Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models by Salaun, A, Knight, S, Wingfield, L, Zhu, T

“…This project uses interpretable methods to predict both graft failure and patient death using data from previously accepted kidney transplant offers. Using more than 25 years of transplant outcome data, we train and compare several survival analysis models in single risk settings. …”

Global availability of medications and health technologies for kidney care: A multinational study from the ISN-GKHA by Kelly, DM, Jones, ESW, Barday, Z, Arruebo, S, Caskey, FJ, Damster, S, Donner, J, Jha, V, Levin, A, Nangaku, M, Saad, S, Tonelli, M, Ye, F, Okpechi, IG, Bello, AK, Johnson, DW

“…Public funding (and free at point of delivery) for medications for dialysis and kidney transplantation was available in only 24% (n = 39) and 30% (n = 50) of countries worldwide, with the proportion increasing in line with country income levels. …”

A qualitative systematic review of anonymous/unspecified living kidney and liver donors' perspectives by Lim, Wen Hui, Chan, Kai En, Ng, Cheng Han, Tan, Darren Jun Hao, Tay, Phoebe Wen Lin, Chin, Yip Han, Yong, Jie Ning, Xiao, Jieling, Fu, Clarissa Elysia, Nah, Benjamin, Tiong, Ho Yee, Syn, Nicholas, Devi, Kamala, Griva, Konstadina, Mak, Loey Lung Yi, Huang, Daniel Q., Fung, James, Siddiqui, Mohammad Shadab, Muthiah, Mark, Tan, Eunice X. X.

“…Methods: A systematic search was conducted on Medline, Embase, CINAHL, PsycINFO, and Web of Science database for qualitative literature regarding unspecified living donors’ motivations and experiences in liver and kidney transplantation. An inductive thematic analysis was conducted to generate themes and supportive subthemes. …”
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