Prevalence of abnormal glucose metabolism in Chinese renal transplant recipients: a single centre study

Chan, Hoi Wong; Cheung, ST; Liu, Yan Lun; Chan, Yiu Han; Wong, Hai Ming; Chak, Wai Leung; Choi, Koon Shing; Chau, Kwong Wing; Li, Chun Sang

doi:10.1093/ndt/gfn246

Cited by 14 publications

(13 citation statements)

References 28 publications

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“…Studies that have examined the prevalence of steroid diabetes in different diseases have reported varying results . It is unlikely that the development of hyperglycemia is related only to the existence of an underlying disease, because abnormalities in glucose metabolism have also been observed in experimental studies in healthy subjects …”

Section: Introductionmentioning

confidence: 99%

Glucocorticoid‐induced hyperglycemia (糖皮质激素诱导的高血糖)

Pérez

Jansen-Chaparro

Saigí

et al. 2013

Journal of Diabetes

211

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Corticosteroid-induced hyperglycemia is a common medical problem that can lead to frequent emergency room visits, hospital admissions and prolonged hospital stay, in addition to the well known morbidity associated with hyperglycemia. However, the diagnosis and treatment of corticosteroid-induced hyperglycemia is surprisingly undervalued by most professionals, probably because of the lack of quality studies to determine specific strategies of action. In the present review, we discuss the pathophysiology of corticosteroid-induced hyperglycemia, focusing on diverse patterns of hyperglycemia induced by the different formulations, and provide clues for diagnosis based on the duration of treatment and the administration schedule of corticosteroids. We propose a treatment strategy based on both the pathophysiology of the process and the mechanism of action of different corticosteroids, and take into account dosing and administration timing to predict the duration of therapy. Finally, we propose treatment goals that differ slightly between the transient and continuous use of corticosteroids based on evidence from clinical practice guidelines of diabetes care both in ambulatory and hospital settings.

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Section: Introductionmentioning

confidence: 99%

Glucocorticoid‐induced hyperglycemia (糖皮质激素诱导的高血糖)

Pérez

Jansen-Chaparro

Saigí

et al. 2013

Journal of Diabetes

211

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“…In light of several documented risk factors of NODAT, it has been recommended to target the modifiable factors, two of the most promising ones being obesity and triglyceride levels. 45,46 Regarding the factor of obesity (at the time of transplantation), this has been repeatedly shown to be linked with heightened risk of developing glucose metabolism disorder or NODAT after transplantation. 8,[46][47][48] Optimization of the bodyweight or body mass index (BMI) is therefore of potential benefit in terms of decreasing the risk of NODAT.…”

Section: How Should We Tackle and Prevent Nodat?mentioning

confidence: 99%

“…45,46 Regarding the factor of obesity (at the time of transplantation), this has been repeatedly shown to be linked with heightened risk of developing glucose metabolism disorder or NODAT after transplantation. 8,[46][47][48] Optimization of the bodyweight or body mass index (BMI) is therefore of potential benefit in terms of decreasing the risk of NODAT. Furthermore, our group has previously demonstrated that a baseline BMI of 25 kg/m 2 or more among Asian renal transplant recipients confers more than fourfold risk of graft loss.…”

Section: How Should We Tackle and Prevent Nodat?mentioning

confidence: 99%

Review article: New‐onset diabetes after transplantation

Chow

2008

Nephrology

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SUMMARY:This article reviews the clinical aspects and epidemiological links between diabetes mellitus and renal transplantation, and emphasizes areas that warrant further clarification. In particular, we summarize the data for various immunosuppression medications on the risk of new-onset diabetes after transplantation (NODAT). An increased mechanistic understanding of new-onset diabetes might provide new insights into the pathophysiology of this complication after solid organ transplantation. Claims that selecting immunosuppression regimen to minimize the risk of NODAT, nevertheless, are currently not supported by the scientific published work. Intuitively, strategies that aim to change the underlying biology of the disease process of NODAT are desirable; among them, lifestyle modification is currently the most promising in terms of real benefit with the least risk.

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“…Early detection of PTDM risk factors and PTDM management are concerns of posttransplantation care. Several risk factors for PTDM have been reported, including age, body mass index, hepatitis C infection [6][7][8][9][10], and immunosuppressive medication [7,11].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Mechanism of Skeletal Muscle in a Tacrolimus-Induced Posttransplantation Diabetes Mellitus Model on Gene Expression Profiles

Zheng

Wang

Zhang

et al. 2020

Journal of Diabetes Research

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Objective. Posttransplantation diabetes mellitus (PTDM) is a known complication of transplantation that affects the prognosis. Tacrolimus (Tac or FK506) is a widely used immunosuppressant that has been reported to be a risk factor for PTDM and to further induce complications in heart and skeletal muscles, but the mechanism is still largely unknown. In our preliminary experiments, we found that after Tac treatment, blood glucose increased, and the weight of skeletal muscle declined. Here, we hypothesize that tacrolimus can induce PTDM and influence the atrophy of skeletal muscle. Methods. We designed preliminary experiments to establish a tacrolimus-induced PTDM model. Gene expression profiles in quadriceps muscle from this rat model were characterized by oligonucleotide microarrays. Then, differences in gene expression profiles in muscle from PTDM rats that received tacrolimus and control subjects were analyzed by using GeneSpring GX 11.0 software (Agilent). Functional annotation and enrichment analysis of differentially expressed genes (DEGs) helped us identify clues for the side effects of tacrolimus. Results. Our experiments found that the quadriceps in tacrolimus-induced PTDM group were smaller than those in the control group. The study identified 275 DEGs that may be responsible for insulin resistance and the progression of PTDM, including 86 upregulated genes and 199 downregulated genes. GO and KEGG functional analysis of the DEGs showed a significant correlation between PTDM and muscle development. PPI network analysis screened eight hub genes and found that they were related to troponin and tropomyosin. Conclusions. This study explored the molecular mechanism of muscle atrophy in a tacrolimus-induced PTDM model by bioinformatics analyses. We identified 275 DEGs and identified significant biomarkers for predicting the development and progression of tacrolimus-induced PTDM.

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Prevalence of abnormal glucose metabolism in Chinese renal transplant recipients: a single centre study

Abstract: AGM is common in our renal transplant recipients.

Cited by 14 publications

References 28 publications

Glucocorticoid‐induced hyperglycemia (糖皮质激素诱导的高血糖)

Glucocorticoid‐induced hyperglycemia (糖皮质激素诱导的高血糖)

Review article: New‐onset diabetes after transplantation

Exploring the Mechanism of Skeletal Muscle in a Tacrolimus-Induced Posttransplantation Diabetes Mellitus Model on Gene Expression Profiles

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