女性急性心肌梗死后高强度降脂治疗处方不足的预后影响。

IF 8.4 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS European journal of preventive cardiology Pub Date : 2024-11-11 DOI:10.1093/eurjpc/zwae255
Orianne Weizman, Marie Hauguel-Moreau, Victoria Tea, Franck Albert, Paul Barragan, Jean-Louis Georges, Nicolas Delarche, Mathieu Kerneis, Vincent Bataille, Elodie Drouet, Etienne Puymirat, Jean Ferrières, François Schiele, Tabassome Simon, Nicolas Danchin
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引用次数: 0

摘要

目的:女性在急性心肌梗死(AMI)后接受降脂治疗(LLT)的可能性较低。我们分析了这种用药不足的情况目前是否依然存在,以及是否会对长期预后产生影响:FAST-MI计划由全国范围内的登记处组成,包括2005年、2010年和2015年所有因急性心肌梗死入院的患者,患者发病时间均在1个月内,且发病时间不超过48小时,并进行了长期随访。本分析主要针对女性和男性的高强度 LLT(阿托伐他汀≥ 40 毫克或同等剂量,或他汀和依折麦布的任意组合)。在12 659名患者中,女性占28%(N=3547)。出院时,女性的高强度LLT处方明显较少[54%对男性的68%,P<0.001,调整后的几率比(OR)为0.78(95%置信区间(CI)为0.71-0.87)],这一趋势并未随着时间的推移而改善:2005年,25%对35%(P=0.14);2010年,66%对79%(P<0.001);2015年,67%对79.5%(P=0.001)。相比之下,女性性别与出院时未接受其他推荐治疗无关:β-受体阻滞剂[调整后 OR 0.98(95% CI 0.88-1.10),P = 0.78]或肾素-血管紧张素阻滞剂[调整后 OR 0.94(95% CI 0.85-1.03),P = 0.18]。出院时进行高强度 LLT 与女性患者 5 年生存率、无梗死和无卒中生存率的改善显著相关[调整后危险比 (HR) 分别为 0.74(95% CI 0.64-0.86),P < 0.001;调整后危险比:0.81(95% CI:0.74-0.89);P < 0.001]。通过倾向得分匹配分析也发现了类似的结果[接受高强度LLT治疗的女性5年生存率:0.82(95% CI 0.70-0.98),P = 0.03]:女性在急性心肌梗死后处方高强度 LLT 时存在偏差,这种偏差在 2005 年至 2015 年间并未减少,可能会对生存率和心血管事件风险造成影响。
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Prognostic impact of high-intensity lipid-lowering therapy under-prescription after acute myocardial infarction in women.

Aims: Women are less likely to receive lipid-lowering therapy (LLT) after acute myocardial infarction (AMI). We analysed whether this under-prescription currently persists and has an impact on long-term outcomes.

Methods and results: The FAST-MI programme consists of nationwide registries including all patients admitted for AMI ≤ 48 h from onset over a 1 month period in 2005, 2010, and 2015, with long-term follow-up. This analysis focused on high-intensity LLT (atorvastatin ≥ 40 mg or equivalent, or any combination of statin and ezetimibe) in women and men. Women accounted for 28% (N = 3547) of the 12 659 patients. At discharge, high-intensity LLT was significantly less prescribed in women [54 vs. 68% in men, P < 0.001, adjusted odds ratio (OR) 0.78(95% confidence interval (CI) 0.71-0.87)], a trend that did not improve over time: 2005, 25 vs. 35% (P = 0.14); 2010, 66 vs. 79% (P < 0.001); 2015, 67 vs. 79.5% (P = 0.001). In contrast, female sex was not associated with a lack of other recommended treatments at discharge: beta-blockers [adjusted OR 0.98(95% CI 0.88-1.10), P = 0.78], or renin-angiotensin blockers [adjusted OR 0.94(95% CI 0.85-1.03), P = 0.18]. High-intensity LLT at discharge was significantly associated with improved 5 year survival and infarct- and stroke-free survival in women [adjusted hazard ratios (HR) 0.74(95% CI 0.64-0.86), P < 0.001 and adjusted HR: 0.81(95% CI: 0.74-0.89); P < 0.001, respectively]. Similar results were found using a propensity score-matched analysis [HR for 5 year survival in women with high-intensity LLT: 0.82(95% CI 0.70-0.98), P = 0.03].

Conclusion: Women suffer from a bias regarding the prescription of high-intensity LLT after AMI, which did not attenuate between 2005 and 2015, with potential consequences on both survival and risk of cardiovascular events.

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来源期刊
European journal of preventive cardiology
European journal of preventive cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
12.50
自引率
12.00%
发文量
601
审稿时长
3-8 weeks
期刊介绍: European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.
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