
Lee, Hyang Kyu(이향규) ORCID logo https://orcid.org/0000-0002-0821-6020
Chang, Hyuk-Jae(장혁재) ORCID logo https://orcid.org/0000-0002-6139-7545
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/188080
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