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Evaluating symptom burden in kidney transplant recipients: validation of the revised Edmonton Symptom Assessment System for kidney transplant recipients - a single-center, cross-sectional study.

Sumaya DanoMartha PokarowskiBetty LiaoEvan TangOladapo EkundayoVernon LiNathaniel EdwardsHeather FordMarta NovakIstvan Mucsi
Published in: Transplant international : official journal of the European Society for Organ Transplantation (2020)
We assessed the validity of the Edmonton Symptom Assessment System (ESAS-r) in kidney transplant recipients (KTR). A cross-sectional sample of 252 KTR was recruited. Individual ESAS-r symptom scores and symptom domain scores were evaluated. Internal consistency, convergent validity, and construct validity were assessed with Cronbach's α, Spearman's rank correlations, and a priori-defined risk group comparisons. Mean (SD) age was 51 (16), 58% were male, and 58% Caucasian. ESAS-r Physical, Emotional, and Global Symptom Scores demonstrated good internal consistency (α > 0.8 for all). ESAS-r Physical and Global Symptom Scores strongly correlated with PHQ-9 scores (0.72, 95% CI: 0.64-0.78 and 0.74, 95% CI: 0.67-0.80). For a priori-defined risk groups, individual ESAS-r symptom score differed between groups with lower versus higher eGFR [pain: 1 (0-3) vs. 0 (0-2), delta = 0.18; tiredness: 3 (1-5) vs. 1.5 (0-4), delta = 0.21] and lower versus higher hemoglobin [tiredness: 3 (1-6) vs. 2 (0-4), delta = 0.27]. ESAS-r Global and Physical Symptom Scores differed between groups with lower versus higher hemoglobin [13 (6-29) vs. 6.5 (0-18.5), delta = 0.3, and 9 (2-19) vs. 4 (0-13), delta = 0.24] and lower versus higher eGFR [11 (4-20) vs. 6.5 (2-13), delta = 0.21, and 7 (2-16) vs. 3 (0-9), delta = 0.26]. These data support reliability and construct validity of ESAS-r in KTR. Future studies should explore its clinical utility for symptom assessment among KTR.
Keyphrases
  • patient reported
  • small cell lung cancer
  • physical activity
  • mental health
  • epidermal growth factor receptor
  • tyrosine kinase
  • machine learning
  • current status
  • pain management
  • clinical evaluation