Prognostic Associations Between Lipid Markers and Outcomes in Kidney Transplant Recipients

Values of Donor Serum Lipids and Calcium in Predicting Graft Function after Kidney Transplantation: A Retrospective Study

OBJECTIVE

Delayed graft function (DGF) and early graft loss of renal grafts are determined by the quality of the kidneys from the deceased donor. As "non-traditional" risk factors, serum biomarkers of donors, such as lipids and electrolytes, have drawn increasing attention due to their effects on the postoperative outcomes of renal grafts. This study aimed to examine the value of these serum biomarkers for prediction of renal graft function.

METHODS

The present study consecutively collected 306 patients who underwent their first single kidney transplantation (KT) from adult deceased donors in our center from January 1, 2018 to December 31, 2019. The correlation between postoperative outcomes [DGF and abnormal serum creatinine (SCr) after 6 and 12 months] and risk factors of donors, including gender, age, body mass index (BMI), past histories, serum lipid biomarkers [cholesterol, triglyceride, high-density lipoprotein (HDL) and low-density lipoprotein (DL)], and serum electrolytes (calcium and sodium) were analyzed and evaluated.

RESULTS

(1) Donor age and pre-existing hypertension were significantly correlated with the incidence rate of DGF and high SCr level (≥2 mg/dL) at 6 and 12 months after KT (P<0.05); (2) The donor's BMI was significantly correlated with the incidence rate of DGF after KT (P<0.05); (3) For serum lipids, merely the low level of serum HDL of the donor was correlated with the reduced incidence rate of high SCr level at 12 months after KT [P<0.05, OR (95% CI): 0.425 (0.202-0.97)]; (4) The serum calcium of the donor was associated with the reduced incidence rate of high SCr level at 6 and 12 months after KT [P<0.05, OR (95% CI): 0.184 (0.045-0.747) and P<0.05, OR (95% CI): 0.114 (0.014-0.948), respectively].

CONCLUSION

The serum HDL and calcium of the donor may serve as predictive factors for the postoperative outcomes of renal grafts after KT, in addition to the donor's age, BMI and pre-existing hypertension.

Risk factors for death in kidney transplant patients: analysis from a large protocol biopsy registry

BACKGROUND

Identification and quantification of the relevant factors for death can improve patients' individual risk assessment and decision-making. We used a well-documented patient cohort (n = 892) in a renal transplant programme with protocol biopsies to establish multivariable Cox models for risk assessment at 3 and 12 months post-transplantation.

METHODS

Patients transplanted between 2000 and 2007 were observed up to 11 years (total observation 5227 patient-years; median 5.9 years). Loss to follow-up was negligible (n = 15). A total of 2251 protocol biopsies and 1214 biopsies for cause were performed. All rejections and clinical borderline rejections in protocol biopsies were treated.

RESULTS

Overall 10-year patient survival was 78%, with inferior survival of patients with graft loss and superior survival of patients with living-donor transplantation. Eight factors were common in the models at 3 and 12 months, including age, pre-transplant heart failure and a score of cardiovascular disease and type 2 diabetes, post-transplant urinary tract infection, treatment of rejection, new-onset heart failure, coronary events and malignancies. Additional variables of the model at 3 months included deceased donor transplantation, transplant lymphocele, BK virus nephropathy and severe infections. Graft function and graft loss were significant factors of the model at 12 months. Internal validation and validation with a separate cohort of patients (n = 349) demonstrated good discrimination of the models.

CONCLUSIONS

The identified factors indicate the important areas that need special attention in the pre- and post-transplant care of renal transplant patients. On the basis of these models, we provide nomograms as a tool to weigh individual risks that may contribute to decreased survival.

Mortality in Elderly Waiting-List Patients Versus Age-Matched Kidney Transplant Recipients: Where is the Risk?

The number of elderly patients on the waiting list (WL) for kidney transplantation (KT) has risen significantly in recent years. Because KT offers a better survival than dialysis therapy, even in the elderly, candidates for KT should be selected carefully, particularly in older waitlisted patients. Identification of risk factors for death in WL patients and prediction of both perioperative risk and long-term post-transplant mortality are crucial for the proper allocation of organs and the clinical management of these patients in order to decrease mortality, both while on the WL and after KT. In this review, we examine the clinical results in studies concerning: a) risk factors for mortality in WL patients and KT recipients; 2) the benefits and risks of performing KT in the elderly, comparing survival between patients on the WL and KT recipients; and 3) clinical tools that should be used to assess the perioperative risk of mortality and predict long-term post-transplant survival. The acknowledgment of these concerns could contribute to better management of high-risk patients and prophylactic interventions to prolong survival in this particular population, provided a higher mortality is assumed.

Clinical assessment of lipid profiles in live kidney donors

BACKGROUND

Abnormal serum lipid profiles are an issue in chronic kidney disease (CKD), but the clinical ramifications of dyslipidemia in live kidney donors are unclear. Thus, we explored the relationship between serum lipids and residual renal function in living donors post-nephrectomy.

METHODS

Charts of living donors who underwent nephrectomy between January 2010 and March 2013 were reviewed, targeting those with 6-month follow-up examinations at minimum. Altogether, 282 donors were studied, examining total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels assayed before donation by standard techniques. Median follow-up time was 14 months. The relationship between postoperative renal function and allograft biopsy results was assessed. Recursive partitioning was applied to identify optimal cut-off points for each parameter.

RESULTS

Median (interquartile range) serum TC, TG, LDL, and HDL levels were 183 (161-205) mg/dL, 86 (63-131) mg/dL, 108 (92-128) mg/dL, and 53 (44-62) mg/dL, respectively. The glomerular filtration rate at last follow-up was associated with TC (r = -0.187; P = .002) and LDL (r = -0.172; P = .005) levels, but showed no correlation with TG and HDL. Root nodes of TC and LDL determinations in recursive partitioning were 170.5 mg/dL and 80.5 mg/dL, respectively, serving as thresholds for further evaluation. On logistic regression analysis, the likelihood of CKD (glomerular filtration rate < 60 mL/min/1.73 m(2)) at last follow-up was greater in donors with elevated TC and LDL levels (odds ratio = 1.96 and 3.33; P = .021 and .029, respectively).

CONCLUSION

Kidney donors with serum TC and LDL elevations require close observation, given their demonstrable predisposition to CKD after donation.

Patient Survival in Renal Allograft Failure: A Time-dependent Analysis

Background:

To improve patient survival after a renal transplant, it is important to detect which variables affect it.

Objectives:

This study aimed to assess the effect of renal allograft failure on patient survival.

Patients and Methods:

This retrospective cohort study included 405 renal transplant patients from Kerman University of Medical Sciences hospital, Kerman, Iran from 2004 to 2010. Kaplan-Meier method was used to estimate survival rates of patients, and time-dependent Cox regression was used to examine the effect of allograft failure on patient survival.

Results:

During 4.06 years (median) of follow-up 28 (6.9%) patients died and 20 (71.4%) of dead patients had allograft failure. Survival rate of patients with allograft failure at 1-, 3-, 5-, and 7-year were 0.98, 0.8, 0.53, and 0.53, respectively; in patients with allograft function these values were 0.99, 0.98, 0.97, and 0.96, respectively. The unadjusted death rate was 0.5 per 100 patient years for the maintained allograft function, which increased to 9 per 100 patient years for patients following allograft failure. In fully adjusted model the risk of death increased in patients with allograft failure (HR = 2.09; 95% CI: 1.56-2.81), pretransplant diabetes (HR = 2.81; 95% CI: 1.2-6.7), patients with BMI ≥ 25 (vs. 18.5 ≤ BMI < 25) (HR = 3.56; 95% CI: 1.09-11.6). With an increase in recipient age this risk increased (HR = 1.04 per year increase; 95% CI: 1.01-6.7). Receiving a living kidney transplant decreased this risk (HR = 0.52; 95% CI: 0.39-0.69).

Conclusions:

An increase in recipient age and BMI, affliction with diabetes, allograft failure, and receiving deceased kidney transplant increased the risk of death.

Model comparisons of competing risk and recurrent events for graft failure in renal transplant recipients

BACKGROUND AND OBJECTIVES

Risk factor analysis of long-term graft survival in kidney transplant recipients is usually based on Cox regression models of time to first occurrence of doubling of serum creatinine or graft loss (DSCGL). However, death is a competing cause of failure, and censoring patients who die could bias estimates. We therefore compared estimates of time to first event versus estimates that included death as a competing risk and recurrent events.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A Cox regression analysis of 1997-2002 data from the Assessment of Lescol in Renal Transplant (ALERT) trial population identified an eight-factor risk model, by analyzing time to first occurrence of DSCGL. The same factors were re-analyzed, allowing for death as competing. The probability of survival free of DSCGL was estimated; and two recurrent models (marginal and conditional) were used for time to events.

RESULTS

Creatinine, systolic BP, and HLA-DR mismatches lost 33%-46% of their strength of association with DSCGL when death was included as a competing risk. Small changes were observed if recurrent events were analyzed in the marginal model.

CONCLUSION

The relationship between serum creatinine and DSCGL was attenuated when death was considered as a competing risk; inclusion of recurrent events had little effect. These findings have important implications for analysis and trial design in populations at high mortality risk.

Cause of death with graft function among renal transplant recipients in an integrated healthcare system

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death in renal transplant recipients with a functioning allograft. Modification of CVD risk factors may, therefore, decrease overall mortality in this patient population. We studied renal transplant recipients within an integrated healthcare system (IHS) that uses case management and electronic health records to determine mortality from CVD.

METHODS

We retrospectively collected data on all renal transplant recipients over a 10-year period. The primary endpoint was death with graft function (DWGF). Cardiovascular events were used as secondary endpoints. We determined the cause of death and collected laboratory data. The data were analyzed using Student's t test for continuous data, chi square for categorical data, and multivariate logistic regression. Survival was determined using the Kaplan-Meier product-limit method.

RESULTS

Death from "other" causes accounted for 29%. This was followed by CVD (24%), infection (16%), and malignancy (12%). The most common "other" causes were diabetes mellitus and end-stage renal disease. Overall, lower hemoglobin, uncontrolled blood pressure, and lower albumin levels were associated with DWGF. There were 184 cardiovascular events in total. Low-density lipid levels were lower in the group with cardiovascular events and DWGF. The use of antihypertensive and antihyperlipidemic agents was similar between the two groups with the exception of diuretics, which were used more often in the DWGF group.

CONCLUSIONS

There was a low rate of DWGF because of CVD within this IHS. It is possible that coordinated care within an IHS leads to improved cardiovascular mortality.