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Association Between the Lipid Profile and Renal Dysfunction in the Heart Failure Patients
Hong Zhang1, Shuang Shi2, Xiu-Juan Zhao3
1Department of Neurology, People's Hospital of Shaanxi Province, Xi'an, China.
Insights
In heart failure patients, high-density lipoprotein-cholesterol (HDL-C) was the sole lipid marker linked to renal dysfunction. This finding is crucial for managing heart failure with chronic kidney disease (CKD).
Area of Science:
- Cardiology
- Nephrology
- Clinical Lipidology
Background:
- Heart failure (HF) frequently co-occurs with chronic kidney disease (CKD), increasing hospitalization and mortality risks.
- The relationship between lipid profiles and renal dysfunction in HF patients remains under-explored.
Purpose of the Study:
- To investigate the association between various lipid parameters and renal dysfunction in hospitalized patients with heart failure.
Main Methods:
- A cohort of 336 hospitalized heart failure patients (LVEF ≤45%, NYHA class II-IV) was analyzed.
- Renal dysfunction was defined as estimated glomerular filtration rate (eGFR) < 90 mL/min·1.73 m2.
- Logistic regression was employed to assess the association between lipid profiles and renal dysfunction, adjusting for confounders.
Main Results:
- Over half (54.2%) of the patients exhibited renal dysfunction.
- High-density lipoprotein-cholesterol (HDL-C) was significantly associated with renal dysfunction (OR=0.119, P=0.003) after adjusting for multiple clinical and laboratory variables.
- Total cholesterol, triglycerides, LDL-C, and apolipoprotein B showed no significant correlation with eGFR.
Conclusions:
- High-density lipoprotein-cholesterol (HDL-C) is the only lipid profile component significantly associated with renal dysfunction in hospitalized heart failure patients.
- These findings highlight the importance of HDL-C in the context of cardiorenal syndrome.
Background/Aims:
In heart failure patients with high prevalence of chronic renal disease (CKD), hospitalization and mortality, whether the lipid profile was associated with renal dysfunction remained unknown. The present study intended to clarify the association between the lipid profile and renal dysfunction in the heart failure patients.
Methods:
336 hospitalized heart failure patients with left ventricle ejection fraction (LVEF) ≤45% and New York Heart Association (NYHA) class II-IV were enrolled. The estimated glomerular filtration rate (eGFR) < 90 mL/min·1.73 m2 was defined as renal dysfunction. The demographic, clinical data, blood samples and echocardiography were documented. The Pearson simple linear correlation was performed to evaluate the confounding factors correlated with eGFR. The significantly correlated factors were enrolled in Logistic regression as confounding factors to determine the association between the lipid profile and renal dysfunction in the heart failure patients.
Results:
182 patients (54.2%) had renal dysfunction and 154 patients (45.8%) did not have renal dysfunction. The waist circumference, platelet counts, platelet distribution width (PDW), high density lipoprotein-cholesterol (HDL-C), apolipoprotein A1 (apoA1), albumin and left ventricular ejection fraction (LVEF) are positively correlated with eGFR (all P< 0.05). Meanwhile, the age, mean platelet volume (MPV), neutrophilic granulocyte percentage (NEUT%), urea nitrogen (BUN), creatinine and total bilirubin (TBIL) are negatively correlated with eGFR (all P< 0.05). The total cholesterol (TC), triglyceride, low density lipoprotein-cholesterol (LDL-C) and apolipoprotein B (apoB) show no correlation with eGFR. After the adjustment of sex, hypertension, diabetes mellitus, age, waist circumference, platelet counts, MPV, PDW, NEUT%, TBIL, albumin and LVEF, HDL-C is the only lipid factor still significantly associated with renal dysfunction in hospitalized heart failure patients (OR=0.119, P=0.003).
Conclusion:
Among the lipid profile of TC, triglyceride, LDL-C, HDL-C, apo A1 and apo B, the HDL-C is the only lipid factor significantly associated with renal dysfunction in hospitalized heart failure patients.
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