Background: De novo post-transplant diabetes mellitus (PTDM) is a frequent complication among renal transplant recipients; it confers a high risk for graft failure and patient mortality. This single-centre study aimed to determine the incidence and risk factors of PTDM and its effects on graft outcome and mortality. Methods: In a single-centre longitudinal cohort analysis of 383 non-diabetic renal transplant follow-up recipients, outcomes were analysed through a detailed chart review. We hypothesized that different donor and recipient characters such as age, gender, and HLA mismatch would affect PTDM development in renal transplant recipients. PTDM is defined on basis of fasting plasma sugar (≥7 mmol/L or ≥126 mg/dL), random plasma sugar (≥11.1 mmol/L or ≥200 mg/dL), and glycated haemoglobin (HBA1C: >6.5% or 48 mmol/mol). We assessed PTDM incidence, risk factors, and its effect on patient mortality and graft outcome using Cox regression. Results: The mean age at the time of transplantation was 35.70 (±14.27) years, and 50.91% were male. PTDM incidence in the study period was 23.30%. Independent risk factors include older age at the time of transplantation, cyclosporine immunosuppression, cytomegalovirus, and hepatitis C virus infection. PTDM is not associated with graft dysfunction, whereas it significantly carries high mortality. Conclusion: PTDM is common among renal transplant recipients. Older age at the time of transplantation, cyclosporine immunosuppression, cytomegalovirus, and hepatitis C virus are risk factors. PTDM carries high mortality but is not associated with graft failure.

Hundreds of thousands of patients’ lives have been changed with solid organ transplantation worldwide since the first renal transplant was done in 1954 between identical twins. Challenges like infection and graft rejection are dealt with advancements in immunosuppressive medications and antimicrobials [1]. Importantly, nevertheless, cardiovascular disease is associated with higher morbidity and mortality in renal transplant recipients, and de novo post-transplant diabetes mellitus (PTDM) is considered a significant contributor to this adverse outcome. Diagnostic criteria for PTDM are based on fasting plasma sugar (≥7 mmol/L or ≥126 mg/dL), random plasma sugar (≥11.1 mmol/L or ≥200 mg/dL), and glycated haemoglobin (HBA1C: >6.5% or 48 mmol/mol) (Table 1) [2‒4]; however, HBA1C in early post-operative period in renal disease patients can be affected by iron deficiency, blood loss, or blood transfusion; therefore, for PTDM screening, HBA1C should merely be used after 3 months of transplantation [5]. Early hyperglycaemia after surgery is quite common, and it may or may not be associated with long-term hyperglycaemia (PTDM). Common causes of this hyperglycaemia are stress, infection, pain, initial high dosage of immunosuppressive medications, and feeding (enteral and parenteral) [6]. PTDM affects 10–40% of renal transplant recipients [7]; it also confers a higher risk of graft failure and mortality as compared to those recipients who do not suffer from PTDM [8]. The central idea of this study is to report the incidence and risk factors of PTDM among our population in Dubai and its effect on graft function and mortality in renal transplant recipients (Table 1).

Table 1.
1. Fasting glucose >126 mg/dL (7 mmol/L) on more than one occasion 
2. Random glucose >200 mg/dL (11.1 mmol/L) with symptoms 
3. Two-hour glucose after a 75-g OGTT of >200 mg/dL (11.1 mmol/L) 
4. HbA1c >6.5% 
1. Fasting glucose >126 mg/dL (7 mmol/L) on more than one occasion 
2. Random glucose >200 mg/dL (11.1 mmol/L) with symptoms 
3. Two-hour glucose after a 75-g OGTT of >200 mg/dL (11.1 mmol/L) 
4. HbA1c >6.5% 

We conducted a retrospective observational study to identify the incidences and risk factors of PTDM and its effect on graft survival in renal transplant recipients, who attended Dubai Hospital renal transplant clinic from January 1, 1990, to December 31, 2020. Mean follow-up period was 11.7 ± 3.3 years. Patients gave their consent to use their data for research by signing the general consent available in the medical record system. PTDM was diagnosed based on clinical presentation, plasma glucose (fasting and random), and HBA1C. Patients with ages less than 14 years were excluded from this study.

Data Collection

Medical records of the study population were reviewed using patients’ manual medical files and electronic medical records (Epic Hyperspace, year 2019) to retrieve patients’ demographic characteristics, follow-up visit notes, hospital admission records, and laboratory findings. Demographic characteristics include age, sex, and comorbidities. Laboratory data consist of plasma glucose (fasting and random), HBA1C, renal functions, urine studies (urine routine, urine protein-creatinine ratio), and serum albumin. Normal ranges of these parameters were provided by the laboratory. Diagnostic criteria for PTDM are based on any of the following: persistent fasting plasma sugar (≥7 mmol/L or ≥126 mg/dL), random plasma sugar (≥11.1 mmol/L or ≥200 mg/dL) with symptoms, and HBA1C (>6.5% or 48 mmol/mol) were solely used to diagnose PTDM after 1 year (Table 1). Plasma glucose readings, renal functions, urine studies on follow-up visits, and HBA1C readings for three months were monitored. Graft dysfunction is defined as a 15% increase in creatinine from baseline [9]. Primary outcome of study was to report incidence of PTDM, whereas secondary outcome was to determine effect of PTDM on renal graft survival and mortality in renal transplant recipients.

Statistical Analysis

Continuous variables are described as mean ± standard deviation and median with interquartile range values for normally distributed and non-normally distributed data, respectively. Categorical variables were presented as frequency and percentage. Independent t test and Mann-Whitney test were used for normally distributed and non-normally distributed continuous variables, respectively, and categorical data were compared with help of Pearson’s χ2 test or Fischer’s exact test. The correlation between risk factors and PTDM was analysed by Cox regression, where PTDM was considered a time-dependent variable because this complication started at different times following the transplant. A p value of <0.05 was considered statistically significant. SPSS version 20 was used for statistical analysis.

Baseline Characteristics

We could retrieve data of a total of 512 renal transplant recipients followed up in our transplant clinic during the study period (January 1991 to December 2021). PTDM patients’ demographic characteristics, graft survival, and mortality rate were compared with those of non-diabetic renal transplant recipients so patients known to have diabetes mellitus before renal transplantation were excluded (n = 129). Basic patients’ characteristics are shown in Table 2. During the mean follow-up period of 11.7 ± 3.3 years, out of 383 patients, 118 (n = 23.30%) renal transplant recipients suffered from PTDM. Overall mean age at the time of transplantation was 35.70 (±14.27) years, and more than half of study population was male (50.91%). PTDM patients belonged to relatively higher age group than non-diabetics (40.48 vs. 34 years, p = <0.05), also there were more females than males (23.72% vs. 63.01%, p = <0.05). Chronic glomerulonephritis (38.13 vs. 36.22), hypertension (12.71 vs. 15.09), and obstructive uropathy (6.77 vs. 8.97) were common causes of renal failure in PTDM and non-diabetic renal transplant recipients. Generally, 72.89% and 24.93% (n = 269 and 92) organ donors were predominantly live unrelated and related, respectively, whereas cadaver organ donors were 2.16% (n = 8) only. In the PTDM group as compared to non-diabetics, organ donors were more among live unrelated (PTDM vs. non-diabetics: 77.96% vs. 70.51%, p = 0.16). Prednisolone (93.21%, n = 357) is the most commonly used immunosuppressive medication in our study population, followed by mycophenolate mofetil (MMF) (60.31%, n = 231), cyclosporine (57.44%, n = 222), tacrolimus (31.59%, n = 121), azathioprine (21.14%, n = 81), and sirolimus (10.96%, n = 42), also 84.85% (n = 325) renal transplant recipients were using triple immunosuppression, and cyclosporine, MMF, and prednisolone were the most common combination used (28.45%, n = 109). In the PTDM group as compared to non-diabetic renal transplant recipients, prednisolone (PTDM vs. non-diabetics: 96.61% vs. 91.69%, p = 0.07), cyclosporine (PTDM vs. non-diabetics: 66.94% vs. 53.20%, p = 0.01), and sirolimus (PTDM vs. non-diabetics: 15.25% vs. 9.05%, p = 0.07) were used more, and only cyclosporine is statistically associated with PTDM. Whereas MMF (PTDM vs. non-diabetics: 56.77% vs. 61.88%, p = 0.34), tacrolimus (PTDM vs. non-Diabetics: 27.96% vs. 33.20%, p = 0.30), azathioprine (PTDM vs. non-diabetics: 20.33% vs. 21.50%, p = 0.79) were used more by non-diabetics relatively. 92.37% (n = 109) of PTDM population was on triple immunosuppressive medications compared to 81.57% (n = 216, p = 0.007) of non-diabetics, and cyclosporine, MMF, and prednisolone were the most common combinations used in both groups (PTDM vs. non-diabetics: 29.66% vs. 27.54%). The overall median creatinine for our transplant population was 1.2 mg/dL (0.5–1.7), also 19.84 (n = 76) people lost their graft and reached chronic kidney disease stage 5. As compared to PTDM, renal functions were relatively well preserved (PTDM vs. non-diabetics: 1.58 ± 0.99 vs. 0.7 ± 0.89, p = 0.517) in non-diabetics; also lesser number of patients (PTDM vs. non-diabetics: 22.80% vs. 19.53%, p = 0.322) lost their graft and reached chronic kidney disease stage 5.

Table 2.

Patients’ characteristics

Patients’ characteristicsRenal transplant recipients, n = 383PTDM, n = 118, 23.30%Non-PTDM, n = 265, 76.70%p value
Age, years, mean (±SD) 49.51 (±14.85) 54.79 (±12.48) 47.22 (±15.23) <0.05 
Age at transplantation, years, mean (±SD) 35.70 (±14.27) 40.48 (±12.59) 34 (±14.48) <0.05 
Sex (male) 195 (50.91) 28 (23.72) 167 (63.01) <0.05 
Primary disease, n (%) 
 Chronic glomerulonephritis 141 (36.81) 45 (38.13) 96 (36.22)  
 Hypertension 55 (14.36) 15 (12.71) 40 (15.09)  
 Chronic allograft nephropathy 14 (3.65) 8 (6.77) 6 (2.26)  
 Obstructive uropathy 31 (8.09) 8 (6.77) 23 (8.97)  
 IgA nephropathy 18 (4.69) 5 (4.23) 13 (4.90)  
 ADPKD 26 (6.78) 8 (6.77) 18 (6.79)  
 Systemic lupus nephritis 15 (3.91) 4 (3.38) 11 (4.15)  
 FSGS 16 (4.17) 4 (3.38) 12 (4.52)  
 Analgesic nephropathy 5 (1.30) 4 (3.38) 1 (0.37)  
 MPGN 12 (3.13) 4 (3.38) 8 (3.01)  
 Solitary kidney 14 (3.65) 8 (6.77) 6 (2.26)  
 Chronic pyelonephritis 12 (3.13) 3 (2.54) 9 (3.39)  
 TIN 2 (0.52) 1 (0.84) 1 (0.37)  
 HUS 1 (0.26) 1 (0.84) 0 (0.00)  
 Alport syndrome 6 (1.56) 6 (2.26)  
 Hypoplastic kidneys 9 (2.34) 9 (3.39)  
Comorbid, n (%) 
 Hypertension 124 (32.37) 59 (50) 65 (24.52)  
 IHD 7 (1.87) 4 (3.38) 3 (1.13)  
 Chronic hepatitis 35 (9.13) 4 (3.38) 31 (11.69)  
 Dyslipidaemia 110 (28.72) 3 (2.54) 107 (40.37)  
 Peptic ulcer disease 3 (0.78) 2 (1.69) 1 (0.37)  
 CHF 88 (22.97) 2 (1.69) 86 (32.45)  
 Asthma 5 (1.30) 2 (1.69) 3 (1.13)  
 Rheumatoid arthritis 10 (2.61) 1 (0.84) 9 (3.39)  
Donor, n (%) n=369 N = 118 n = 251 0.168 
 LURD 269 (72.89) 92 (77.96) 177 (70.51) 
 LRD 92 (24.93) 24 (20.33) 68 (27.09) 
 Cadaver 8 (2.16) 2 (1.69) 6 (2.39) 
Immunosuppression, n (%) 0.795 
 Azathioprine 81 (21.14) 24 (20.33) 57 (21.50)  
 Cyclosporine 220 (57.44) 79 (66.94) 141 (53.20) <0.05 
 MMF 231 (60.31) 67 (56.77) 164 (61.88) 0.345 
 Prednisolone 357 (93.21) 114 (96.61) 243 (91.69) 0.077 
 Sirolimus 42 (10.96) 18 (15.25) 24 (9.05) 0.073 
 Tacrolimus 121 (31.59) 33 (27.96) 88 (33.20) 0.308 
TWO 35 (9.13) 9 (7.62) 26 (9.81) 0.565 
 CO + PRED 15 (3.91) 7 (5.93) 8 (3.01)  
 AZA + PRED 1 (0.26) 0 (0) 1 (0.37)  
 AZA + CO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + SIRO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + TAC 1 (0.26) 0 (0) 1 (0.37)  
 CO + MMF 2 (0.52) 0 (0) 2 (0.75)  
 MMF + PRED 5 (1.30) 0 (0) 5 (1.88)  
 MMF + TAC 2 (0.52) 0 (0) 2 (0.75)  
 PRED + TAC 6 (1.56) 1 (0.84) 5 (1.88)  
 PRED + SIRO 1 (0.26) 1 (0.84) 0 (0)  
Three 325 (84.85) 109 (92.37) 216 (81.50) 0.007 
 AZA + CO + PRE 70 (18.27) 26 (22.03) 46 (17.35)  
 AZA + PRED + SIRO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + PRED + TAC 6 (1.56) 0 (0) 6 (2.26)  
 CO + PRED + SIR 18 (4.69) 11 (9.35) 7 (2.64)  
 CO + MMF + PRED 109 (28.45) 35 (29.66) 73 (27.54)  
 CO + PRED + TAC 3 (0.78) 2 (1.69) 1 (0.37)  
 EVO + MMF + PRED 2 (0.52) 0 (0) 2 (0.75)  
 MMF + PRED + SIRO 14 (3.65) 3 (2.54) 11 (4.15)  
 MMF + PRED + TAC 96 (25.06) 29 (24.57) 66 (24.90)  
 PRED + TAC + SIRO 4 (1.04) 1 (0.84) 3 (1.13)  
 PRED + SIRO + LEF 2 (0.52) 2 (1.69) 0 (0)  
Creatinine, mg/dL, median (IQR) 1.2 (0.5–1.7), n = 294 1.58 (±0.99), n = 88 0.7 (±0.89), n = 206 0.517 
 ≤1.2 148 (50.34) 44 (38.56) 104 (40.62)  
 1.3–2 97 (24.56) 28 (24.56) 69 (26.95)  
 2.1–3 29 (9.86) 10 (8.77) 19 (7.42)  
 3.1–4 11 (3.74) 2 (1.75) 9 (3.51)  
 4.1–5 3 (1.02) 2 (1.75) 1 (0.37)  
 >5.1 6 (2.04) 2 (1.75) 4 (1.56)  
Graft failure on dialysis 76 (19.84) 26 (6.78) 50 (13.05) 0.322 
Proteinuria 0.5 (0.03–1.27), n = 334 0.218 (0.15–1), n = 107 0.6 (0.3–1.67), n = 227 0.307 
 ≤500 mg/d 226 (67.66) 66 (61.68) 160 (70.48)  
 500 mg–1 gm 51 (15.26) 17 (15.88) 34 (14.97)  
 1–1.5 g 6 (1.79) 2 (1.87) 4 (1.76)  
 1.5–2 6 (1.79) 2 (1.87) 4 (1.76)  
 2.1–3 18 (5.38) 7 (6.54) 11 (4.84)  
 3.1–5 14 (4.19) 7 (6.54) 7 (3.08)  
 >5.1 13 (3.89) 6 (5.60) 7 (3.08)  
Post-transplant CMV infection n= 307 n = 47 n = 260 <0.05 
 CMV-DNA −ve 260 (84.69) 32 (60.08) 228 (87.69) 
 CMV-DNA +ve 47 (15.30) 15 (31.91) 32 (12.30) 
Post-transplant HCV infection <0.05 
 Negative 331 (86.42) 91 (73.12) 240 (90.57) 
 Positive 52 (13.57) 27 (22.88) 25 (9.43) 
Post-transplant HBV infection 0.868 
 Negative 371 (96.86) 112 (95.23) 259 (97.73) 
 Positive 12 (3.13) 6 (4.76) 6 (2.26) 
Acute rejection episodes n= 352 n = 112 n = 240 0.961 
 No 252 (71.59) 81 (72.32) 171 (71.25) 
 Yes 100 (28.40) 31 (5.35) 69 (28.75) 
Graft survival, years, mean (±SD) 11.92 (±6.87) 12.85 (±6.68) 11.32 (±6.95) 0.059 
 Less than 1 years 5 (1.69) 1 (0.86) 4 (2.23)  
 1.1–5 52 (17.62) 14 (12.06) 38 (21.22)  
 5.1–10 84 (28.47) 32 (27.58) 52 (29.05)  
 10.1–15 67 (22.71) 29 (25) 38 (21.22)  
 15.1–20 55 (18.64) 30 (25.86) 25 (13.96)  
 >20 32 (10.84) 10 (8.62) 22 (12.29)  
Mortality, n (%) <0.05 
 Mortality 59 (15.40) 26 (22.03) 33 (12.45)  
 Cardiac 22 (37.28) 5 (19.23) 17 (51.51)  
 Sepsis 28 (47.45) 15 (57.69) 13 (39.39)  
 Malignancy 3 (5.08) 2 (7.69) 1 (3.03)  
 Cerebrovascular accident 3 (5.08) 2 (7.69) 1 (3.03)  
 Pulmonary haemorrhage 1 (1.69) 0 (00) 1 (3.03)  
 Hepatic failure 2 (3.38) 2 (7.69) 0 (00)  
Patients’ characteristicsRenal transplant recipients, n = 383PTDM, n = 118, 23.30%Non-PTDM, n = 265, 76.70%p value
Age, years, mean (±SD) 49.51 (±14.85) 54.79 (±12.48) 47.22 (±15.23) <0.05 
Age at transplantation, years, mean (±SD) 35.70 (±14.27) 40.48 (±12.59) 34 (±14.48) <0.05 
Sex (male) 195 (50.91) 28 (23.72) 167 (63.01) <0.05 
Primary disease, n (%) 
 Chronic glomerulonephritis 141 (36.81) 45 (38.13) 96 (36.22)  
 Hypertension 55 (14.36) 15 (12.71) 40 (15.09)  
 Chronic allograft nephropathy 14 (3.65) 8 (6.77) 6 (2.26)  
 Obstructive uropathy 31 (8.09) 8 (6.77) 23 (8.97)  
 IgA nephropathy 18 (4.69) 5 (4.23) 13 (4.90)  
 ADPKD 26 (6.78) 8 (6.77) 18 (6.79)  
 Systemic lupus nephritis 15 (3.91) 4 (3.38) 11 (4.15)  
 FSGS 16 (4.17) 4 (3.38) 12 (4.52)  
 Analgesic nephropathy 5 (1.30) 4 (3.38) 1 (0.37)  
 MPGN 12 (3.13) 4 (3.38) 8 (3.01)  
 Solitary kidney 14 (3.65) 8 (6.77) 6 (2.26)  
 Chronic pyelonephritis 12 (3.13) 3 (2.54) 9 (3.39)  
 TIN 2 (0.52) 1 (0.84) 1 (0.37)  
 HUS 1 (0.26) 1 (0.84) 0 (0.00)  
 Alport syndrome 6 (1.56) 6 (2.26)  
 Hypoplastic kidneys 9 (2.34) 9 (3.39)  
Comorbid, n (%) 
 Hypertension 124 (32.37) 59 (50) 65 (24.52)  
 IHD 7 (1.87) 4 (3.38) 3 (1.13)  
 Chronic hepatitis 35 (9.13) 4 (3.38) 31 (11.69)  
 Dyslipidaemia 110 (28.72) 3 (2.54) 107 (40.37)  
 Peptic ulcer disease 3 (0.78) 2 (1.69) 1 (0.37)  
 CHF 88 (22.97) 2 (1.69) 86 (32.45)  
 Asthma 5 (1.30) 2 (1.69) 3 (1.13)  
 Rheumatoid arthritis 10 (2.61) 1 (0.84) 9 (3.39)  
Donor, n (%) n=369 N = 118 n = 251 0.168 
 LURD 269 (72.89) 92 (77.96) 177 (70.51) 
 LRD 92 (24.93) 24 (20.33) 68 (27.09) 
 Cadaver 8 (2.16) 2 (1.69) 6 (2.39) 
Immunosuppression, n (%) 0.795 
 Azathioprine 81 (21.14) 24 (20.33) 57 (21.50)  
 Cyclosporine 220 (57.44) 79 (66.94) 141 (53.20) <0.05 
 MMF 231 (60.31) 67 (56.77) 164 (61.88) 0.345 
 Prednisolone 357 (93.21) 114 (96.61) 243 (91.69) 0.077 
 Sirolimus 42 (10.96) 18 (15.25) 24 (9.05) 0.073 
 Tacrolimus 121 (31.59) 33 (27.96) 88 (33.20) 0.308 
TWO 35 (9.13) 9 (7.62) 26 (9.81) 0.565 
 CO + PRED 15 (3.91) 7 (5.93) 8 (3.01)  
 AZA + PRED 1 (0.26) 0 (0) 1 (0.37)  
 AZA + CO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + SIRO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + TAC 1 (0.26) 0 (0) 1 (0.37)  
 CO + MMF 2 (0.52) 0 (0) 2 (0.75)  
 MMF + PRED 5 (1.30) 0 (0) 5 (1.88)  
 MMF + TAC 2 (0.52) 0 (0) 2 (0.75)  
 PRED + TAC 6 (1.56) 1 (0.84) 5 (1.88)  
 PRED + SIRO 1 (0.26) 1 (0.84) 0 (0)  
Three 325 (84.85) 109 (92.37) 216 (81.50) 0.007 
 AZA + CO + PRE 70 (18.27) 26 (22.03) 46 (17.35)  
 AZA + PRED + SIRO 1 (0.26) 0 (0) 1 (0.37)  
 AZA + PRED + TAC 6 (1.56) 0 (0) 6 (2.26)  
 CO + PRED + SIR 18 (4.69) 11 (9.35) 7 (2.64)  
 CO + MMF + PRED 109 (28.45) 35 (29.66) 73 (27.54)  
 CO + PRED + TAC 3 (0.78) 2 (1.69) 1 (0.37)  
 EVO + MMF + PRED 2 (0.52) 0 (0) 2 (0.75)  
 MMF + PRED + SIRO 14 (3.65) 3 (2.54) 11 (4.15)  
 MMF + PRED + TAC 96 (25.06) 29 (24.57) 66 (24.90)  
 PRED + TAC + SIRO 4 (1.04) 1 (0.84) 3 (1.13)  
 PRED + SIRO + LEF 2 (0.52) 2 (1.69) 0 (0)  
Creatinine, mg/dL, median (IQR) 1.2 (0.5–1.7), n = 294 1.58 (±0.99), n = 88 0.7 (±0.89), n = 206 0.517 
 ≤1.2 148 (50.34) 44 (38.56) 104 (40.62)  
 1.3–2 97 (24.56) 28 (24.56) 69 (26.95)  
 2.1–3 29 (9.86) 10 (8.77) 19 (7.42)  
 3.1–4 11 (3.74) 2 (1.75) 9 (3.51)  
 4.1–5 3 (1.02) 2 (1.75) 1 (0.37)  
 >5.1 6 (2.04) 2 (1.75) 4 (1.56)  
Graft failure on dialysis 76 (19.84) 26 (6.78) 50 (13.05) 0.322 
Proteinuria 0.5 (0.03–1.27), n = 334 0.218 (0.15–1), n = 107 0.6 (0.3–1.67), n = 227 0.307 
 ≤500 mg/d 226 (67.66) 66 (61.68) 160 (70.48)  
 500 mg–1 gm 51 (15.26) 17 (15.88) 34 (14.97)  
 1–1.5 g 6 (1.79) 2 (1.87) 4 (1.76)  
 1.5–2 6 (1.79) 2 (1.87) 4 (1.76)  
 2.1–3 18 (5.38) 7 (6.54) 11 (4.84)  
 3.1–5 14 (4.19) 7 (6.54) 7 (3.08)  
 >5.1 13 (3.89) 6 (5.60) 7 (3.08)  
Post-transplant CMV infection n= 307 n = 47 n = 260 <0.05 
 CMV-DNA −ve 260 (84.69) 32 (60.08) 228 (87.69) 
 CMV-DNA +ve 47 (15.30) 15 (31.91) 32 (12.30) 
Post-transplant HCV infection <0.05 
 Negative 331 (86.42) 91 (73.12) 240 (90.57) 
 Positive 52 (13.57) 27 (22.88) 25 (9.43) 
Post-transplant HBV infection 0.868 
 Negative 371 (96.86) 112 (95.23) 259 (97.73) 
 Positive 12 (3.13) 6 (4.76) 6 (2.26) 
Acute rejection episodes n= 352 n = 112 n = 240 0.961 
 No 252 (71.59) 81 (72.32) 171 (71.25) 
 Yes 100 (28.40) 31 (5.35) 69 (28.75) 
Graft survival, years, mean (±SD) 11.92 (±6.87) 12.85 (±6.68) 11.32 (±6.95) 0.059 
 Less than 1 years 5 (1.69) 1 (0.86) 4 (2.23)  
 1.1–5 52 (17.62) 14 (12.06) 38 (21.22)  
 5.1–10 84 (28.47) 32 (27.58) 52 (29.05)  
 10.1–15 67 (22.71) 29 (25) 38 (21.22)  
 15.1–20 55 (18.64) 30 (25.86) 25 (13.96)  
 >20 32 (10.84) 10 (8.62) 22 (12.29)  
Mortality, n (%) <0.05 
 Mortality 59 (15.40) 26 (22.03) 33 (12.45)  
 Cardiac 22 (37.28) 5 (19.23) 17 (51.51)  
 Sepsis 28 (47.45) 15 (57.69) 13 (39.39)  
 Malignancy 3 (5.08) 2 (7.69) 1 (3.03)  
 Cerebrovascular accident 3 (5.08) 2 (7.69) 1 (3.03)  
 Pulmonary haemorrhage 1 (1.69) 0 (00) 1 (3.03)  
 Hepatic failure 2 (3.38) 2 (7.69) 0 (00)  

ADPKD, autosomal dominant polycystic kidney disease; FSGS, focal segmental glomerulosclerosis; TIN, tubulointerstitial nephritis; HUS, haemolytic uraemic syndrome; IHD, ischaemic heart disease; CHF, congestive heart failure; LURD, live unrelated donor; LRD, live related donor; MMF, mycophenolate mofetil; CO, cyclosporine; PRED, prednisolone; AZA, azathioprine; SIRO, sirolimus; TAC, tacrolimus; CMV, cytomegalovirus; IQR, interquartile range.

Viral Infection

Post-transplant CMV infection as evident with positive PCR (PTDM vs. non-diabetics: 31.91% vs. 12.30%, p = 0.003) as well as hepatitis C virus infection (HCV) (PTDM vs. non-diabetics: 22.88% vs. 9.43%, p = 0.003) rate was significantly higher among PTDM patients, while hepatitis B virus infection rate was 4.76% (n = 6) in PTDM and 2.26% (n = 6) in non-diabetic renal transplant recipients.

Risk Factors for PTDM

Univariate regression analysis was used to determine factors that independently predicted the development of PTDM (Table 3). The proven significant factors were inserted into multivariate model, as shown in Table 4. Older age of recipient (overall and also at the time of renal transplantation), male gender, cyclosporine immunosuppression, and post-transplant cytomegalovirus and HCV are the factors that independently predict development of PTDM in renal transplant recipients.

Table 3.

Factors predicting PTDM: univariate analysis

Hazard ratio95% CIp value
Age, years 1.05 1.03–1.08 <0.05 
Age at transplantation, years 1.06 1.01–2.86 <0.05 
Sex (male) 1.87 1.03–3.38 <0.05 
Cyclosporine 2.12 1.37–5.09 <0.05 
Prednisolone 0.96 0.3–1.6 0.07 
CMV seroconversion 1.39 1.14–1.49 <0.05 
BK virus 0.97 0.24–1.77 0.36 
HCV status 1.3 1.30–2.41 <0.05 
HBV 0.94 0.35–1.88 0.86 
Rejection 1.39 0.96–3.14 0.96 
Hazard ratio95% CIp value
Age, years 1.05 1.03–1.08 <0.05 
Age at transplantation, years 1.06 1.01–2.86 <0.05 
Sex (male) 1.87 1.03–3.38 <0.05 
Cyclosporine 2.12 1.37–5.09 <0.05 
Prednisolone 0.96 0.3–1.6 0.07 
CMV seroconversion 1.39 1.14–1.49 <0.05 
BK virus 0.97 0.24–1.77 0.36 
HCV status 1.3 1.30–2.41 <0.05 
HBV 0.94 0.35–1.88 0.86 
Rejection 1.39 0.96–3.14 0.96 
Table 4.

Factors predicting PTDM: multivariate analysis

Hazard ratio95% CIp value
Age, years 1.08 1.01–1.07 <0.05 
Age at transplantation, years 1.08 1.03–1.09 <0.05 
Sex (male) 1.7 1.15–3.92 <0.05 
Cyclosporine 3.83 1.77–9.21 <0.05 
CMV seroconversion 1.17 1.19–1.59 <0.05 
HCV status 1.21 1.01–2.1 <0.05 
Rejection 1.11 1.05–1.86 0.96 
Hazard ratio95% CIp value
Age, years 1.08 1.01–1.07 <0.05 
Age at transplantation, years 1.08 1.03–1.09 <0.05 
Sex (male) 1.7 1.15–3.92 <0.05 
Cyclosporine 3.83 1.77–9.21 <0.05 
CMV seroconversion 1.17 1.19–1.59 <0.05 
HCV status 1.21 1.01–2.1 <0.05 
Rejection 1.11 1.05–1.86 0.96 

Graft Survival and Patient Mortality

Overall renal graft survival at 1, 5, and 10 years was 97.39%, 85.64%, and 75.93%, respectively. There was no difference in graft survival between PTDM and non-diabetic statistically. At 5 and 10 years, graft survival were 88.13% and 72.03% for PTDM patients and 84.52% and 69.52% for non-diabetes. A total of 59 (15.40%) renal transplant recipients expired in study period. The mortality in the PTDM group was significantly higher (PTDM vs. non-diabetic: 22.03 vs. 12.45%, p = 0.016) than in the non-diabetic group. Overall and in PTDM population, common cause of death was infection (47.45% and 57.69%, respectively), whereas cardiac-related causes were more prevalent in non-diabetics (n = 17, 51.51%).

In this single-centre study, we found an incidence of PTDM of 23.04% (n = 118) in renal transplant recipients. PTDM incidence in renal transplant recipients varies between 10 and 40%, and this variation depends on the length of follow-up, type of immunosuppressive, and diagnostic criteria [10]. Malik et al. [11] reported 29 and 20.55% PTDM incidence in 5 years and 6 months after transplantation, respectively [11, 12]. In studies using OGTT for diagnosis, Hjelmesaeth et al. [13] observed an incidence of PTDM at 18% in 1995, which has reduced to 11% in 2012 [14]. PTDM pathophysiology is multifactorial; risk factors for its development are pre-and post-transplantation, also allograft-associated. Increased age of recipient (>40 years), obesity (BMI >30 kg/m2), family history of diabetes, and high-risk ethnicities (Asian and African-American) are known pre-transplant risk factors [15, 16]. We also found age at transplantation in the PTDM group was higher than that of non-diabetics (40.48 vs. 34 years, p = <0.05). Medical comorbidities in renal transplant recipients: HCV, cystic fibrosis, and polycystic kidney disease can also influence the development of PTDM [17, 18]. Studies have shown significantly reduced insulin sensitivity in HCV-positive renal transplant recipients without affecting insulin secretion or hepatic insulin uptake [19]. HCV infection is statistically significant in our PTDM population (22.88% vs. 9.43%, p = 0.003). Allograft type is the most important allograft-associated risk factor for PTDM; Gaurishankar et al. [20] observed nearly four times higher incidence of PTDM in deceased donor allograft recipients than in live donors. In our study, 98.31% of patients had live donors, and allograft type is not associated with PTDM. Immunosuppressive regimen (induction and maintenance), cytomegalovirus infection, and number of rejection episodes are known post-transplant risk factors for PTDM. Steroids, calcineurin inhibitors (CNIs), and mammalian target of rapamycin inhibitors (mTORis) are the mainstay of immunosuppressive therapy in transplantation. Corticosteroids are used for induction (in high doses) and maintenance (lower and tapering doses) immunosuppression in renal transplantation. Hyperglycaemia and diabetes mellitus are well-known side effects of corticosteroids, and impaired insulin sensitivity, increased hepatic gluconeogenesis, and appetite stimulation leading to weight gain are the underlying mechanisms behind steroid-induced diabetes mellitus [21, 22]. The diabetic potential of the Induction protocol of corticosteroids is more than the maintenance dosage because its hyperglycaemic effect is dose-dependent [17]. Hjelmesaeth et al. [13] found a 5% increase in the risk of PTDM with a 0.01 mg/kg/day increase in the dose of prednisolone. Mathews et al. [23] also demonstrate high risk at increased dose in fix dose protocol, also there is a decrease in the incidence of PTDM with alteration of dose from high to low [24]. In our study population, Corticosteroids are the most common immunosuppressive medication used by PTDM patients as well as non-diabetic patients, and we use a fixed-dose protocol; however, its association with PTDM is statistically not significant (96.61% vs. 91.69%, p = 0.07). CNIs remain the standard of care as maintenance immunosuppression in renal transplantation for the last four decades since the discovery of cyclosporine [25]. Diabetogenic potential of CNIs is explained by impaired insulin secretion, increased islet cell apoptosis, and decreased beta cell mass [17, 26, 27]. Cyclosporine and tacrolimus are the two main CNIs used in renal transplant recipients. Webster et al. [28] illustrated in his meta-analysis of 30 randomized trials of renal transplantation that tacrolimus is more effective in preventing graft loss and acute rejection than cyclosporine; however, incidence of PTDM was greater in patients receiving tacrolimus at 1-year follow-up (RR 1.86) and increased with higher dose of tacrolimus (p = 0.003). Mathew et al. [23] observed that with every 100 ng/mL increase in trough C2 CNIs level, there is 50% increase in the risk of either post-transplant impaired glucose tolerance or PTDM. In our study population, 219 (57.18%) patients were using cyclosporine; 79 (36.07%, p = 0.009) of them developed PTDM, while 31.59% (n = 121) renal transplant recipients were using tacrolimus, and only 33 (27%, p = 0.308) developed PTDM. mTORis such as sirolimus are used in combination with other immunosuppressive agents in renal transplantation and are considered an independent risk factor for PTDM development [29]. Veroux et al. [30] observed improved glycaemic control when switching cyclosporine with sirolimus in renal transplant recipients. Possible mechanisms behind mTORi-induced PTDM include impaired insulin secretion, reduced signal transduction, islet cell apoptosis (in vitro) [31]. In our study, 10.9% (n = 42) renal transplant recipients were using sirolimus, and 18 (42.85%, p = 0.007) of them developed PTDM; this association is statistically insignificant. CMV infection is common in renal transplant recipients due to its opportunistic nature and immunosuppression. Einalohi et al. [32] observed relative risk of PTDM up to 1.94 in CMV-positive renal transplant recipients than CMV-negative, hence considered independent factor for PTDM development. Definite mechanism behind CMV-induced PTDM is not clear, and it may involve islet cell destruction or pro-inflammatory cytokine production. We identified CMV infection in 23.49% (n = 90) of our study population, and 64.44% (N = 58, p = <0.005) developed PTDM. Renal graft rejection may predispose occurrence of PTDM. Schweer et al. [33] reported 3.98 hazard ratio for PTDM development in patients with acute cellular graft rejection; nonetheless, it is difficult to distinguish effects of rejection versus effect of anti-rejection therapy that involves high dose of steroids and CNIs. However, lesser number of patients had renal graft rejection reported in the PTDM group than non-PTDM (PTDM 26.27% vs. 28.75%, p = 0.96); hence, it was not risk factor in our study population. Many studies have revealed that PTDM is affiliated with increased mortality [34, 35], poor graft outcome [35, 36], and death-censored graft failure [37, 38]. Cardiovascular events, increased risk of opportunistic infection, and sepsis-related mortality are the main reasons for increased mortality in renal transplant recipients. In our renal transplant recipients, the mortality rate was 15% (n = 59) during the study period, and PTDM group significantly suffers higher mortality than non-PTDM renal transplant recipients (22% vs. 12.45%, p = <0.05). Overall, sepsis (47.45%, n = 28) was the most common cause of death in our transplant recipients; 15 (57.69%) of the PTDM patients and 13 (39.39%) of non-PTDM patients expired due to sepsis. Cardiac causes were the second most common reason of mortality, and non-PTDM patients have significantly more cardiac events than PTDM (51.51% vs. 19.23%).

Regarding limitations, our study is a single centre-based and pre-transplant information for some patients was not available, which precluded our analysis, for example, HBA1C data and induction therapy, as most patients had transplants outside and their data were missing. Prednisolone is a proven modifiable risk factor for PTDM; 93% of our study patients received prednisolone, and no association could be deduced between prednisolone and PTDM probably due to underpowered analysis.

PTDM is common among renal transplant recipients. Older age at the time of transplantation, prednisolone and cyclosporine immunosuppression, cytomegalovirus, and hepatitis C virus are risk factors. PTDM carries high mortality but is not associated with graft failure.

This research complies with the guidelines for human studies and is conducted ethically in accordance with the Declaration of Helsinki. The study was approved by the authorized Research and Ethical Committee of Dubai. This is a retrospective observational medical study; the patient de-identified data used in this research were carried out retrospectively. Patients gave their consent to use their data for research by signing the general consent available in the medical record system.

Authors have no conflicts of interest to declare.

There was no funding received by authors from any institute or commercial source.

D.K. and F.J.A.: conceived the idea of research, proposal writing, and data collection; K.G.: data analysis and manuscript writing; A.A.S., H.A., M.A., S.N., and H.Y.: data collection; and M.H.R. and A.K.A.: conceived the idea of research, supervision of study, and creative input.

The data that support the findings of this study are not publicly available due to their containing information that could compromise the privacy of research participants, but they are available from the corresponding author (M.A.A.) upon reasonable request.

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):
1685
9
.