Suppr超能文献

改善心血管风险分层:腹型肥胖在预测主要不良心血管事件中的作用。

Improving cardiovascular risk stratification: the role of abdominal obesity in predicting MACEs.

作者信息

De Matteis Carlo, Petruzzelli Stefano, Graziano Giusi, Novielli Fabio, Di Buduo Ersilia, Cantatore Salvatore, Berardi Elsa, Antonica Gianfranco, Arconzo Maria, Cariello Marica, Florio Marilina, Crudele Lucilla, Moschetta Antonio

机构信息

Department of Interdisciplinary Medicine, University of Bari "Aldo Moro", Bari, 70124, Italy.

Center for Outcomes Research and Clinical Epidemiology (CORESEARCH), Pescara, 65124, Italy.

出版信息

Cardiovasc Diabetol. 2025 Aug 11;24(1):328. doi: 10.1186/s12933-025-02885-4.

Abstract

BACKGROUND

Accurate cardiovascular risk (CVR) stratification remains challenging, particularly in identifying individuals with residual risk despite current screening tools. Abdominal obesity reflects visceral adipose tissue, which is metabolically active and strongly linked to pro-inflammatory and atherogenic states. This study aimed to evaluate the predictive utility of baseline cardiometabolic risk factors, with a particular focus on abdominal obesity as quantified by waist circumference (WC), alongside established 10-year CVR scores, for incident Major Adverse Cardiovascular Events (MACEs).

METHODS

We prospectively followed 736 outpatients (347 males, 389 females) from an Italian Internal Medicine Unit, initially free of MACEs. Baseline data included anthropometrics, biochemical markers, and calculated Framingham Risk Score (FRS) and SCORE2/SCORE2-OP. Abdominal obesity was defined according to the International Diabetes Federation criteria for Metabolic Syndrome (MetS) as a WC ≥ 94 cm in males and ≥ 80 cm in females. Incident MACEs were recorded during follow-up. Statistical analyses included t-tests, Chi-Square, ANOVA, and logistic regression.

RESULTS

Over a median follow-up of 84.9 months, 132 participants (17.9%) developed MACEs. Baseline abdominal obesity, present in 78.1% of the cohort, was significantly associated with incident MACEs (OR = 1.784, 95% CI = 1.04-3.118, p = 0.038), whereas BMI-defined obesity showed no such association (p = 0.394). Low HDL-cholesterol also emerged as a key predictor (OR = 1.672, 95% CI = 1.115-2.482, p = 0.012). In multivariate logistic regression, adjusted for age and other MetS components, abdominal obesity (OR = 2.2, 95% CI = 1.6-4.2, p = 0.001) and low HDL-c (OR = 1.9, 95% CI = 1.4-3.5, p = 0.001) remained robustly associated with MACEs. Notably, individuals within the SCORE2/SCORE2-OP 'Moderate-Risk' category, despite not being the highest risk overall, exhibited the highest baseline LDL-c levels and accounted for the largest proportion of MACEs (36.4%). Even among participants without baseline abdominal obesity, those who developed MACEs had significantly higher WC (p < 0.0001) and lower HDL-c (p = 0.0078) at baseline.

CONCLUSION

Abdominal obesity and low HDL-c are potent, independent predictors of cardiovascular events, outperforming traditional markers like BMI. Together with the need of reaching LDL-c serum target levels, these biomarkers are crucial for unmasking the residual risk missed by current stratification models.

摘要

背景

准确的心血管风险(CVR)分层仍然具有挑战性,尤其是在识别尽管有当前筛查工具但仍存在残余风险的个体方面。腹部肥胖反映了内脏脂肪组织,其具有代谢活性,并且与促炎和动脉粥样硬化状态密切相关。本研究旨在评估基线心脏代谢危险因素的预测效用,特别关注通过腰围(WC)量化的腹部肥胖,以及既定的10年CVR评分,对新发主要不良心血管事件(MACE)的预测效用。

方法

我们对来自意大利一个内科单元的736名门诊患者(347名男性,389名女性)进行了前瞻性随访,这些患者最初无MACE。基线数据包括人体测量学、生化标志物以及计算得出的弗明汉风险评分(FRS)和SCORE2/SCORE2-OP。腹部肥胖根据国际糖尿病联盟代谢综合征(MetS)标准定义为男性WC≥94厘米,女性WC≥80厘米。在随访期间记录新发MACE。统计分析包括t检验、卡方检验、方差分析和逻辑回归。

结果

在中位随访84.9个月期间,132名参与者(17.9%)发生了MACE。队列中78.1%存在基线腹部肥胖,其与新发MACE显著相关(OR = 1.784,95% CI = 1.04 - 3.118,p = 0.038),而BMI定义的肥胖则无此关联(p = 0.394)。低高密度脂蛋白胆固醇也成为关键预测因素(OR = 1.672,95% CI = 1.115 - 2.482,p = 0.012)。在多变量逻辑回归中,经年龄和其他MetS组分校正后,腹部肥胖(OR = 2.2,95% CI = 1.6 - 4.2,p = 0.001)和低高密度脂蛋白胆固醇(OR = 1.9,95% CI = 1.4 - 3.5,p = 0.001)仍与MACE密切相关。值得注意的是,SCORE2/SCORE2-OP“中度风险”类别中的个体,尽管并非总体风险最高,但基线低密度脂蛋白胆固醇水平最高,且发生MACE的比例最大(36.4%)。即使在无基线腹部肥胖的参与者中,发生MACE的个体在基线时WC也显著更高(p < 0.0001),高密度脂蛋白胆固醇更低(p = 0.0078)。

结论

腹部肥胖和低高密度脂蛋白胆固醇是心血管事件的有力独立预测因素,优于BMI等传统标志物。连同达到低密度脂蛋白胆固醇血清目标水平的必要性,这些生物标志物对于揭示当前分层模型遗漏的残余风险至关重要。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验