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Related Experiment Videos

Predicting early renal allograft function using clinical variables.

Jason Moore1, Kay Tan, Paul Cockwell

  • 1Department of Renal Transplantation, University Hospital Birmingham, Edgbaston, Birmingham, B15 2TH, UK.

Nephrology, Dialysis, Transplantation : Official Publication of the European Dialysis and Transplant Association - European Renal Association
|June 9, 2007
PubMed
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Clinical variables moderately predict early renal transplant function, including delayed graft function (DGF). While useful, caution is advised before changing patient management based solely on these scores.

Area of Science:

  • Nephrology
  • Transplantation immunology
  • Clinical prediction modeling

Background:

  • Suboptimal early graft function is a significant challenge in renal transplantation.
  • Delayed graft function (DGF), requiring post-operative dialysis, is a key indicator, but other forms of suboptimal function are less studied.

Purpose of the Study:

  • To evaluate the predictive ability of clinical variables and established scoring systems for suboptimal early renal allograft function.
  • To assess prediction for various definitions of suboptimal function, including DGF, DGF duration, and creatinine levels.

Main Methods:

  • Analysis of clinical data from 217 renal transplant recipients on ciclosporin-based immunosuppression.
  • Multiple regression and receiver operating characteristic (ROC) curve analyses were used.

Related Experiment Videos

  • Evaluated individual clinical variables and three scoring systems: US Renal Database System (USRDS), deceased donor score (DDS), and expanded criteria donor (ECD) criteria.
  • Main Results:

    • Donor age, BMI, hypertension, donation after cardiac death, recipient ethnicity, recipient weight, and cold ischemic time were associated with early graft function (P<=0.05).
    • All tested scoring systems showed associations with early graft function; only the USRDS score remained significant in the regression model.
    • The USRDS score demonstrated moderate predictive utility for DGF, with improved accuracy at extreme scores (e.g., specificity 95%, PPV 73% for score >=150).

    Conclusions:

    • Clinical variables and scoring systems offer moderate predictive value for early renal allograft function.
    • While potentially useful in practice, these tools should be used cautiously, and management decisions should not rely solely upon them.