ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on Twitter

Kidney Week

Abstract: PO0096

Risk Factors for Patient Subgroups with Distinct Health Utility Profiles Following AKI

Session Information

Category: Acute Kidney Injury

  • 102 AKI: Clinical, Outcomes, and Trials

Authors

  • Kwong, Yuenting Diana, University of California San Francisco, San Francisco, California, United States
  • Liu, Kathleen D., University of California San Francisco, San Francisco, California, United States
  • Kellum, John A., University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Miaskowski, Christine, University of California San Francisco, San Francisco, California, United States
Background

Health-related quality of life (HRQOL) after dialysis initiation for acute kidney injury (AKI) is low. We sought to determine patient subgroups with distinct health utility profiles at 60 days after diagnosis of AKI and evaluated the potential risk factors for these profiles.

Methods

The Biologic Markers of Renal Recovery for the Kidney (BioMaRK) study is an observational cohort of patients nested within the Veterans Affairs/National Institutes of Health Acute Renal Failure Trial Network study. Clinical characteristics and biomarkers of inflammation were collected from 817 patients with AKI around the time of dialysis initiation. Of these patients, 402 were alive at 60 days and 328 completed the Health Utility Index, which measures 8 health attributes and calculates an overall HRQOL score. Using latent class analysis (LCA) of these 8 attributes, we identified patient subgroups with distinct health utility profiles and risk factors associated with subgroup membership.

Results

Two subgroups were identified with 47% of patients being included in the low healthy utility subgroup (i.e. Low HU subgroup). This subgroup was characterized as having higher median ambulation, emotion, cognition, and pain scores. The remaining (i.e., 53%) were labeled as belonging in the subgroup with higher health utility (i.e. High HU subgroup). No significant differences were found between the two subgroups in terms of age, gender, or race. However, patients in the Low HU subgroup were more likely to have diabetes, lower albumin levels, and higher SOFA score. In addition, patients in the Low HU subgroup had more dialysis days, hospital days, and ICU days. No between groups differences were found in the assignment of high versus normal dialysis intensity. Day 1 biomarkers of GM-CSF, IL1, IL6, IL8, TNF-alpha, IL10, TNFR1, TNFR2, MIF, IL18 and DR5 were not statistically different between the two subgroups. However, patients in the Low HU subgroup had higher IL8, TNFR1, TNFR2, and DR5 levels at day 8.

Conclusion

Using a person-centered analytic technique (i.e., LCA), we found two subgroups of patients with distinct health utility profiles among 60 day survivors following acute kidney injury. Demographic, clinical, and biomarker characteristics associated with each subgroup may be used to identify patients at high risk of poor HRQOL.

Funding

  • NIDDK Support