Kidney Week

Abstract: FR-PO951

Early-Stage Characteristics and Potential Predictors of CKD Among US Veterans

Session Information

• CKD Epidemiology, Risk Factors, Prevention - II
  November 03, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

• 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Dojcsak, Levente, University of Tennessee, Knoxville, Tennessee, United States

Levente Dojcsak,

• Chen, Cheng, University of Tennessee, Knoxville, Tennessee, United States

Cheng Chen,

• Grady, Stephen, University of Tennessee, Knoxville, Tennessee, United States

Stephen Grady,

• Mallisetty, Yamini, The University of Tennessee Health Science Center, Memphis, Tennessee, United States

Yamini Mallisetty,

• Niu, Haoran, University of Tennessee, Knoxville, Tennessee, United States

Haoran Niu,

• Shrestha, Prabin, The University of Tennessee Health Science Center, Memphis, Tennessee, United States

Prabin Shrestha,

• Sumida, Keiichi, The University of Tennessee Health Science Center, Memphis, Tennessee, United States

Keiichi Sumida,

• Thomas, Fridtjof, The University of Tennessee Health Science Center, Memphis, Tennessee, United States

Fridtjof Thomas,

• Langston, Michael Allen, University of Tennessee, Knoxville, Tennessee, United States

Michael Allen Langston,

• Kovesdy, Csaba P., The University of Tennessee Health Science Center, Memphis, Tennessee, United States

Csaba P. Kovesdy,

Background

Chronic Kidney Disease (CKD) is prevalent but under-diagnosed across the world. Its prediction remains a formidable challenge, even when complete clinical and demographic information is available. We studied a large patient cohort from the US Department of Veterans Affairs (VA) in an effort to identify predictive characteristics common to those afflicted with CKD before the disease becomes clinically evident.

Methods

From a cohort of 692,942 veterans with stable eGFR >60 ml/min/1.73m², we identified 174,627 patients who developed CKD within up to eight years following enrollment and compared them to patients who remained CKD free. Over these two patient subgroups, we calculated Pearson correlation coefficients for all baseline variable pairs and, for each such pair, we examined those that were differentially correlated as defined by an absolute difference of at least 0.15 between the CKD and non-CKD cohorts. Using a graph theoretic approach, we created finite, simple, undirected graphs, with variables of interest represented by vertices and edges weighted by correlation then thresholded. From these graphs we extracted dense subgraphs indicative of latent variable relationships to account for complex correlations.

Results

Age and a variety of specific comorbidities were correlated higher within the non-CKD subgroup than within the CKD subgroup. From graph theoretical analysis, we found that the Charlson index, congestive heart failure (CHF), myocardial infarctions (MI), and peripheral vascular disease (PVD) formed a dense subgraph indicative of highly interconnected disease relationships (Figure). Age and cardiovascular disease (CVD) only entered this putative network among non-CKD patients.

Conclusion

These results suggest that kidney disease belongs to a constellation of comorbidities that may help to act as predictors of incipient CKD. Chronological age may not play a prominent role in the development of comorbidities in patients with CKD, which may be explained by premature ageing seen in CKD.

Funding

• Veterans Affairs Support