PMID- 35870041
OWN - NLM
STAT- MEDLINE
DCOM- 20230104
LR  - 20230111
IS  - 1573-2584 (Electronic)
IS  - 0301-1623 (Linking)
VI  - 55
IP  - 1
DP  - 2023 Jan
TI  - Development and validation of a novel nomogram to predict diabetic kidney disease 
      in patients with type 2 diabetic mellitus and proteinuric kidney disease.
PG  - 191-200
LID - 10.1007/s11255-022-03299-x [doi]
AB  - PURPOSE: 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. METHODS: 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. RESULTS: 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. 
      CONCLUSIONS: A novel nomogram incorporating 5 clinical parameters is useful in 
      predicting DKD in type 2 diabetes mellitus patients with proteinuric kidney 
      disease.
CI  - (c) 2022. The Author(s), under exclusive licence to Springer Nature B.V.
FAU - Tan, Hui Zhuan
AU  - Tan HZ
AUID- ORCID: 0000-0003-4899-6399
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore. tan.hui.zhuan@singhealth.com.sg.
FAU - Choo, Jason Chon Jun
AU  - Choo JCJ
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
FAU - Fook-Chong, Stephanie
AU  - Fook-Chong S
AD  - Duke-NUS Medical School, Programme in Health Services and Systems Research, 
      Singapore, Singapore.
FAU - Chin, Yok Mooi
AU  - Chin YM
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
FAU - Chan, Choong Meng
AU  - Chan CM
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
FAU - Tan, Chieh Suai
AU  - Tan CS
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
FAU - Woo, Keng Thye
AU  - Woo KT
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
FAU - Kwek, Jia Liang
AU  - Kwek JL
AD  - Department of Renal Medicine, Singapore General Hospital, Academia Level 3, 20 
      College Road, Singapore, 169856, Singapore.
LA  - eng
PT  - Journal Article
DEP - 20220723
PL  - Netherlands
TA  - Int Urol Nephrol
JT  - International urology and nephrology
JID - 0262521
SB  - IM
MH  - Humans
MH  - Nomograms
MH  - *Diabetes Mellitus, Type 2/complications
MH  - Retrospective Studies
MH  - *Diabetic Nephropathies/diagnosis
MH  - Prognosis
OTO - NOTNLM
OT  - Diabetic kidney disease
OT  - Diabetic nephropathy
OT  - Glomerulonephritis
OT  - Kidney biopsy
OT  - Nomogram
OT  - Non-diabetic kidney disease
OT  - Prediction Tool
EDAT- 2022/07/24 06:00
MHDA- 2023/01/05 06:00
CRDT- 2022/07/23 11:16
PHST- 2021/12/31 00:00 [received]
PHST- 2022/07/07 00:00 [accepted]
PHST- 2022/07/24 06:00 [pubmed]
PHST- 2023/01/05 06:00 [medline]
PHST- 2022/07/23 11:16 [entrez]
AID - 10.1007/s11255-022-03299-x [pii]
AID - 10.1007/s11255-022-03299-x [doi]
PST - ppublish
SO  - Int Urol Nephrol. 2023 Jan;55(1):191-200. doi: 10.1007/s11255-022-03299-x. Epub 
      2022 Jul 23.