Predicting a kidney transplant patient's pre-transplant functional status based on information from waitlist registration.

ABSTRACT: With over 100,000 patients on the kidney transplant waitlist in 2019, it is important to understand if and how the functional status of a patient may change while on the waitlist. Recorded both at registration and just prior to transplantation, the Karnofsky Performance Score measures a patient's functional status and takes on values ranging from 0 to 100 in increments of 10. Using machine learning techniques, we built a gradient boosting regression model to predict a patient's pre-transplant functional status based on information known at the time of waitlist registration. The model's predictions result in an average root mean squared error of 12.99 based on 5 rolling origin cross validations and 12.94 in a separate out-of-time test. In comparison, predicting that the pre-transplant funct

SUBMITTER: Mark E 

PROVIDER: S-EPMC10105757 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature