Predictive value of remnant cholesterol level for all-cause mortality in heart failure patients

Abstract

Background: Lower cholesterol levels are associated with increased mortality in heart failure (HF) patients. Remnant cholesterol corresponds to all cholesterol not found in high-density lipoprotein (HDL) and low-density lipoprotein (LDL). The prognostic role of remnant cholesterol in HF remains unknown.

Objective: To reveal the relationship between the baseline remnant cholesterol level and all-cause mortality in HF patients.

Methods: This study enrolled 2,823 patients hospitalized for HF. Kaplan-Meier analysis, Cox regression, C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the prognostic value of remnant cholesterol for all-cause mortality in HF.

Results: The mortality rate was lowest in the fourth quartile of remnant cholesterol, which had an adjusted hazard ratio (HR) for death of 0.56 [HR: 0.39, 95% confidence interval (CI): 0.46-0.68, p < 0.001] relative to the first quartile. After adjustment, a one-unit increase in the level of remnant cholesterol was associated with a 41% decrease in the risk of all-cause mortality (HR: 0.59, 95% CI: 0.47-0.73, p < 0.001). A refinement in risk prediction was observed after adding remnant cholesterol quartile to the original model (ΔC-statistic = 0.010, 95% CI: 0.003-0.017; NRI = 0.036, 95% CI: 0.003-0.070; IDI = 0.025, 95% CI: 0.018-0.033; all p < 0.05).

Conclusion: Low remnant cholesterol levels are associated with increased all-cause mortality in HF patients. The addition of the remnant cholesterol quartile improved the predictive value over traditional risk factors.

Clinical trial registration: ClinicalTrials.gov, Unique Identifier: NCT02664818.

Keywords: all-cause mortality; heart failure; prognosis role; remnant cholesterol; serum lipid.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2023 Zhao, Zhao, Tian, Liang, Huang, Huang, Feng, Zhang and Zhang.

Figures

Figure 1

Flow diagram of the screening and enrollment of study participants. HF, heart failure; TC, total cholesterol; HDL-C, high density lipoprotein cholesterol; LDL, low density lipoprotein cholesterol.

Figure 2

Kaplan–Meier curves for all-cause mortality. (A) Kaplan–Meier curves for all-cause death stratified by total cholesterol (TC) quartiles (log-rank, p = 0.002). (B) Kaplan–Meier curves for all-cause death stratified by high density lipoprotein cholesterol (HDL-C) quartiles (log-rank, p = 0.002). (C) Kaplan–Meier curves for all-cause death stratified by low density lipoprotein cholesterol (LDL-C) quartiles (log-rank, p = 0.085). (D) Kaplan–Meier curves for all-cause death stratified by remnant cholesterol (log-rank, p < 0.001).

Figure 3

Adjusted risk of all-cause mortality by remnant cholesterol level. Smooth curve fitting was performed to explore the association between remnant cholesterol and the risk of all-cause mortality. Multivariate Cox regression was adjusted for sex, age, body mass index, hypertension, diabetes mellitus, coronary heart disease, heart rate, systolic pressure, diastolic pressure, hemoglobin, albumin, alanine aminotransferase, aspartate transaminase, total bilirubin, serum uric, estimated glomerular filtration rate, high sensitivity C reactive protein, log(N-terminal pro-brain natriuretic peptide), left ventricular ejection fraction, New York Heart Association Functional Class and pharmacotherapy. The solid blue line indicates the adjusted risk of all-cause mortality. The gray shading indicates the 95% confidence interval. The red dotted lines indicate the first, second and third quartile of remnant cholesterol, left to right.

Figure 4

Subgroup analyses on prognostic role remnant cholesterol on all-cause mortality. The dots and lines indicate the estimates of the hazard ratio of all-cause mortality for per unit increment of remnant cholesterol with the corresponding 95% confidence intervals, respectively. The multivariate Cox regression model was adjusted for sex, age, body mass index, hypertension, diabetes mellitus, coronary heart disease, heart rate, systolic pressure, diastolic pressure, hemoglobin, albumin, alanine aminotransferase, aspartate transaminase, total bilirubin, serum uric, estimated glomerular filtration rate, high sensitivity C reactive protein, log(N-terminal pro-brain natriuretic peptide), left ventricular ejection fraction, New York Heart Association Functional Class and pharmacotherapy, except for the variable that is stratified.