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A simplified prediction model for end-stage kidney disease in patients with diabetes.

ABSTRACT: This study aimed to develop a simplified model for predicting end-stage kidney disease (ESKD) in patients with diabetes. The cohort included 2549 individuals who were followed up at Kyushu University Hospital (Japan) between January 1, 2008 and December 31, 2018. The outcome was a composite of ESKD, defined as an eGFR < 15 mL min^-1 [1.73 m]^-2, dialysis, or renal transplantation. The mean follow-up was 5.6 [Formula: see text] 3.7 years, and ESKD occurred in 176 (6.2%) individuals. Both a machine learning random forest model and a Cox proportional hazard model selected eGFR, proteinuria, hemoglobin A1c, serum albumin levels, and serum bilirubin levels in a descending order as the most important predictors among 20 baseline variables. A model using eGFR, proteinuria and hemoglobin A1c showed a relatively good performance in discrimination (C-statistic: 0.842) and calibration (Nam and D'Agostino [Formula: see text]² statistic: 22.4). Adding serum albumin and bilirubin levels to the model further improved it, and a model using 5 variables showed the best performance in the predictive ability (C-statistic: 0.895, [Formula: see text]² statistic: 7.7). The accuracy of this model was validated in an external cohort (n = 5153). This novel simplified prediction model may be clinically useful for predicting ESKD in patients with diabetes.

SUBMITTER: Inoguchi T

PROVIDER: S-EPMC9304378 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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A simplified prediction model for end-stage kidney disease in patients with diabetes.

Inoguchi Toyoshi T Okui Tasuku T Nojiri Chinatsu C Eto Erina E Hasuzawa Nao N Inoguchi Yukihiro Y Ochi Kentaro K Takashi Yuichi Y Hiyama Fujiyo F Nishida Daisuke D Umeda Fumio F Yamauchi Teruaki T Kawanami Daiji D Kobayashi Kunihisa K Nomura Masatoshi M Nakashima Naoki N

Scientific reports 20220721 1

This study aimed to develop a simplified model for predicting end-stage kidney disease (ESKD) in patients with diabetes. The cohort included 2549 individuals who were followed up at Kyushu University Hospital (Japan) between January 1, 2008 and December 31, 2018. The outcome was a composite of ESKD, defined as an eGFR < 15 mL min<sup>-1</sup> [1.73 m]<sup>-2</sup>, dialysis, or renal transplantation. The mean follow-up was 5.6 [Formula: see text] 3.7 years, and ESKD occurred in 176 (6.2%) indivi ...[more]

PMID: 35864124

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Project description:BackgroundObesity often initiates or coexists with metabolic abnormalities. This study aimed to investigate the pathological characteristics and the independent or mutual relations of obesity and metabolic abnormalities with end-stage kidney disease (ESKD) in patients with type 2 diabetes (T2D) and associated diabetic kidney disease (DKD).MethodsA total of 495 Chinese patients with T2D and biopsy-confirmed DKD between 2003 and 2020 were enrolled in this retrospective study. The metabolic phenotypes were based on the body weight index (BMI)-based categories (obesity, BMI ≥ 25.0 kg/m2) and metabolic status (metabolically unhealthy status, ≥ 1 criterion National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATP III) excluding waist circumference and hyperglycemia) and were categorized into four types: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO). The pathological findings were defined by the Renal Pathology Society classification. Cox proportional hazards models were used to estimate hazard ratios (HRs) for ESKD.ResultsThere are 56 (11.3%) MHNO patients, 28 (5.7%) MHO patients, 176 (35.6%) MUNO patients, and 235 (47.5%) MUO patients. The high prevalence of the Kimmelstiel-Wilson nodule and severe mesangial expansion were associated with obesity, whereas severe IFTA was related to metabolically unhealthy status. In the multivariate analysis, the adjusted HR (aHR) was 2.09 [95% confidence interval (CI) 0.99-4.88] in the MHO group, 2.16 (95% CI 1.20-3.88) in the MUNO group, and 2.31 (95% CI 1.27-4.20) in the MUO group compared with the MHNO group. Furthermore, the presence of obesity was insignificantly associated with ESKD compared with non-obese patients (aHR 1.22, 95% CI 0.88-1.68), while the metabolically unhealthy status was significantly associated with ESKD compared to the metabolically healthy status in the multivariate analysis (aHR 1.69, 95% CI 1.10-2.60).ConclusionObesity itself was insignificantly associated with ESKD; however, adding a metabolically unhealthy status to obesity increased the risk for progression to ESKD in T2D and biopsy-proven DKD.

Dataset Information

A simplified prediction model for end-stage kidney disease in patients with diabetes.

Publications

A simplified prediction model for end-stage kidney disease in patients with diabetes.

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