Momentum builds for tests that predict kidney damage

By Emily Hayes, LabPulse.com editor in chief

November 13, 2019 -- New studies show the potential for lab tests to help predict damage to kidneys in different settings -- one in kids in intensive care units and the other in diverse, multinational populations of adults. The two studies, both of which were reported separately in November, build hopes for prevention in the future.

Pairing the renal angina index (RAI) and urinary neutrophil gelatinase-associated lipocalin (uNGAL) in children seen in intensive care gives a more accurate picture of risk for acute kidney injury, researchers concluded in a study presented on November 9 at the American Society of Nephrology Kidney Week annual meeting in Washington, DC.

In the study of 569 renal angina index tests for 627 children admitted for intensive care, an RAI score of 8 or higher indicated a greater risk of developing severe acute kidney injury soon after admission (38% incidence for RAI-positive patients; 1.8% for RAI-negative patients, i.e., score less than 8). The researchers also noted that positive RAI was associated with significantly longer stays in the hospital.

A positive RAI result along with uNGAL of at least 150 ng/mL meant significantly higher risk for developing severe acute kidney injury, compared with a negative RAI score and negative uNGAL (55.5% versus 17.6%), Kelli Krallman, a research nurse at Cincinnati Children's Hospital Medical Center, and colleagues noted. Using both tests together has potential to flag patients at risk for acute kidney injury and associated poor outcomes, including the need for kidney dialysis.

Preventing chronic kidney disease

In a separate study, investigators with the Chronic Kidney Disease Prognosis Consortium (CKD-PC) reported on the development of accurate equations for predicting the risk of developing chronic kidney disease, based on data from more than 5.2 million people drawn from 34 multinational cohorts. The results from Johns Hopkins epidemiologist Dr. Josef Coresh, PhD, and colleagues were published online November 8 in the Journal of the American Medical Association.

The researchers examined the development of reduced kidney function, defined as an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 across the datasets. Results were stratified by those with and without diabetes.

CKD-PC study results: Risk for developing kidney disease
Population Incident chronic kidney disease, defined as eGFR less than 60 mL/min/1.73 m2 Mean time of onset
With diabetes; mean age, 54 (n = 4,441,084) 660,856 (14.9%) 4.2 years
No known diabetes; mean age, 62 (n = 781,627) 313,646 (40%) 3.9 years
Source: Coresh et al, JAMA, November 8, 2019.

The researchers developed equations for identifying those at risk for developing reduced eGFR over five years, incorporating a wide range of factors that included the following:

  • Age/sex
  • eGFR results
  • Albuminuria concentration
  • Hemoglobin A1c (for those with diabetes)
  • History of cardiovascular disease
  • Body mass index

The accuracy of the risk scores was very good for those with diabetes and excellent for those without it, Coresh and colleagues found. They suggested the risk models could be helpful in identifying those at risk for chronic kidney disease and taking steps to prevent it.

"Readily available demographic, clinical, and laboratory variables were used in these risk models so that risk calculators from these models could conceivably be added to electronic health records to identify patients at increased risk of developing reduced eGFR," Coresh et al wrote.

A common and dangerous condition

The authors noted how common chronic kidney disease is: An estimated 697 people worldwide have reduced eGFR or increased albuminuria, up by 70% since 1990. In the U.S., the lifetime risk for developing it is 59.1%, they wrote.

Research has been more active in developing ways to predict the risk of kidney failure in people with established chronic kidney disease than in preventing its onset, they suggested. The authors see stratification by the presence or absence of diabetes and the inclusion of diverse populations as strengths of their approach relative to other models.

"A wide range of risk was seen, and the level of risk was strongly associated with the demographic features and comorbid conditions," Coresh and colleagues wrote. "The absolute risk was generally higher among persons with diabetes than among those without diabetes and those of older age regardless of the presence or absence of diabetes."

Paradigm change toward primary prevention?

The results bode well for primary prevention in chronic kidney disease, according to an accompanying editorial by University of California, San Francisco (UCSF) clinicians Dr. Sri Lekha Tummalapalli and Dr. Michelle Estrella.

The risk models demonstrated excellent ability to distinguish the likelihood of developing reduced eGFR over five years, they suggested in the editorial, which was also published online November 8 in JAMA.

"As with other risk prediction models, the present equations may require recalibration for use across populations with disparate baseline risks and within a specific population if the risk evolves over time," Tummalapalli and Estrella wrote. "Although the majority of cohorts in the derivation sample had a small proportion of black or Hispanic participants, the risk equations appeared to work well across racial and ethnic groups."

The CKD-PC study shifts the focus from secondary to primary prevention of kidney disease, which is a "critical step" toward reducing the global burden of the disease. The research could be used to develop screening strategies, they suggested.

"Moreover, to develop risk-based approaches for CKD rescreening, specific thresholds for action will need to be tested and refined for different clinical practice settings," they wrote.

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Last Updated eh 11/13/2019 12:43:55 PM