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Mild Malnutrition Contributes the Greatest to the Poor Prognosis in Coronary Artery Disease With Well-Controlled Low-Density Lipoprotein Cholesterol Levels: A 4,863 Chinese Cohort Study

ABSTRACT: Background: Previous studies reported that patients with coronary artery disease (CAD) and well-controlled baseline LDL-C (<1.8 mmol/L) still had higher long-term all-cause mortality. However, no study has been conducted to explore the independent risk factors for long-term mortality. In addition, there also was no study evaluating the population attributable risk (PAR) of independent risk factors in combination with their prevalence and relative risk. Therefore, we aimed to identify the independent risk factors and estimate their PAR in patients with CAD and well-controlled baseline LDL-C (<1.8 mmol/L). Methods: We analyzed 4,863 consecutive CAD patients with well-controlled baseline LDL-C admitted to Guangdong Provincial People's Hospital in China from January 2007 to December 2018. Independent risk factors for long-term all-cause death were evaluated through stepwise approach and multivariable Cox regression analysis. PAR of independent risk factors was calculated with their hazard ratio and prevalence among our cohort. Results: The overall mortality was 16.00% (n = 778) over a median follow-up period of 5.93 years. Independent risk factors for all-cause death included malnutrition, age ≥75 years, congestive heart failure (CHF), chronic kidney disease (CKD) and atrial fibrillation. Among these risk factors of interest, the hazard ratio (HR) of severe malnutrition was the highest (HR 2.82, 95% CI: 1.86–4.26), and the PAR of mild malnutrition was the highest (19.49%, 95% CI: 0.65–36.01%). Conclusion: Malnutrition, age ≥75 years, CHF, CKD and atrial fibrillation were independent predictors for long-term all-cause mortality in CAD patients with well-controlled LDL-C levels. Considering prevalence of these risk factors, more attention should be paid to the occurrence of mild malnutrition for these patients. Clinical Trial Registration:ClinicalTrials.gov, identifier: NCT04407936.

SUBMITTER: Wang B

PROVIDER: S-EPMC8511711 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Coronary artery disease (CAD) is the leading cause of death worldwide, which has a long asymptomatic period of atherosclerosis. Thus, it is crucial to develop efficient strategies or biomarkers to assess the risk of CAD in asymptomatic individuals. Methods: A total of 356 consecutive CAD patients and 164 non-CAD controls diagnosed using coronary angiography were recruited. Blood lipids, other baseline characteristics, and clinical information were investigated in this study. In addition, low-density lipoprotein cholesterol (LDL-C) subfractions were classified and quantified using the Lipoprint system. Based on these data, we performed comprehensive analyses to investigate the risk factors for CAD development and to predict CAD risk. Results: Triglyceride, LDLC-3, LDLC-4, LDLC-5, LDLC-6, and total small and dense LDL-C were significantly higher in the CAD patients than those in the controls, whereas LDLC-1 and high-density lipoprotein cholesterol (HDL-C) had significantly lower levels in the CAD patients. Logistic regression analysis identified male [odds ratio (OR) = 2.875, P < 0.001], older age (OR = 1.018, P = 0.025), BMI (OR = 1.157, P < 0.001), smoking (OR = 4.554, P < 0.001), drinking (OR = 2.128, P < 0.016), hypertension (OR = 4.453, P < 0.001), and diabetes mellitus (OR = 8.776, P < 0.001) as clinical risk factors for CAD development. Among blood lipids, LDLC-3 (OR = 1.565, P < 0.001), LDLC-4 (OR = 3.566, P < 0.001), and LDLC-5 (OR = 6.866, P < 0.001) were identified as risk factors. To predict CAD risk, six machine learning models were constructed. The XGboost model showed the highest AUC score (0.945121), which could distinguish CAD patients from the controls with a high accuracy. LDLC-4 played the most important role in model construction. Conclusions: The established models showed good performance for CAD risk prediction, which can help screen high-risk CAD patients in asymptomatic population, so that further examination and prevention treatment might be taken before any sudden or serious event.

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Mild Malnutrition Contributes the Greatest to the Poor Prognosis in Coronary Artery Disease With Well-Controlled Low-Density Lipoprotein Cholesterol Levels: A 4,863 Chinese Cohort Study

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