低密度脂蛋白胆固醇水平对心肌梗死后非甾体抗炎药相关心血管风险的影响：基于人群的队列研究

IF 3.4 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Clinical Epidemiology Pub Date : 2024-04-22 DOI:10.2147/clep.s447451

Mohab Basem, Kasper Bonnesen, Lars Pedersen, Henrik Toft Sørensen, Morten Schmidt

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引用次数: 0

摘要

目的：研究低密度脂蛋白胆固醇（LDL-C）水平是否会影响心肌梗死（MI）后使用非阿司匹林类非甾体抗炎药（NSAID）相关的心血管风险：我们利用丹麦健康登记处，对 2010-2020 年间首次心肌梗死且出院前有 LDL-C 值的所有成年患者进行了一项基于人群的队列研究。根据最新的 LDL-C 值，我们将患者分为低 LDL-C 组和高 LDL-C 组（< 3.0 vs ≥ 3.0 mmol/L）。我们使用时变 Cox 回归计算了使用非甾体抗炎药与主要不良心血管事件（MACE：复发性心肌梗死、缺血性中风和全因死亡）之间的危险比（HRs）及 95% 的置信区间：我们对 50,573 名患者进行了中位数为 3.1 年的随访。在暴露期间，521 名患者发生了 MACE：低 LDL-C 组 312 人，高 LDL-C 组 209 人。使用非甾体抗炎药与不使用非甾体抗炎药相比，总体MACE的HR为1.21（1.11-1.32），低LDL-C组为1.19（1.06-1.33），高LDL-C组为1.23（1.07-1.41）。各低密度脂蛋白胆固醇亚组的复发性心肌梗死和缺血性中风的 HR 值相当。低 LDL-C 组的全因死亡 HR 值为 1.22（1.07- 1.39），高 LDL-C 组为 1.54（1.30- 1.83）。将低密度脂蛋白胆固醇的临界值改为 1.8 和 1.4 mmol/L，结果显示一致：结论：在心肌梗死患者中，低密度脂蛋白胆固醇水平不会影响使用非甾体抗炎药导致的MACE风险增加，但可能会影响使用非甾体抗炎药与全因死亡之间的关系。关键词：心血管疾病、非甾体类抗炎药、胆固醇、低密度脂蛋白胆固醇、心肌梗死、效应修饰

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Influence of Low-Density Lipoprotein Cholesterol Levels on NSAID-Associated Cardiovascular Risks After Myocardial Infarction: A Population-Based Cohort Study

Aim: To examine whether low-density lipoprotein cholesterol (LDL-C) levels influence the cardiovascular risk associated with non-aspirin non-steroidal anti-inflammatory drug (NSAID) use after myocardial infarction (MI).
Methods: Using Danish health registries, we conducted a population-based cohort study of all adult patients with first-time MI during 2010– 2020 with an LDL-C value before discharge. Based on the latest LDL-C value, we categorized patients into a low and a high LDL-C group (< 3.0 vs ≥ 3.0 mmol/L). We used time varying Cox regression to compute hazard ratios (HRs) with 95% confidence intervals of the association between NSAID use and a major adverse cardiovascular event (MACE: recurrent MI, ischemic stroke, and all-cause death).
Results: We followed 50,573 patients for a median of 3.1 years. While exposed, 521 patients experienced a MACE: 312 in the low LDL-C group and 209 in the high LDL-C group. The HRs for MACE comparing NSAID use with non-use were 1.21 (1.11– 1.32) overall, 1.19 (1.06– 1.33) in the low LDL-C group, and 1.23 (1.07– 1.41) in the high LDL-group. The HRs for recurrent MI and ischemic stroke were comparable between the LDL-C subgroups. The HRs for all-cause death were 1.22 (1.07– 1.39) in the low LDL-C group and 1.54 (1.30– 1.83) in the high LDL-C group. Changing the cut-off value for LDL-C to 1.8 and 1.4 mmol/L showed consistent results.
Conclusion: In patients with MI, LDL-C levels did not influence the increased risk of MACE associated with NSAID use, but might influence the association between NSAID use and all-cause death.

Keywords: cardiovascular disease, non-steroidal anti-inflammatory drugs, cholesterol, low-density lipoprotein cholesterol, myocardial infarction, effect modification

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来源期刊

Clinical Epidemiology Medicine-Epidemiology

CiteScore

6.30

自引率

5.10%

发文量

169

审稿时长

16 weeks

期刊介绍： Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.