Continuous glucose monitoring in kidney transplant recipients: a narrative review

TL;DR

This review discusses how continuous glucose monitoring (CGM) can improve diabetes management and predict post-transplant diabetes in kidney transplant patients.

Contribution

The paper highlights CGM's potential for early detection and management of dysglycemia in kidney transplant recipients, which is not yet part of standard care.

Findings

CGM outperforms traditional methods in detecting hyperglycemia and glycemic variability after kidney transplantation.

CGM metrics predict post-transplant diabetes mellitus (PTDM) with high sensitivity and specificity.

Poor glycemic control detected by CGM is linked to acute rejection and reduced graft survival.

Abstract

Continuous glucose monitoring (CGM) has transformed diabetes management, offering real-time and dynamic insights into glucose variability and addressing the limitations of traditional glucose assessment methods. Kidney transplantation, the most common solid organ transplant, carries a considerable burden of post-transplant diabetes mellitus (PTDM), which is linked to increased cardiovascular events, graft dysfunction, and increased mortality. This review explores the role of CGM in kidney transplant recipients, particularly its impact on glycemic profiles and its predictive value for post-transplant diabetes mellitus (PTDM). At the time of this review, CGM had not yet been incorporated into standard transplant care protocols. Evidence shows that perioperative CGM outperforms traditional tests in identifying frequent hyperglycemia and glycemic variability in the first weeks after transplantation, enabling enhanced glycemic control and improving the recipient’s clinical outcome. Studies demonstrate higher glucose variability in kidney only recipients compared to other organ recipients, and in type 2 diabetes patients compared to those with PTDM. Poor perioperative glycemic control and glycemic variability detected by CGM have been linked to acute rejection and reduced graft survival. CGM-derived metrics outperform conventional glucose measures in predicting PTDM. CGM metric thresholds within the first month post-transplant achieved sensitivities above 85% and specificities up to 83% for PTDM risk. CGM-guided adjustment of immunosuppressants and steroid dosing have been shown to reduce hyperglycemia and variability. Comparative studies indicate that glycosylated hemoglobin A1c correlates poorly with CGM in the early post-transplant period, often misclassifying patients as normoglycemic. CGM appears to offer clinically relevant insights for the early detection, prediction, and management of dysglycemia in kidney transplant recipients.