Predicting long-term kidney allograft outcomes: pitfalls and progress.

Abstract:

:Early identification of kidney transplant recipients at risk of progressive allograft dysfunction may allow clinicians to provide closer monitoring and more aggressive risk factor modification. In this issue, Raynaud et al. presented a latent class model that clustered kidney transplant recipients into 8 risk categories of post-transplant kidney function loss. This commentary discusses some of the advantages, but also challenges, of the use of latent class analyses, including the clinical applicability of models that are often derived from such approaches.

journal_name

Kidney Int

journal_title

Kidney international

authors

Dinh A,McCulloch CE,Ku E

doi

10.1016/j.kint.2020.07.031

subject

Has Abstract

pub_date

2021-01-01 00:00:00

pages

24-26

issue

1

eissn

0085-2538

issn

1523-1755

pii

S0085-2538(20)30946-7

journal_volume

99

pub_type

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