Association Between the Lipid Profile and Renal Dysfunction in the Heart Failure Patients

Zhang, Hong; Shi, Shuang; Zhao, Xiujuan; Wang, Jun-Kui; Liu, Zhongwei; Liu, Fuqiang; Zhu, Ling; Zhu, Shunming; Zhang, Yong; Pan, Shuo

doi:10.1159/000498834

Cited by 17 publications

(19 citation statements)

References 51 publications

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“…The results of the present study are in agreement with the majority of literature, yet, in many studies, the direct and independent relationship between higher levels of lipids with the progression of kidney diseases was missing [41]. The relation between HDL-C with kidney dysfunction is presented in many studies, yet, the topic remains controversial whether it can be used as an indicator for predicting renal dysfunctions [42]. In a previous study, lipid dyslipidemia in kidney disease patients is linked to high TG levels, normal or slightly low LDL-C, and decreased HDL-C levels [43].…”

Section: Discussionsupporting

confidence: 88%

The Correlation Between Lipid Profile and Renal Function Tests in Patients with Cardiovascular Disease in Erbil city, Kurdistan Region of Iraq

Baqi

Rostam

2020

KJAR

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Cardiovascular disease patients frequently suffer from the incidence of renal dysfunctions, the prevalence of the correlation, however, remains ambiguous. This study aims to see how CVD and renal function are related to the subjected group of patients suffer from symptoms of CVD. The method recruited for this objective was using of serum lipid profile test as a marker for evaluating the CVD and making correlations to the blood urea, serum uric acid, and serum creatinine levels as markers for assessing renal function on 159 individuals with CVD symptoms in Erbil city. Two statistical analysis methods (The linear regression and Pearson’s correlation) were employed for determining the existence from a lack of relationship between them. The results showed a statistically significant correlation p<0.05 by both methods between the renal function markers and TC. The UA was correlated to TG, LDL-C, and VLDL-C p<0.05 by regression analysis. The SCr was correlated to TG and LDL-C p<0.05 by both methods, and to VLDL by regression analysis. According to the outcome of the current study both lipid profile and renal function markers are correlated in mostly a statistically significant manner. Yet, the results are not conclusive, further studies are needed in this area for indemnify the irrefutable evidence concerning this relation.

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Section: Discussionsupporting

confidence: 88%

The Correlation Between Lipid Profile and Renal Function Tests in Patients with Cardiovascular Disease in Erbil city, Kurdistan Region of Iraq

Baqi

Rostam

2020

KJAR

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“…change in odds of 1.5). This is consistent with literature that shows a link between chronic kidney disease with heart failure, and with hyperlipidaemia, respectively [24,25]. Pathophysiological features indicate that heart failure can cause a reduction in cardiac output and decrease in renal perfusion which are primary drivers of renal dysfunction in heart failure.…”

Section: Quantifying Disease Interactionssupporting

confidence: 92%

Data-driven identification of complex disease phenotypes

Strauss

Niederkrotenthaler

Thurner

et al. 2021

J. R. Soc. Interface.

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Disease interaction in multimorbid patients is relevant to treatment and prognosis, yet poorly understood. In the present work, we combine approaches from network science, machine learning and computational phenotyping to assess interactions between two or more diseases in a transparent way across the full diagnostic spectrum. We demonstrate that health states of hospitalized patients can be better characterized by including higher-order features capturing interactions between more than two diseases. We identify a meaningful set of higher-order diagnosis features that account for synergistic disease interactions in a population-wide ( N = 9 M) medical claims dataset. We construct a generalized disease network where (higher-order) diagnosis features are linked if they predict similar diagnoses across the whole diagnostic spectrum. The fact that specific diagnoses are generally represented multiple times in the network allows for the identification of putatively different disease phenotypes that may reflect different disease aetiologies. At the example of obesity, we demonstrate the purely data-driven detection of two complex phenotypes of obesity. As indicated by a matched comparison between patients having these phenotypes, we show that these phenotypes show specific characteristics of what has been controversially discussed in the medical literature as metabolically healthy and unhealthy obesity, respectively. The findings also suggest that metabolically healthy patients show some progression towards more unhealthy obesity over time, a finding that is consistent with longitudinal studies indicating a transient nature of metabolically healthy obesity. The disease network is available for exploration at https://disease.network/.

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“…Zhang et al have demonstrated no association between TC, TG, LDL-C, and Apolipoprotein B with eGFR in patients with CKD. Only HDL-C was significantly positively associated with renal dysfunction [ 50 ]. Seok-Hyung Kim et al detected Apolipoprotein B/A1 ratio’s predictive ability for coronary artery calcification only in patients with normal kidney function [ 51 ].…”

Section: Discussionmentioning

confidence: 99%

Association of Early Renal Dysfunction with Lipid Profile Parameters among Hypertensives in Kazakhstan

et al. 2021

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Dyslipidemia plays an essential role in chronic kidney disease (CKD). The role of lipids and lipoproteins in the early pre-disease state of CKD in hypertensive patients is still unclear. The study aimed to evaluate the relationship between early renal dysfunction and lipid profile parameters among hypertensive patients in Kazakhstan. From April 2015 to December 2016, 800 Kazakh males and females with primary hypertension who met the inclusion criteria were included in this cross-sectional study. Data were collected on socio-demographics, lifestyle parameters, family history of cardiovascular disease, and hypertension. Additionally, Dietary Quality Score (DQS), anthropometric data, and blood pressure were recorded. Laboratory blood measurements included eGFR (estimated glomerular filtration rate), lipid profile parameters such as Apolipoprotein B, A1, HDL-C, LDL-C, and TG. We found a linear relationship between early renal dysfunction and LDL-C, Apolipoprotein B, and Apolipoprotein B/A1 ratio, which was in all cases negative and small (r = −0.27, −0.23 and −0.16, respectively). Apolipoprotein A1, HDL-C and TG have not revealed a linear relationship with GFR (r = −0.06, r = −0.06, and r = −0.045, respectively). The multicollinearity test restricted the linear model to Apolipoprotein B only. Further linear regression analysis confirmed an inverse significant linear association between eGFR and Apolipoprotein B. Age, DQS, and income appear to be positive confounding factors, significantly fitted the final model. ROC analysis had proven the predictive power of Apolipoprotein B in pre-CKD eGFR decline before and after adjustment for age, DQS and income (AUC = 0.62 and AUC = 0.77, respectively). For differentiating non-diabetic subjects with and without pre-CKD eGFR decrease, 1.05 g/L and 0.98 g/L are likely to be optimal cutoff points in males and females, respectively. These findings will help early prediction of renal dysfunction and contribute to a more accurate estimation of CVD risk.

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Association Between the Lipid Profile and Renal Dysfunction in the Heart Failure Patients

Cited by 17 publications

References 51 publications

The Correlation Between Lipid Profile and Renal Function Tests in Patients with Cardiovascular Disease in Erbil city, Kurdistan Region of Iraq

The Correlation Between Lipid Profile and Renal Function Tests in Patients with Cardiovascular Disease in Erbil city, Kurdistan Region of Iraq

Data-driven identification of complex disease phenotypes

Association of Early Renal Dysfunction with Lipid Profile Parameters among Hypertensives in Kazakhstan

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