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Transplantation Learning Zone
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Predicting graft survival

Declaration of sponsorship Novartis Pharma AG
Read time: 40 mins
Last updated:16th Apr 2021
Published:16th Apr 2021
Are you up to date with the latest predictive tools for graft survival? Explore this section to find out all you need to know about the unmet need for graft survival and the tools used to predict survival, including the iBox algorithm.

Improving graft survival

One of the unmet needs of transplantation is long-term graft survival. Although short-term graft survival remains relatively high, long-term survival is poor, posing a significant burden to the healthcare practitioners, patients and society.

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Predictive tools for graft survival

To date, many models exist which are based on clinical parameters and have been developed to predict the time-to-graft failure or patient survival, several of which have been made publicly available online8–10

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The iBox algorithm

The iBox is a clinical decision support system for clinicians developed by the Paris Transplant Group, Paris, France.

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Implementing predictive tools in clinical practice

There is a need for a robust tool that can predict long-term graft survival since no improvement has been observed over the past 20 years. 

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References

  1. Rao KV, Andersen RC, O’brien TJ. Factors contributing for improved graft survival in recipients of kidney transplants. Kidney Int. 1983;24:210–221.
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Why sign up with Medthority?

Develop your knowledge with our disease and condition focused Learning Zones

Access content from credible sources, including expert-led commentary, videos, podcasts, and webinars as well as clinical trials, treatment information and guidelines 

Personalised dashboard providing updates and recommendations for content within your areas of interest

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