Evolution of Glycemic Control and Variability after Kidney Transplant

Leyla J. Aouad, Philip Clayton, Kate R. Wyburn, David M. Gracey, Steven J. Chadban

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background The evolution of glycemic changes after kidney transplantation has not been described. We prospectively examined glycemic control and variability over time from transplantation using continuous glucose monitoring (CGM). Method Continuous glucose monitoring devices were fitted for 3 to 5 days at time of transplant, month 3, and month 6 posttransplant. Indices of glucose control (mean glucose, percent time in hyperglycemic range, and Glycemic Risk Assessment Diabetes Equation score) and variability were calculated. An oral glucose tolerance test was performed at month 3. Results Twenty-eight patients (mean age, 45 ± 15 years) were enrolled, 64% male, 75% white, receiving tacrolimus, mycophenolate, and prednisolone (93%). Of 24 patients with complete CGM data at month 0, 3 had prior diabetes and 6 (25%) developed new-onset diabetes after transplant (NODAT). Hyperglycemia (>11.1 mM) was evident in 79% during days 0 to 3 posttransplant, particularly between 1 and 9 pm. Compared with recipients without diabetes, recipients with prior diabetes had higher mean glucose (7.8 mM; 95% confidence interval [CI], 7.4-8.2 vs 9.9 mM; 95% CI, 8.9-10.8; P < 0.001), Glycemic Risk Assessment Diabetes Equation (GRADE) score (4.5; 95% CI, 3.7-5.4 vs 7.8; 95% CI, 5.6-10.4; P = 0.003) and percent time with hyperglycemia. Glycemic control was also inferior in those that subsequently developed NODAT (mean glucose, 8.8 mM; 95% CI, 8.2-9.4; P = 0.004, GRADE: 6.2, 95% CI, 5.2-7.7; P = 0.04 vs no diabetes). Glucose variability was increased in patients with prior diabetes (glucose standard deviation, 1.99; 95% CI, 1.72-2.27 vs 2.97; 95% CI, 2.27-3.67; P = 0.006) but not in NODAT. All measures of glucose control and variability significantly improved over time after transplantation (P < 0.001). Conclusions Dysglycemia is very common after renal transplantation, exhibiting a distinct diurnal pattern of afternoon and evening hyperglycemia. The magnitude of hyperglycemia and variability are maximal in recipients with preexisting diabetes and significant in those who go on to develop NODAT. Dysglycemia improves with time.

LanguageEnglish
Pages1563-1568
Number of pages6
JournalTransplantation
Volume102
Issue number9
DOIs
Publication statusPublished - 1 Sep 2018
Externally publishedYes

ASJC Scopus subject areas

  • Transplantation

Cite this

Aouad, Leyla J. ; Clayton, Philip ; Wyburn, Kate R. ; Gracey, David M. ; Chadban, Steven J. / Evolution of Glycemic Control and Variability after Kidney Transplant. In: Transplantation. 2018 ; Vol. 102, No. 9. pp. 1563-1568.
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title = "Evolution of Glycemic Control and Variability after Kidney Transplant",
abstract = "Background The evolution of glycemic changes after kidney transplantation has not been described. We prospectively examined glycemic control and variability over time from transplantation using continuous glucose monitoring (CGM). Method Continuous glucose monitoring devices were fitted for 3 to 5 days at time of transplant, month 3, and month 6 posttransplant. Indices of glucose control (mean glucose, percent time in hyperglycemic range, and Glycemic Risk Assessment Diabetes Equation score) and variability were calculated. An oral glucose tolerance test was performed at month 3. Results Twenty-eight patients (mean age, 45 ± 15 years) were enrolled, 64{\%} male, 75{\%} white, receiving tacrolimus, mycophenolate, and prednisolone (93{\%}). Of 24 patients with complete CGM data at month 0, 3 had prior diabetes and 6 (25{\%}) developed new-onset diabetes after transplant (NODAT). Hyperglycemia (>11.1 mM) was evident in 79{\%} during days 0 to 3 posttransplant, particularly between 1 and 9 pm. Compared with recipients without diabetes, recipients with prior diabetes had higher mean glucose (7.8 mM; 95{\%} confidence interval [CI], 7.4-8.2 vs 9.9 mM; 95{\%} CI, 8.9-10.8; P < 0.001), Glycemic Risk Assessment Diabetes Equation (GRADE) score (4.5; 95{\%} CI, 3.7-5.4 vs 7.8; 95{\%} CI, 5.6-10.4; P = 0.003) and percent time with hyperglycemia. Glycemic control was also inferior in those that subsequently developed NODAT (mean glucose, 8.8 mM; 95{\%} CI, 8.2-9.4; P = 0.004, GRADE: 6.2, 95{\%} CI, 5.2-7.7; P = 0.04 vs no diabetes). Glucose variability was increased in patients with prior diabetes (glucose standard deviation, 1.99; 95{\%} CI, 1.72-2.27 vs 2.97; 95{\%} CI, 2.27-3.67; P = 0.006) but not in NODAT. All measures of glucose control and variability significantly improved over time after transplantation (P < 0.001). Conclusions Dysglycemia is very common after renal transplantation, exhibiting a distinct diurnal pattern of afternoon and evening hyperglycemia. The magnitude of hyperglycemia and variability are maximal in recipients with preexisting diabetes and significant in those who go on to develop NODAT. Dysglycemia improves with time.",
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Evolution of Glycemic Control and Variability after Kidney Transplant. / Aouad, Leyla J.; Clayton, Philip; Wyburn, Kate R.; Gracey, David M.; Chadban, Steven J.

In: Transplantation, Vol. 102, No. 9, 01.09.2018, p. 1563-1568.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Evolution of Glycemic Control and Variability after Kidney Transplant

AU - Aouad, Leyla J.

AU - Clayton, Philip

AU - Wyburn, Kate R.

AU - Gracey, David M.

AU - Chadban, Steven J.

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Background The evolution of glycemic changes after kidney transplantation has not been described. We prospectively examined glycemic control and variability over time from transplantation using continuous glucose monitoring (CGM). Method Continuous glucose monitoring devices were fitted for 3 to 5 days at time of transplant, month 3, and month 6 posttransplant. Indices of glucose control (mean glucose, percent time in hyperglycemic range, and Glycemic Risk Assessment Diabetes Equation score) and variability were calculated. An oral glucose tolerance test was performed at month 3. Results Twenty-eight patients (mean age, 45 ± 15 years) were enrolled, 64% male, 75% white, receiving tacrolimus, mycophenolate, and prednisolone (93%). Of 24 patients with complete CGM data at month 0, 3 had prior diabetes and 6 (25%) developed new-onset diabetes after transplant (NODAT). Hyperglycemia (>11.1 mM) was evident in 79% during days 0 to 3 posttransplant, particularly between 1 and 9 pm. Compared with recipients without diabetes, recipients with prior diabetes had higher mean glucose (7.8 mM; 95% confidence interval [CI], 7.4-8.2 vs 9.9 mM; 95% CI, 8.9-10.8; P < 0.001), Glycemic Risk Assessment Diabetes Equation (GRADE) score (4.5; 95% CI, 3.7-5.4 vs 7.8; 95% CI, 5.6-10.4; P = 0.003) and percent time with hyperglycemia. Glycemic control was also inferior in those that subsequently developed NODAT (mean glucose, 8.8 mM; 95% CI, 8.2-9.4; P = 0.004, GRADE: 6.2, 95% CI, 5.2-7.7; P = 0.04 vs no diabetes). Glucose variability was increased in patients with prior diabetes (glucose standard deviation, 1.99; 95% CI, 1.72-2.27 vs 2.97; 95% CI, 2.27-3.67; P = 0.006) but not in NODAT. All measures of glucose control and variability significantly improved over time after transplantation (P < 0.001). Conclusions Dysglycemia is very common after renal transplantation, exhibiting a distinct diurnal pattern of afternoon and evening hyperglycemia. The magnitude of hyperglycemia and variability are maximal in recipients with preexisting diabetes and significant in those who go on to develop NODAT. Dysglycemia improves with time.

AB - Background The evolution of glycemic changes after kidney transplantation has not been described. We prospectively examined glycemic control and variability over time from transplantation using continuous glucose monitoring (CGM). Method Continuous glucose monitoring devices were fitted for 3 to 5 days at time of transplant, month 3, and month 6 posttransplant. Indices of glucose control (mean glucose, percent time in hyperglycemic range, and Glycemic Risk Assessment Diabetes Equation score) and variability were calculated. An oral glucose tolerance test was performed at month 3. Results Twenty-eight patients (mean age, 45 ± 15 years) were enrolled, 64% male, 75% white, receiving tacrolimus, mycophenolate, and prednisolone (93%). Of 24 patients with complete CGM data at month 0, 3 had prior diabetes and 6 (25%) developed new-onset diabetes after transplant (NODAT). Hyperglycemia (>11.1 mM) was evident in 79% during days 0 to 3 posttransplant, particularly between 1 and 9 pm. Compared with recipients without diabetes, recipients with prior diabetes had higher mean glucose (7.8 mM; 95% confidence interval [CI], 7.4-8.2 vs 9.9 mM; 95% CI, 8.9-10.8; P < 0.001), Glycemic Risk Assessment Diabetes Equation (GRADE) score (4.5; 95% CI, 3.7-5.4 vs 7.8; 95% CI, 5.6-10.4; P = 0.003) and percent time with hyperglycemia. Glycemic control was also inferior in those that subsequently developed NODAT (mean glucose, 8.8 mM; 95% CI, 8.2-9.4; P = 0.004, GRADE: 6.2, 95% CI, 5.2-7.7; P = 0.04 vs no diabetes). Glucose variability was increased in patients with prior diabetes (glucose standard deviation, 1.99; 95% CI, 1.72-2.27 vs 2.97; 95% CI, 2.27-3.67; P = 0.006) but not in NODAT. All measures of glucose control and variability significantly improved over time after transplantation (P < 0.001). Conclusions Dysglycemia is very common after renal transplantation, exhibiting a distinct diurnal pattern of afternoon and evening hyperglycemia. The magnitude of hyperglycemia and variability are maximal in recipients with preexisting diabetes and significant in those who go on to develop NODAT. Dysglycemia improves with time.

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