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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Nonlinear association between atherogenic index of plasma and chronic kidney disease: a nationwide cross-sectional
Bo Wang1, Chunqi Jiang2, Yinuo Qu2
1Central Hospital of Jinan City, No. 105, Jiefang Road, Jinan City, Shandong Province, China.
Insights
The atherogenic index of plasma (AIP) shows a complex, non-linear link with chronic kidney disease (CKD). This relationship varies, with AIP inversely related to CKD below a certain threshold and positively related above it.
Area of Science:
- Cardiology
- Nephrology
- Metabolic Disorders
Background:
- Metabolic disorders and chronic kidney disease (CKD) have established links.
- The association between CKD and atherogenic index of plasma (AIP) is less understood.
- This study investigates the relationship between AIP and CKD.
Purpose of the Study:
- To explore the correlation between AIP and CKD.
- To identify potential non-linear associations.
- To determine the inflection point of this relationship.
Main Methods:
- Weighted multivariate logistic regression was used.
- Smooth curve fitting analyzed curvilinear relationships.
- Recursive partitioning and two-stage linear regression identified inflection points.
- Stratified analyses examined subgroup heterogeneity.
Main Results:
- Initial regression showed no significant linear association between AIP and CKD.
- Sensitivity and smooth curve analyses revealed a non-linear relationship.
- An inflection point was identified at AIP = -0.55.
- Below -0.55, AIP was inversely correlated with CKD; above it, AIP was positively correlated.
- Non-linear associations were noted in females and individuals aged 50+.
Conclusions:
- A significant curvilinear relationship exists between CKD and AIP.
- The nature of the association depends on the AIP threshold.
Background:
The interplay between metabolic disorders and chronic kidney disease (CKD) has been well-documented. However, the connection between CKD and atherogenic index of plasma (AIP) remains understudied. This research delves into the correlation between these two factors, aiming to shed new light on their potential association.
Methods:
The relationship between AIP and CKD was evaluated using a weighted multivariate logistic regression model, and the curvilinear relationship between AIP and CKD was explored through smooth curve fitting. We engaged a recursive partitioning algorithm in conjunction with a two-stage linear regression model to precisely determine the inflection point. By conducting stratified analyses, the heterogeneity within subpopulations was explored.
Results:
In the regression model that accounted for all covariates, ORs (95% CI) for the association between CKD and AIP were 1.12 (0.91, 1.36), indicating no significant association between AIP and CKD. However, sensitivity analyses suggested that the relationship between them may be non-linear. Smooth curve analysis confirmed the non-linear relationship between AIP and CKD, identifying an inflection point at -0.55. Below this threshold, AIP exhibited a significant inverse correlation with CKD. Conversely, above this threshold, a pronounced positive correlation was detected. Stratified analyses elucidated that a non-linear association between AIP and CKD was observed among female participants and those aged 50 and above.
Conclusion:
We found a curvilinear relationship between chronic kidney disease and atherogenic index of plasma.
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