Evidence map›Paper›PMID 40026511›Full record

ArticleReviews in cardiovascular medicine2025

Which Parameter Related to Low-Density Lipoprotein Cholesterol is Superior for Predicting the Recurrence of Myocardial Infarction in Young Patients with Previous Coronary Heart Disease? A Real-World Study.

Feng Xu, Hao-Ran Xing, Hong-Xia Yang, Jin-Wen Wang, Xian-Tao Song, Hui-Juan Zuo

Abstract read
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Article in Reviews in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Feng XuDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Hao-Ran XingDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.ORCID https://orcid.org/0000-0001-9436-3993
Hong-Xia YangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Jin-Wen WangDepartment of Community Health Research, Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.
Xian-Tao SongDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.ORCID https://orcid.org/0000-0002-9176-1985
Hui-Juan ZuoDepartment of Community Health Research, Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China.ORCID https://orcid.org/0000-0001-6899-1988

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lowering low-density lipoprotein cholesterol (LDL-C) is a well-established strategy for the secondary prevention of coronary heart disease (CHD). However, the effectiveness of specific LDL-C parameters in predicting myocardial infarction (MI) recurrence in real-world settings remains inadequately explored. This study aims to examine the relationship between MI recurrence and various LDL-C parameters in young CHD patients. Methods: This retrospective cohort study involved 1013 patients aged 18-44 at the time of initial CHD diagnosis, collected from the cardiology department clinics at Beijing Anzhen Hospital between October 2022 and October 2023. LDL-C levels were assessed at the time of CHD diagnosis and at the final follow-up. The primary outcome was MI events, analyzed using survival analysis and logistic regression models to determine associations with LDL-C parameters. Results: The study included 1013 patients (mean age: 38.5 ± 3.9 years; 94.7% men), with a median follow-up time of 1.7 years. Initially, 13.6% had LDL-C levels <1.8 mmol/L, which increased to 37.8% by the study's end. During follow-up, 96 patients (9.5%) experienced MI. While LDL-C <1.8 mmol/L at baseline showed a slightly lower cumulative incidence of MI than LDL-C ≥1.8 mmol/L, the difference was not statistically significant (log-rank Conclusions: This study suggests that the most important parameter related to LDL-C for predicting the recurrence of MI in young patients with a history of CHD is the ideal target LDL-C level. Lowering LDL-C to <1.4 mmol/L could potentially reduce MI risk, regardless of baseline LDL-C levels.

Indexed as

coronary heart diseaseLDL cholesterolmyocardial infarctionsecondary prevention

Identifiers

PMID40026511
PMCPMC11868898

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.