Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease.
Diabetic kidney disease
Diabetic nephropathy
Glomerulonephritis
Kidney biopsy
Nomogram
Non-diabetic kidney disease
Prediction Tool
Journal
International urology and nephrology
ISSN: 1573-2584
Titre abrégé: Int Urol Nephrol
Pays: Netherlands
ID NLM: 0262521
Informations de publication
Date de publication:
Jan 2023
Jan 2023
Historique:
received:
31
12
2021
accepted:
07
07
2022
pubmed:
24
7
2022
medline:
5
1
2023
entrez:
23
7
2022
Statut:
ppublish
Résumé
Differentiating between diabetic kidney disease (DKD) and non-diabetic kidney disease (NDKD) in patients with Type 2 diabetes mellitus (T2DM) is important due to implications on treatment and prognosis. Clinical methods to accurately distinguish DKD from NDKD are lacking. We aimed to develop and validate a novel nomogram to predict DKD in patients with T2DM and proteinuric kidney disease to guide decision for kidney biopsy. A hundred and two patients with Type 2 Diabetes Mellitus (T2DM) who underwent kidney biopsy from 1st January 2007 to 31st December 2016 were analysed. Univariate and multivariate analyses were performed to identify predictive variables and construct a nomogram. The discriminative ability of the nomogram was assessed by calculating the area under the receiver operating characteristic curve (AUROC), while calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration plot. Internal validation of the nomogram was assessed using bootstrap resampling. Duration of T2DM, HbA1c, absence of hematuria, presence of diabetic retinopathy and absence of positive systemic biomarkers were found to be independent predictors of DKD in multivariate analysis and were represented as a nomogram. The nomogram showed excellent discrimination, with a bootstrap-corrected C statistic of 0.886 (95% CI 0.815-0.956). Both the calibration curve and the Hosmer-Lemeshow goodness-of-fit test (p = 0.242) showed high degree of agreement between the prediction and actual outcome, with the bootstrap bias-corrected curve similarly indicating excellent calibration. A novel nomogram incorporating 5 clinical parameters is useful in predicting DKD in type 2 diabetes mellitus patients with proteinuric kidney disease.
Identifiants
pubmed: 35870041
doi: 10.1007/s11255-022-03299-x
pii: 10.1007/s11255-022-03299-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
191-200Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.
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