Prediction of kidney transplant outcome by donor quality scoring systems: expanded criteria donor and deceased donor score.

Due to disparity between organ supply and demand, use of kidneys from suboptimal donors has become increasingly common. Several donor quality systems have been developed to identify kidneys with an increased risk for graft dysfunction and loss. The purpose of our study was to compare the utility of deceased donor score (DDS) and expanded criteria donor (ECD) status to predict kidney transplant outcomes in a single center. We analysed 280 deceased donor renal transplantation procedures, collecting data from the prospectively maintained institutional database. Kidney transplant outcome variable included delayed graft function, 1-year glomerular filtration rate (GFR1y), and death-censored graft loss (DCGL). Kidneys were obtained from marginal donors in 45.7% of transplant recipients by DDS and in 24.9% by ECD. DDS-defined marginal donors suffered delayed graft function (DGF) more frequently than nonmarginal donors (40.8% vs 25.0%; P = .006), whereas ECD did not develop DGF at a greater rate. GFR1Y was significantly worse among patients receiving kidneys from marginal donors: DDS 40.3 ± 12.9 vs 57.7 ± 19.4 mL/min/1.73 m(2) (P < .001) and ECD 39.4 ± 14.1 vs 53.8 ± 19.1 mL/min/1.73 m(2) (P < .0001). The most severe donor category defined by DDS (grade D) showed an independently worse death-censored graft survival hazard rate [HR] 2.661, 95% confidence interval [CI], 1.076-6.582; P = .034). DDS and ECD scoring systems are based on donor information available at the time of transplantation that predict 1-year graft function. Moreover in our center, DDS was better to predict DGF and death-censored graft survival than ECD.

New-onset diabetes after transplantation: drug-related risk factors.

INTRODUCTION: New-onset diabetes after transplantation (NODAT), an important complication of renal transplantation leads to reduced graft function and increased patient morbidity and mortality. Because of its high incidence and immense impact on clinical outcomes, prevention of NODAT is highly desirable. Several modifiable and nonmodifiable risk factors for NODAT have been described. The aim of this study was to analyze the influence of various drugs on the development of NODAT during the first year. METHODS: A retrospective analysis was performed on 303 adult kidney transplant recipients free of previously known diabetes. NODAT was defined as a fasting plasma glucose level ≥ 126 mg/dL confirmed by repeat testing on a different day. We excluded patients with transiently elevated fasting plasma glucose during the first 3 months. RESULTS: NODAT was diagnosed in 37 recipients (12.2%). Univariate analysis identified several variables related to NODAT: recipient age (P < .001), body mass index (P < .001), donor age (P = .005), family history of diabetes (P < .001), statin use (P = .005), diuretic use (P = .040) and tacrolimus therapy (P = .029). After multivariate analysis, recipient age (relative risk [RR] = 1.060, 95% confidence interval [CI] 1.019- 1.102, P = .004), family history of diabetes (RR = 3.562, 95% CI 1.574-8.058, P = .002), smoking habit (RR 2.514, 95% CI 1.118-5.655, P = .026) and diuretic use (RR = 2.496, 95% CI 1.087-5.733, P = .031) were independently associated with NODAT development. CONCLUSIONS: In our population of kidney transplant recipients, the main nonmodifiable risk factors for NODAT were recipient age and a family history of diabetes. Diuretic use was a modifiable risk factor associated with the development of NODAT. To reduce NODAT incidence, it is necessary to consider not only immunosuppressive therapy, but also concomitant drugs such as diuretics.

Prediction of delayed graft function by means of a novel web-based calculator: a single-center experience.

Renal failure persisting after renal transplant is known as delayed graft function (DGF). DGF predisposes the graft to acute rejection and increases the risk of graft loss. In 2010, Irish et al. developed a new model designed to predict DGF risk. This model was used to program a web-based DGF risk calculator, which can be accessed via http://www.transplantcalculator.com . The predictive performance of this score has not been tested in a different population. We analyzed 342 deceased-donor adult renal transplants performed in our hospital. Individual and population DGF risk was assessed using the web-based calculator. The area under the ROC curve to predict DGF was 0.710 (95% CI 0.653-0.767, p < 0.001). The "goodness-of-fit" test demonstrates that the DGF risk was well calibrated (p = 0.309). Graft survival was significantly better for patients with a lower DGF risk (5-year survival 71.1% vs. 60.1%, log rank p = 0.036). The model performed well with good discrimination ability and good calibration to predict DGF in a single transplant center. Using the web-based DGF calculator, we can predict the risk of developing DGF with a moderate to high degree of certainty only by using information available at the time of transplantation.

Early prediction of new-onset diabetes mellitus by fifth-day fasting plasma glucose, pulse pressure, and proteinuria.

Renal transplant recipients are at high risk of cardiovascular disease (CVD). New-onset diabetes mellitus after transplantation (NODAT) contributes to the risk of CVD, reducing graft and patient survival. To improve outcome of kidney transplant recipients, it is of great interest to identify those patients who will develop NODAT. The aim of our study was to explore the predictive value of fifth-day fasting plasma glucose (FPG), third-month proteinuria, and pulse pressure (PP) for NODAT development. We analyzed 282 non-previously-diabetic kidney transplants in our center. Fifth-day FPG, PP, and third-month 24-hour proteinuria were collected. NODAT was defined at month 12 according to the "consensus guidelines": symptoms of diabetes plus casual glucose concentrations ≥ 200 mg/dL or FPG ≥ 126 mg/dL. Some 46 patients (16.3%) developed NODAT at month 12. Fifth-day FPG (133 ± 35 vs 108 ± 16 mg/dL, P < .001) and PP (57 ± 17 vs 49 ± 15 mm Hg, P = .007) were significantly higher in patients at risk for NODAT, but there was no difference in third-month proteinuria (652 ± 959 vs 472 ± 1336 mg, P = .390). A multivariate regression model showed an increased risk for NODAT associated with recipient age, body mass index, smoking habit, and a fifth-day FPG ≥ 126 mg/dL (relative risk 4.784, 95% confidence interval 2.121-10.788, P = .0002). The negative predictive value of a fifth-day FPG ≥ 126 mg/dL for predicting 1-year NODAT was 89.4%. Fifth-day FPG was independently related to NODAT development. The detection of a fifth-day FPG ≥ 126 mg/dL increases the risk of suffering NODAT more than 4 times. Fifth-day FPG < 126 mg/dL allows us to identify a transplant population with a low risk (near 10%) for NODAT.

Elevated serum gamma-glutamyltransferase and hypomagnesemia are not related with new-onset diabetes after transplantation.

BACKGROUND: New-onset diabetes mellitus after transplantation (NODAT) contributes to the risk of cardiovascular disease (CVD) and infection, reducing graft and patient survival in kidney transplant recipients. To reduce CVD and improve outcomes of kidney transplant recipients, it is of great interest to more precisely elucidate the risk factors that contribute to the development of NODAT. A previous study reported that hypomagnesemia is an independent predictor of NODAT. Elevated gamma-glutamyltransferase (GGT) activity increases the risk of incident type 2 diabetes in the general population. The objective of this study was to determine whether magnesium (Mg) and GGT were risk factors for NODAT among our population of kidney transplant recipients. METHODS: We retrospectively analyzed 205 non-previously diabetic kidney transplant recipients. GGT was measured before transplantation as well as at months 1, 2, and 12. Mg was measured at months 1, 2, and 12. NODAT was defined at month 12 and at the end of follow-up according to the "2003 international consensus guidelines." RESULTS: Although 36 patients (17.5%) developed NODAT at month 12, 55 patients (26.8%) displayed it at the end of follow-up. We did not observe any significant difference, either in mean Mg (month 1, 1.73±0.24 vs 1.75±0.30 [P=.824]; month 2, 1.71±0.22 vs 1.68±0.26 [P=.565]; month 12, 1.77±0.27 vs 1.80±0.24 [P=.596]) or GGT values (pretransplantation, 32 ± 27 vs 33±85 [P=.866]; month 1:39±24 vs 48±70 [P=.452]; month 2, 53±96 vs 48±83 [P=.739]; month 12, 40±37 vs 38±53 [P=.830]) between NODAT and non-NODAT patients at month 12 or at the end of follow-up. CONCLUSION: Hypomagnesemia and high GGT activity were not risk factors for NODAT development in kidney transplant recipients.

Correlation of C0 and C2 levels with cyclosporine side effects in kidney transplantation.

Cyclosporine has a narrow therapeutic window requiring close monitoring to ensure adequate immunosuppression while avoiding nephrotoxicity and other side effects. Pharmacokinetic studies have suggested that cyclosporine levels at 2 hours postdose (C2) is the best single time point to predict area under the concentration curve (AUC) in kidney transplant recipients. C2 also predicted acute rejection episodes and nephrotoxicity better than trough levels (C0). Targeting cyclosporine levels to minimize side effects while maintaining adequate immunosuppressive effects is of clinical interest. There are conflicting evidence and few reports about whether cyclosporine-related side effects are a dose-dependent phenomenon. The aim of this single center study was to ascertain whether cyclosporine side effects were dose-dependent and which single time point level (C0 or C2) was more closely related to them. We analyzed 225 patients on Neoral-based immunosuppression with C0 and C2 levels measured on the same day of 2 different visits. Serum creatinine, glucose, uric acid, potassium, total cholesterol, triglycerides, and 24-hour urinary sodium elimination were measured by routine biochemical analyses. Blood pressure was measured at each visit. A significant positive correlation was observed between C2 and C0 concentrations and levels of potassium (P < .001), total cholesterol (P < .001), systolic blood pressure (P < .001), and pulse pressure (P < .01). There was a significant negative correlation between C2 and uric acid (P < .001). AUCs of receiver operating characteristic (ROC) curves for both C2 and C0 levels were significant as predictors of hyperkalemia (P < .001), hyperuricemia (P = .001), hypercholesterolemia (P < .05), and high systolic blood pressure (P < .05). There were no significant differences between the capacities of C2 or C0 to predict these variables. In conclusion, potassium, total cholesterol, uric acid, and systolic hypertension were influenced by cyclosporine in a dose-dependent manner. Both C2 and C0 were useful to predict cyclosporine side effects.

Lung cavitation due to Mycobacterium xenopi in a renal transplant recipient.

Mycobacterium xenopi is an unusual pathogen and few such cases have been reported in the literature. We report the case of a patient with a sirolimus-based immunosuppressive regimen, who developed lung cavitation. M. xenopi was isolated from the sputum. The patient was treated initially with rifampicin, isoniazid, and pyrazinamide; levofloxacin was added to the treatment regimen after M. xenopi was demonstrated. A possible relationship between sirolimus and M. xenopi infection has been postulated, probably due to the combination of pulmonary toxicity and cellular immunosuppression of rapamycin.

Nefropatía asociada a VIH sin deterioro de función renal / No disponible

No disponible

Cytokine polymorphisms and risk of infection after kidney transplantation.

INTRODUCTION: Infection remains a significant cause of morbidity and mortality after solid organ transplantation. Genetic background has an influence on the incidence of infection. The aim of our study was to analyze the relationship between cytokine polymorphisms and infection in our kidney transplant recipients. METHODS: DNA from 255 kidney transplant recipients was isolated routinely. Polymerase chain reaction sequence-specific primer was performed using commercially available cytokine genotyping primer packs to determine polymorphisms of interleukin (IL)-10, transforming growth factor-beta, tumor necrosis factor-alpha, interferon-gamma, IL-6, IL-4, IL-2, IL-12, IL-4R alpha, IL-1RA, IL-1R, IL-1 beta, and IL-1 alpha. The appearance and number of infections within the first year after transplantation were identified retrospectively. RESULTS: One hundred twenty-two patients experienced at least one episode of infection in the first year after transplant. The frequency of the -511 IL-1beta CC genotype and the frequencies of the -1188 IL-12 CA and CC genotypes were significantly higher among the infected patients compared with the noninfected patients. We failed to observe significant differences in the genotype distribution of the other analyzed cytokines regarding the incidence of infection. After adjusting, recipient IL-1beta (-511 CC) genotype (relative risk [RR] 2.67, 95% confidence interval (CI) 1.30 to 5.49, P = .007) and recipient IL-12 (-1188 CA and CC) genotypes (RR 2.57, 95% CI 1.22 to 5.38, P = .012) predicted independently the risk of infection in the first year after kidney transplantation. CONCLUSION: Kidney transplant recipients with -511 IL-1beta CC genotype or with -1188 IL-12 CA and CC genotypes were at higher risk of developing infections in the first year after transplantation. Patients with genetic susceptibility to infection may benefit from less potent immunosuppressive therapy and more intense preventive measures.

Similar impact of slow and delayed graft function on renal allograft outcome and function.

Kidney transplant patients can be divided into three groups, according to the initial graft function. First-week dialyzed patients form the delayed graft function (DGF) group. Nondialyzed patients are divided into slow graft function (SGF) or immediate graft function (IGF) according to whether the day 5 serum creatinine was higher versus lower than 3 mg/dL, respectively. SGF patients showed worse graft survival, above higher incidence of acute rejection and lower renal function than IGF patients, although few reports have analyzed outcomes in these groups. We analyzed the impact of SGF on graft survival, first-year renal function, and incidence of acute rejection in 291 renal transplant patients. Creatinine was significantly worse at 12 months for SGF and DGF than for IGF patients (1.9 +/- 0.8 mg/dL, 1.8 +/- 0.7 mg/dL, 1.5 +/- 0.5 mg/dL, respectively; P < .05). There was no difference in first-year renal function between SGF and DGF. The acute rejection rate was higher among the SGF than the IGF group (45% vs 21%, P < .05), but not different from DGF patients (42%, P < .05). Graft survival was better among IGF than SGF or DGF patients, with no significant difference between the last two groups (3-year graft survival, 82%, 71%, 70%, respectively; log-rank test, P < .05). Kidney transplant recipients who develop SGF have a worse outcome than patients with IGF, similar to DGF patients. SGF patients show worse graft survival, worse renal function, and higher acute rejection rates than IGF patients, despite not needing dialysis.

High initial blood levels of tacrolimus in overweight renal transplant recipients.

For the purpose of both efficacy and safety, exposure to tacrolimus and other immunosuppressive drugs must be monitored, since initial levels influence the development of acute rejection episodes, nephrotoxicity, and posttransplantation diabetes mellitus. The aim of this study was to identify risk factors for developing high initial tacrolimus blood levels. We analyzed clinical and biochemical parameters of 85 renal transplant recipients receiving tacrolimus-based immunosuppressive therapy by stratifying into subgroups of patients who displayed first tacrolimus concentrations higher and lower than 15 ng/mL. Patients with a first level of tacrolimus higher than 15 ng/mL were older (52 +/- 13 vs 40 +/- 12 years, P < .05) and had a larger body mass index (27 +/- 4 vs 23 +/- 3 kg/m2, P < .05) than patients with lower levels, despite receiving a lower weight-adjusted cumulative steroid dose (8.2 +/- 2.2 vs 9.3 +/- 2.5 mg/kg, P < .05). Upon logistic regression, age (RR 1.047, 95% CI 1.007 to 1.08, P = .021) and body mass index (RR 1.176, 95% CI 1.009 to 1.371, P = .036) remained significant risk factors for high initial blood levels of tacrolimus. As these subgroups of patients are most prone to develop posttransplantation glycemic disorders, attention must be paid to avoid high tacrolimus blood levels by diminishing initial tacrolimus doses or estimating them from ideal body weight.

Higher initial tacrolimus blood levels and concentration-dose ratios in kidney transplant recipients who develop diabetes mellitus.

Posttransplantation diabetes mellitus (PTDM) is a common complication of kidney transplantation, associated with poorer graft and patient outcomes. Tacrolimus is a strong immunosuppressive drug associated with low acute rejection rates, but a higher risk for PTDM. High trough levels of tacrolimus during the first month after transplantation have been found to be a significant risk factor for the development of PTDM. The aim of this single-center study was to identify the risk factors for the development of PTDM among kidney transplant recipients under tacrolimus therapy. We examined 73 cadaveric kidney transplant recipients receiving tacrolimus between 1994 and 2003. Age, donor and recipient gender, dialysis method, body mass index (BMI), first year weight gain, mismatches, incidence of acute rejection and delayed graft function, hepatitis C serology, first year cumulative steroid dose, first tacrolimus blood level, first tacrolimus blood level <15 ng/mL, and corresponding tacrolimus daily doses and concentration/dose ratios (CDR) were also collected. PTDM was defined as at least 2 fasting blood glucose values > or =126 mg/dL, according to the World Health Organization criteria. Incidence of first year PTDM was 27.4%. Patients with PTDM showed significantly higher age, BMI, first tacrolimus blood level, first tacrolimus CDR, and CDR with tacrolimus blood level <15 ng/mL as well as less 1-year weight gain. After logistic regression, age (relative risk [RR] 1.060, confidence interval [CI] 95%, 1.001-1.122; P = .043) and first tacrolimus blood level (RR 1.154; CI 95%, 1.038-1.283; P = .008) remain significant risk factors for developing PTDM. Older age and initial tacrolimus blood levels were the main risk factors for PTDM among our group of patients. Kidney transplant recipients who develop PTDM maintain a high CDR of tacrolimus.

[Clinical suspicion of vertebral osteomielitis: back pain in patients with hemodyalisis by catheter related infection]. / Sospecha clínica de osteomielitis vertebral: dolor de espalda en los pacientes con infección asociada a catéter de hemodiálisis.

The overall incidence of vertebral osteomyelitis is increasing due to, the increasing rates of bacteraemia due to intravascular devices. We report a patient with end-stage renal failure under hemodialysis by internal jugular catheters who started with back pain after several episodes of Staphylococcus aureus bacteraemia, and whose magnetic resonance imaging was showed signs suggestive of spondylodiscitis. Other 4 similar cases from our service have been analysed, thereby we can conclude the most effective treatment of vertebral osteomyelitis and/or epidural abscess is premature diagnosis of these pathologies. Magnetic resonance imaging is the most sensitive radiologic technique whom we have. Treatment of vertebral osteomyelitis must be preceded by a correct bacteriological diagnosis. Surgery plays a central role in the successful treatment and should be performed as soon as neurological problems are apparent.

Assessment of glomerular filtration rate in transplant recipients with severe renal insufficiency by Nankivell, Modification of Diet in Renal Disease (MDRD), and Cockroft-Gault equations.

Measurement of glomerular filtration rate (GFR) is time consuming and cumbersome. Several formulas have been developed to predict creatinine clearance (CrCl) or GFR using serum creatinine (Cr) concentrations and demographic characteristics. However, few studies have been performed to discern the best formula to estimate GFR in kidney transplantation. In this study, Cockroft-Gault (CG), Nankivell, and Levey (MDRD) formulas were tested to predict GFR in 125 cadaveric renal transplant patients with severe renal insufficiency (GFR less than 30 mL/min per 1.73 m2). The GFR was estimated as the average Cr and urea clearances. The mean GFR estimated by averaged Cr and urea clearances (22.18+/-5.23 mL/min per 1.73 m2) was significantly different from the mean values yielded by the MDRD formula (20.42+/-6.65 mL/min per 1.73 m2, P=.000), the Nankivell formula (30.14+/-11.98 mL/min per 1.73 m2, P=.000), and the CG formula (29.42+/-8.64 mL/min per 1.73 m2, P=.000). The MDRD formula showed a better correlation (R=0.741, P=.000) than the CG (R=0.698, P=.000) and the Nankivell formulas (R=0.685, P=.000). Analysis of differences using the Bland-Altmann method demonstrated that MDRD gave the lowest bias (MDRD: -1.65+/-4.4 mL/min per 1.73 m2; CG: 7.33+/-6.24 mL/min per 1.73 m2; Nankivell: 8.05+/-9.23 mL/min per 1.73 m2) and narrower limits of agreement (Nankivell: -10.41-26.51 mL/min per 1.73 m2; CG: -5.15-19.81 mL/min per 1.73 m2; MDRD: -10.61-7.31 mL/min per 1.73 m2). In transplant patients with severe renal insufficiency, the MDRD equation seems better than the other formulas to estimate GFR.

Pulse pressure is an independent risk factor of cardiovascular disease in renal transplant patients.

Elevated pulse pressure in the general population has been shown to be associated with cardiovascular disease, which is the main cause of death in renal transplant patients. We investigated the effects that a wide pulse pressure has on cardiovascular disease after renal transplantation in a cohort of 532 transplant patients with functioning grafts for more than one year. Patients were classified into two groups depending on whether the one-year pulse pressure was less than or greater than 65 mm Hg. We analyzed patient survival, posttransplant cardiovascular disease and principle causes of death. Five- and ten-year patient survival were lower among the group with higher pulse pressures. The main cause of death was vascular disease in both groups. The presence of posttransplant cardiovascular disease was higher among the group with higher pulse pressures (RR=1.73). In addition, the incidence of an elevated pulse pressure was directly associated with recipient age and posttransplant diabetes mellitus. In conclusion, pulse pressure represents an independent risk factor for increased cardiovascular morbidity and mortality in renal transplant patients.