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Assessment of Kidney Organ Quality and Prediction of Outcome at Time of Transplantation

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Publisher Springer
Date 2011 Jan 29
PMID 21274534
Citations 13
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Abstract

The critical importance of donor organ quality, i.e., number of surviving nephrons, ability to withstand injury, and capacity for repair in determining short- and long-term outcomes is becoming increasingly clear. This review provides an overview of studies to assess donor kidney quality and subsequent transplant outcomes based on clinical pathology and transcriptome-based variables available at time of transplantation. Prediction scores using clinical variables function when applied to large data sets but perform poorly for the individual patient. Histopathology findings in pre-implantation or post-reperfusion biopsies help to assess structural integrity of the donor kidney, provide information on pre-existing donor disease, and can serve as a baseline for tracking changes over time. However, more validated approaches of analysis and prospective studies are needed to reduce the number of discarded organs, improve allocation, and allow prediction of outcomes. Molecular profiling detects changes not seen by morphology or captured by clinical markers. In particular, molecular profiles provide a quantitative measurement of inflammatory burden or immune activation and reflect coordinated changes in pathways associated with injury and repair. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management needs the integration of clinical and pathology-based variables, as well as more objective reference markers of transplant function, post-transplant events, and long-term outcomes.

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References
1.
Oh C, Jeon K, Kim H, Kim S, Kim Y, Pelletier S . Metabolic demand and renal mass supply affecting the early graft function after living donor kidney transplantation. Kidney Int. 2005; 67(2):744-9. DOI: 10.1111/j.1523-1755.2005.67136.x. View

2.
Pratschke J, Tullius S, Neuhaus P . Brain death associated ischemia/reperfusion injury. Ann Transplant. 2004; 9(1):78-80. View

3.
Li X, Hassoun H, Santora R, Rabb H . Organ crosstalk: the role of the kidney. Curr Opin Crit Care. 2009; 15(6):481-7. DOI: 10.1097/MCC.0b013e328332f69e. View

4.
Grossberg J, Reinert S, Monaco A, Gohh R, Morrissey P . Utility of a mathematical nomogram to predict delayed graft function: a single-center experience. Transplantation. 2006; 81(2):155-9. DOI: 10.1097/01.tp.0000188621.54448.c8. View

5.
Oh C, Lee B, Kim H, Kim S, Kim Y . Predicting the ideal serum creatinine of kidney transplant recipients by a simple formula based on the balance between metabolic demands of recipients and renal mass supply from donors. Transplant Proc. 2008; 40(7):2307-9. DOI: 10.1016/j.transproceed.2008.07.002. View