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A grading system that predicts the risk of dialysis induction in IgA nephropathy patients based on the combination of the clinical and histological severity.

Hideo OkonogiTetsuya KawamuraKensuke JohKentaro KoikeYoichi MiyazakiMakoto OguraNobuo TsuboiKeita HiranoMasato MatsushimaTakashi YokooSatoshi HorikoshiYusuke SuzukiTakashi YasudaSayuri ShiraiTakanori ShibataMotoshi HattoriYuko AkiokaRitsuko KatafuchiAkinori HashiguchiSatoshi HisanoAkira ShimizuKenjiro KimuraShoichi MaruyamaSeiichi MatsuoYasuhiko Tominonull null
Published in: Clinical and experimental nephrology (2018)
Histological classification is essential in the clinical management of immunoglobulin A nephropathy (IgAN). However, there are limitations in predicting the prognosis of IgAN based on histological information alone, which suggests the need for better prognostic models. Therefore, we defined a prognostic model by combining the grade of clinical severity with the histological grading system by the following processes. We included 270 patients and explored the clinical variables associated with progression to end-stage renal disease (ESRD). Then, we created a predictive clinical grading system and defined the risk grades for dialysis induction by a combination of the clinical grade (CG) and the histological grade (HG). A logistic regression analysis revealed that the 24-h urinary protein excretion (UPE) and the estimated glomerular filtration rate (eGFR) were significant independent variables. We selected UPE of 0.5 g/day and eGFR of 60 ml/min/1.73 m2 as the threshold values for the classification of CG. The risk of progression to ESRD of patients with CG II and III was significantly higher than that of patients with CG I. The patients were then re-classified into nine compartments based on the combination of CG and HG. Furthermore, the nine compartments were grouped into four risk groups. The risk of ESRD in the moderate, high, and super-high-risk groups was significantly higher than that in the low-risk group. Herein, we are giving a detailed description of our grading system for IgA nephropathy that predicted the risk of dialysis based on the combination of CG and HG.
Keyphrases
  • end stage renal disease
  • chronic kidney disease
  • peritoneal dialysis
  • small cell lung cancer
  • ejection fraction
  • newly diagnosed
  • machine learning
  • prognostic factors
  • high intensity
  • living cells
  • aqueous solution