Prognostic impact of malnutrition in patients with coronary artery disease: a systematic review and meta-analysis

医学 子群分析 营养不良 危险系数 荟萃分析 冠状动脉疾病 背景(考古学) 内科学 队列研究 置信区间 队列 体质指数 生物 古生物学
作者
Fengling He,Haoxiang Huang,Wenlong Xu,Kai Cui,Yifei Ruan,Yuetong Guo,Junfen Wang,Jianping Bin,Yuegang Wang,Yanmei Chen
出处
期刊:Nutrition Reviews [Oxford University Press]
卷期号:82 (8): 1013-1027 被引量:2
标识
DOI:10.1093/nutrit/nuad108
摘要

Abstract Context Conflicting predictions of malnutrition for the long-term prognosis of coronary artery disease (CAD) exist. Objective This study aimed to investigate the relationship between malnutrition and long-term prognosis of patients with CAD. Data Sources Four databases were searched for articles from February 11, 1936, to September 10, 2022. Data Extraction Cohort studies adjusting for multiple cardiovascular risk factors with data on CAD and malnutrition were included. Malnutrition was measured and defined by different nutritional evaluation tools. The hazard ratios (HRs) and confidence intervals (CIs) for all-cause mortality and major adverse cardiovascular events (MACEs) were synthesized. Subgroup analyses were performed based on study design, assessment tools, ethnicity/race, follow-up, sample size, and types of CAD. Meta-regression was used to compare whether the effect sizes of the 2 subgroups were statistically significant. Data Analysis A total of 30 cohort studies were included, totaling 81 361 participants with CAD. Nutritional evaluation tools, including the Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status (CONUT), Nutritional Risk Screening 2002, Mini-Nutritional Assessment, and Prognostic Nutritional Index, were used. Malnutrition increased all-cause mortality (HR = 1.72; 95% CI: 1.53, 1.93) and MACEs (HR = 1.47; 95% CI: 1.35, 1.60) in patients with CAD. Subgroup analysis revealed the results were consistent across study design, ethnicity/race, follow-up, sample size, and types of CAD. Subgroup analyses and meta-regression revealed that malnutrition was associated with a higher risk of all-cause mortality (HR = 2.26; 95% CI: 1.91, 2.68) and MACEs (HR = 2.28; 95% CI: 1.69, 3.08) in patients with stable CAD than those with other types of CAD. Meta-regression revealed that the GNRI (HR = 2.20; 95% CI: 1.65, 2.93) was more effective than CONUT (HR = 1.47; 95% CI: 1.21, 1.78) in predicting all-cause mortality. Conclusion Malnutrition independently increased all-cause mortality by 72% and MACEs by 47% in patients with CAD, especially with stable CAD. The GNRI is a more effective nutritional evaluation tool than CONUT in predicting all-cause mortality.
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