Body Fat Area as a Predictive Marker of New-Onset Diabetes Mellitus After Kidney Transplantation

Taoka, Rikiya; Tanaka, Kenichi; Sofue, Tadashi; Abe, Yohei; Naito, Hirohito; Miyauchi, Yoshimasa; Matsuoka, Yuki; Tajima, Motofumi; Kato, Takuma; Tsunemori, Hiroyuki; Ueda, Nobufumi; Nishiyama, Yoshihiro; Minamino, Tetsuo; Sugimoto, Mikio; Kakehi, Yoshiyuki

doi:10.1016/j.transproceed.2019.08.031

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…Multiple studies have indicated that age, current smoking, BMI, family history of diabetes, history of hypertension and tacrolimus use are risk factors for NODM in patients taking ISDs following renal transplantation and for glomerular disease. 5 , 21 , 22 , 23 , 24 Our previous study demonstrated that age is an independent risk factor for NODM in patients with idiopathic membranous nephropathy treated with ISDs. 6 Glucose tolerance progressively declines with age, 25 which may be caused by the shortening of telomeres in β and α cells 26 and by age‐related changes in DNA methylation in human islet cells.…”

Section: Resultsmentioning

confidence: 94%

LASSO ‐derived nomogram predicting new‐onset diabetes mellitus in patients with kidney disease receiving immunosuppressive drugs

Shao

Luo

Yuan

et al. 2022

Clinical Pharmacy Therapeu

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What is known and objective Patients with kidney disease receiving immunosuppressive drugs (ISDs) (tacrolimus, cyclosporine and glucocorticoids) have a high risk of developing new‐onset diabetes mellitus (NODM). We aimed to establish a precise and convenient model for predicting NODM in patients receiving immunosuppressive drugs. Methods This retrospective study recruited 1883 patients receiving ISDs between January 2010 and October 2018. The occurrence of NODM was the primary endpoint. The patients were randomly divided into training (n = 1318) and validation cohorts (n = 565) at a 7:3 ratio. A nomogram was established based on a least absolute shrinkage and selection operator (LASSO)‐derived logistic regression model. The nomogram's discrimination and calibration abilities were evaluated in both cohorts using the Hosmer‐Lemeshow test and calibration curves. Decision curve analysis (DCA) was used to evaluate the net benefit of the predictive efficacy. Results and discussion Amongst the 1883 patients with kidney disease receiving immunosuppressive drugs, 375 (28.5%) and 169 (29.9%) developed NODM in the training (n = 1318) and validation cohorts (n = 565), respectively. Nine clinic predictors were included in this LASSO‐derived nomogram, which is easy to be operated clinically. The discriminative ability, determined by the area under the receiver operating characteristic curve (AUC), was 0.816 (95% confidence interval [CI] 0.790–0.841) and 0.831 (95%CI 0.796–0.867) in the training and validation cohorts, respectively. Calibration was confirmed with the Hosmer‐Lemeshow test in the training and validation cohorts (p = 0.238, p = 0.751, respectively). What is new and conclusion Nearly one‐third of patients with kidney disease receiving immunosuppressive drugs developed NODM. The nomogram established in this study may aid in predicting the occurrence of NODM in patients with kidney disease receiving immunosuppressive drugs.

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Section: Resultsmentioning

confidence: 94%

LASSO ‐derived nomogram predicting new‐onset diabetes mellitus in patients with kidney disease receiving immunosuppressive drugs

Shao

Luo

Yuan

et al. 2022

Clinical Pharmacy Therapeu

View full text Add to dashboard Cite

show abstract

“… 29 In particular, visceral adipose tissue content has been indicated as a strong predictor of new-onset diabetes after transplantation. 30 , 31 For female patients, the problem was more pronounced. These findings may indicate that overweight and obese patients, especially if female, should be referred to tailored weight management programs (including physical activity and nutrition), whereas further patient characteristics eg preexisting diabetes should be taken into account when delivering the intervention.…”

Section: Discussionmentioning

confidence: 99%

First Testing of Literature-Based Models for Predicting Increase in Body Weight and Adipose Tissue Mass After Kidney Transplantation

et al. 2022

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Introduction: Weight gain is a risk factor for poor clinical outcomes following kidney transplantation. Research Question: This study’s aim was a first testing of 2 models to identify patients early after kidney transplantation who are at risk for weight gain and increase in adipose tissue mass in the first year after kidney transplantation. Design: The literature-based models were evaluated on longitudinal data of 88, respectively 79 kidney transplant recipients via ordinary and Firth regression, using gains ≥ 5% in weight and adipose tissue mass respectively as primary and secondary endpoints. Results: The models included physical activity, smoking cessation at time of kidney transplantation, self-reported health status, depressive symptomatology, gender, age, education, baseline body mass index and baseline trunk fat as predictors. Area under the curve was 0.797 (95%-CI 0.702 to 0.893) for the weight model and 0.767 (95%-CI 0.656 to 0.878) for the adipose tissue mass model—showing good, respectively fair discriminative ability. For weight gain ≥ 5%, main risk factors were smoking cessation at time of transplantation (OR 16.425, 95%-CI 1.737-155.288) and better self-reported baseline health state (OR 1.068 for each 1-unit increase, 95%-CI 1.012-1.128). For the adipose tissue mass gain ≥ 5%, main risk factor was overweight/obesity (BMI ≥ 25) at baseline (odds ratio 7.659, 95%-CI 1.789-32.789). Conclusions: The models have potential to assess patients' risk for weight or adipose tissue mass gain during the year after transplantation, but further testing is needed before implementation in clinical practice.

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Body Fat Area as a Predictive Marker of New-Onset Diabetes Mellitus After Kidney Transplantation

Cited by 2 publications

References 19 publications

LASSO ‐derived nomogram predicting new‐onset diabetes mellitus in patients with kidney disease receiving immunosuppressive drugs

LASSO ‐derived nomogram predicting new‐onset diabetes mellitus in patients with kidney disease receiving immunosuppressive drugs

First Testing of Literature-Based Models for Predicting Increase in Body Weight and Adipose Tissue Mass After Kidney Transplantation

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