Prediction of prognosis in immunoglobulin a nephropathy patients with focal crescent by machine learning.

ABSTRACT:

Background and objectives

Immunoglobulin a nephropathy (IgAN) is the most common primary glomerular disease in the world, with different clinical manifestations, varying severity of pathological changes, common complications of crescent formation in different proportions, and great individual heterogeneous in clinical outcomes. Therefore, we aim to develop a machine learning (ML) based predictive model for predicting the prognosis of IgAN with focal crescent formation and without obvious chronic renal lesions (glomerulosclerosis <25%).

Materials

We retrospectively reviewed biopsy-proven IgAN patients in our hospital and cooperative hospital from 2005 to 2017. The method of feature importance of random forest (RF) was applied to conduct feature exploration of feature variable

SUBMITTER: Lin X 

PROVIDER: S-EPMC8906594 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature