<b><i>Introduction:</i></b> A working group on the Oxford classification of IgA nephropathy (IgAN) recently reported that crescents detected in the kidney tissue predicted a worse renal outcome. However, the effect of C1 lesion (crescents in &#x3c;1/4th of all glomeruli) and their volume on the prognosis of IgAN is still unclear. We explored the association of C1 lesion with the renal prognosis in IgAN patients without obvious chronic renal lesions (glomerulosclerosis &#x3c;25%, T score &#x3c;2). <b><i>Methods:</i></b> We investigated 305 biopsy-proven IgAN patients without obvious chronic renal lesions. Clinicopathologic features and treatment modalities were recorded. The patients were divided into several groups according to the presence or absence of a global crescent: no crescent (NC) group, only segmental crescent (SC) group, and global crescent (GC) group. The outcome was the survival from a combined event defined by a ≥15% decline in the estimated glomerular filtration rate (eGFR) after 1 year or ≥30% decline in the eGFR after 2 years. <b><i>Results:</i></b> Among all patients, 75.7% were in the NC group, 14.8% were in the SC group, and 9.5% were in the GC group. Compared with the NC group, patients in the SC group and the GC group had more urine protein, lower eGFR, and presented with more severe pathological change. During a median follow-up of 34.8 (26.16–57.95) months, the combined event occurred in 34 individuals (11.1%). In a multivariate model, the GC group (HR = 2.756, 95% CI = 1.068–7.109) was associated with an increased risk of the combined event. <b><i>Conclusions:</i></b> In IgAN patients without obvious chronic renal lesions, the GC group had more severe clinical and pathological manifestations than in the NC group. GC is an independent risk factor for the progression of IgAN renal function.

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 variables to establish the characteristic variables that are closely related to the prognosis of focal crescent IgAN. Multiple ML algorithms were attempted to establish the prediction models. The area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUROC) were applied to evaluate the predictive performance via three-fold cross validation (namely 2 training sets and 1 validation set). Results RF was used to screen the important features, the top three of which were baseline estimated glomerular filtration rate (eGFR), serum creatine and triglyceride. Ten important features were selected as important predictors for modeling on the basis of data-driven and medical selection, predictors include: age, baseline eGFR, serum creatine, serum triglycerides, complement 3(C3), proteinuria, mean arterial pressure (MAP) and Hematuria, crescents proportion of glomeruli, Global crescent proportion of glomeruli. In a variety of ML algorithms, the support vector machine (SVM) algorithm displayed better predictive performance, with Precision of 0.77, Recall of 0.77, F1-score of 0.73, accuracy of 0.77, AUROC of 79.57%, and AUPRC of 76.5%. Conclusions The SVM model is potentially useful for predicting the prognosis of IgAN patients with focal crescent shape and without obvious chronic renal lesions.