Ƶ

Serum Bicarbonate Tied to CKD Progression

— Another use for multivariate risk equations

Last Updated April 16, 2018
Ƶ MedicalToday

This article is a collaboration between Ƶ and:

AUSTIN, Texas -- Low serum bicarbonate (TCO2) was an independent predictor for chronic kidney disease (CKD) progression, researchers reported here.

This relationship was identified by incorporating the eight-variable kidney failure risk equation (KFRE) to adjust the risk model, explained Navdeep Tangri, Chronic Disease Innovation Center in Winnipeg, Canada, speaking at the .

Tangri and colleagues reported that by adjusting for baseline risk factors with the KFRE in a cohort of patients with stages 3-5 CKD -- an eGFR of 10-60 ml/min/1.73 m2 -- there was 7% decrease in the risk of kidney failure or a ≥40% decline in eGFR associated with every 1 mEq/L increase in TCO2 (aHR 0.93, 95% CI 0.90-0.94).

Prior to adjustment with the KFRE, the associated risk for the composite outcome was higher with TCO2 decline.

Tangri's group , which combines the following eight clinical factors into a predictive equation for CKD progression to kidney failure: age, sex, estimated GFR, albuminuria, serum calcium, serum phosphate, serum bicarbonate, and serum albumin.

"Since then, they have been widely used to predict the risk of kidney failure requiring dialysis," Tangri told Ƶ.

He added that his group wanted to see how changes in serum bicarbonate could affect this CKD progression, independent of the patient's baseline kidney failure risk.

"These changes can occur in metabolic acidosis, which is common in late-stage CKD patients and, as seen in our work and in others, can lead to accelerated progression of CKD," Tangri noted, adding how the findings were consistent with their original hypothesis. However, he noted they were particularly surprised at the strong linear association between serum bicarbonate levels and kidney failure risk, seen across patients with a wide range of kidney functioning.

"We were also able to demonstrate that population event rates for kidney failure and 40% decline in eGFR could be estimated using the kidney failure risk equation," he added.

Similar relationships were reported in subgroups of patients whose risk was also adjusted using a KFRE. Patients with an eGFR of 15-45 (n=1,560) reported a 6% lower risk for kidney failure or a ≥40% decline in eGFR with every 1 mEq/L increment in TCO2 (aHR 0.94, 95% CI 0.91-0.97).

Those with metabolic acidosis (n=437) -- TCO2 between 12-22 -- had a 9% lower risk for this same composite outcome per TCO2 increment (aHR 0.91, 95% CI 0.86-0.97).

Ultimately, he suggested these findings provide evidence that KFREs can be used to predict CKD progression, as well as can be used to estimate the effect that one clinical factor can have on progression.

Because of these findings, Tangri suggested future clinical trials "should consider using the KFREs to model effect sizes and event rates for new trials that target CKD progression" in order to conduct a more efficient trial by having a more accurate understanding of the expected event rates and effect size in their cohorts.

  • author['full_name']

    Kristen Monaco is a senior staff writer, focusing on endocrinology, psychiatry, and nephrology news. Based out of the New York City office, she’s worked at the company since 2015.

Disclosures

The study was supported by Tricida, Inc.

Primary Source

National Kidney Foundation

Tangri N, et al "Use of the kidney failure risk equations to model clinical trial outcomes" NKF 2018; Abstract #365.