Association and predictive value analysis for metabolic syndrome on systolic and diastolic heart failure in high-risk patients

• Published in: BMC cardiovascular disorders Vol. 14; no. 1; p. 124
• Main Authors: Tang, Zi-Hui, Wang, Lin, Zeng, Fangfang, Zhang, Keqin
• Format: Journal Article
• Language: English
• Published: England BioMed Central 24.09.2014
• Subjects: Adult; Aged; Area Under Curve; Biomarkers - blood; Blood Glucose - analysis; Blood Pressure; Body mass index; Chi-Square Distribution; China - epidemiology; Cholesterol; Drug therapy; Dyslipidemias - blood; Dyslipidemias - epidemiology; Female; Glucose Metabolism Disorders - blood; Glucose Metabolism Disorders - epidemiology; Heart attacks; Heart Failure, Diastolic - blood; Heart Failure, Diastolic - diagnosis; Heart Failure, Diastolic - epidemiology; Heart Failure, Diastolic - physiopathology; Heart Failure, Systolic - blood; Heart Failure, Systolic - diagnosis; Heart Failure, Systolic - epidemiology; Heart Failure, Systolic - physiopathology; Humans; Hypertension - epidemiology; Hypertension - physiopathology; Insulin resistance; Linear Models; Logistic Models; Male; Metabolic syndrome; Metabolic Syndrome - blood; Metabolic Syndrome - diagnosis; Metabolic Syndrome - epidemiology; Metabolic Syndrome - physiopathology; Middle Aged; Multivariate Analysis; Odds Ratio; Predictive Value of Tests; Prevalence; Retrospective Studies; Risk Assessment; Risk Factors; ROC Curve; Severity of Illness Index; Triglycerides - blood
• ISSN: 1471-2261; 1471-2261
• DOI: 10.1186/1471-2261-14-124

The purpose of this study was, in high-risk patients, to simultaneously estimate the effect of metabolic syndrome (MetS) on diastolic or systolic heart failure (DHF or SHF), to evaluate MetS predictive value for both outcomes. We retrospective enrolled 347 high-risk patients who were scheduled to undergo coronary angiography. They were categorized into DHF cases, SHF cases and reference group. The association of MetS with DHF or SHF was assessed by multinomial logistic regression model. The shared contributor to both outcomes was estimated by bivariate association analysis. The predictive performance of MetS severity score was evaluated using the area under the receiver-operating characteristic curve (AUC). Hypertension (HT) and triglycerides (TG) were detected to independently associate with DHF (P = 0.044 and 0.049, respectively), while HT and fasting plasma glucose (FPG) independently associate with SHF (P = 0.036 and 0.016, respectively). Bivariate association analysis showed that HT as a shared predictor to both outcomes (P = 0.028). MetS severity score significantly associated with DHF or SHF independently (P = 0.004 and 0.043, respectively), and was a shared predictor to both outcomes (P = 0.049), and showed a high value in predicting DHF and SHF (AUC = 0.701 and 0.722, respectively). Our findings signify that MetS is an independently shared predictor of DHF and SHF, and HT is also independently associated with both outcomes in high-risk patients. Prevalence of DHF or SHF trends to increase with increasing MetS severity showing high predictive value for both outcomes.