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Kidney Week

Abstract: PO2492

Predictors of Kidney Transplant Evaluation Non-Attendance

Session Information

Category: Transplantation

  • 1902 Transplantation: Clinical

Authors

  • Ford, Christopher Graham, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
  • Kruger, Eric, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
  • Leyva, Yuridia, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
  • Zhu, Yiliang, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
  • Kendall, Kellee, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
  • Croswell, Emilee J., University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
  • Dew, Mary amanda, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
  • Puttarajappa, Chethan M., University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States
  • Unruh, Mark L., University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
  • Ng, Yue-Harn, University of Washington Medical Center, Seattle, Washington, United States
  • Myaskovsky, Larissa, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, United States
Background

We examined which medical and socio-cultural factors predict kidney transplant evaluation (KTE) non-attendance, because missing a KTE appointment precludes access to transplantation, and having empty clinic slots impacts access to care for others.

Methods

We collected patient characteristics in an interview prior to KTE, covering demographics (e.g., income, education), medical factors (e.g., on dialysis, co-morbidities), cultural factors (e.g., medical mistrust), psychosocial characteristics (e.g., social support, depression), and knowledge factors (e.g. knowledge about transplant). We used latent class analysis (LCA) to determine if we could identify meaningful classes (groups of patients with patterns across variables) that were associated with KTE non-attendance.

Results

Our sample (N=1119) was 37% female, 76% non-Hispanic White, median age 59.4 years (IQR= 49.2-67.5), 25% had income below federal poverty line, 47% were < high school graduate, 48% were married, 44% had public insurance only, and 142 (13%) did not attend KTE appointment. LCA analyses indicated that a two-class solution consisting of a (1) high burden and (2) low burden group was optimal. Relative to the low burden group, the high burden group was less likely to be married, more likely to be on dialysis, less likely to have potential living donor, had higher kidney disease burden, more experiences of healthcare discrimination, higher medical mistrust, less social support, more depression, less knowledge about transplant, and more worry about kidney transplant harm. Belonging to the high burden group was associated with approximately twice greater odds of KTE non-attendance (OR=1.92, p<0.001, 95% CI:1.57, 2.34).

Conclusion

Medical and socio-cultural factors predict KTE non-attendance. Transplant teams should consider targeting patients with characteristics indicating high burden for additional support (e.g., exploring motivation and barriers with patients, assisting with resources to attend appointment, and providing additional reminders or notifications). Given the association of clinic non-attendance with being on dialysis, a treatment with significant patient burden, future research should also focus on the benefits of referring patients for transplant evaluation prior to initiating dialysis.

Funding

  • NIDDK Support