Clinical Assessment of Mortality Risk in Renal Transplant Candidates in Spain

Physiological Age by Artificial Intelligence-Enhanced Electrocardiograms as a Novel Risk Factor of Mortality in Kidney Transplant Candidates

BACKGROUND

Mortality risk assessment before kidney transplantation (KT) is imperfect. An emerging risk factor for death in nontransplant populations is physiological age as determined by the application of artificial intelligence to the electrocardiogram (ECG). The aim of this study was to examine the relationship between ECG age and KT waitlist mortality.

METHODS

We applied a previously developed convolutional neural network to the ECGs of KT candidates evaluated 2014 to 2019 to determine ECG age. We used a Cox proportional hazard model to examine whether ECG age was associated with waitlist mortality.

RESULTS

Of the 2183 patients evaluated, 59.1% were male, 81.4% were white, and 11.4% died during follow-up. Mean ECG age was 59.0 ± 12.0 y and mean chronological age at ECG was 53.3 ± 13.6 y. After adjusting for chronological age, comorbidities, and other characteristics associated with mortality, each increase in ECG age of >10 y than the average ECG age for patients of a similar chronological age was associated with an increase in mortality risk (hazard ratio 3.59 per 10-y increase; 95% confidence interval, 2.06-5.72; P  < 0.0001).

CONCLUSIONS

ECG age is a risk factor for KT waitlist mortality. Determining ECG age through artificial intelligence may help guide risk-benefit assessment when evaluating candidates for KT.

Kidney transplant in the next decade: Strategies, challenges and vision of the future

Although the results of kidney transplantation (KT) have improved substantially in recent years, a chronic and inexorable loss of grafts mainly due to the death of the patient and chronic dysfunction of the KT, continues to be observed. The objectives, thus, to optimize this situation in the next decade are fundamentally focused on minimizing the rate of kidney graft loss, improving patient survival, increasing the rate of organ procurement and its distribution, promoting research and training in health professionals and the development of scientific registries providing clinical and reliable information that allow us to optimize our clinical practice in the field of KT. With this perspective, this review will deep into: (1) strategies to avoid chronic dysfunction and graft loss in the medium and long term; (2) to prolong patient survival; (3) strategies to increase the donation, maintenance and allocation of organs; (4) promote clinical and basic research and training activity in KT; and (5) the analysis of the results in KT by optimizing and merging scientific registries.

Peripheral Vascular Disease and Kidney Transplant Outcomes: Rethinking an Important Ongoing Complication

Peripheral vascular disease (PVD) is highly prevalent in patients on the waiting list for kidney transplantation (KT) and after transplantation and is associated with impaired transplant outcomes. Multiple traditional and nontraditional risk factors, as well as uremia- and transplant-related factors, affect 2 processes that can coexist, atherosclerosis and arteriosclerosis, leading to PVD. Some pathogenic mechanisms, such as inflammation-related endothelial dysfunction, mineral metabolism disorders, lipid alterations, or diabetic status, may contribute to the development and progression of PVD. Early detection of PVD before and after KT, better understanding of the mechanisms of vascular damage, and application of suitable therapeutic approaches could all minimize the impact of PVD on transplant outcomes. This review focuses on the following issues: (1) definition, epidemiological data, diagnosis, risk factors, and pathogenic mechanisms in KT candidates and recipients; (2) adverse clinical consequences and outcomes; and (3) classical and new therapeutic approaches.

Outcomes of ABO-incompatible kidney transplantation in older patients: a national cohort study

BACKGROUND

Outcomes of ABO-incompatible living donor kidney transplantation (ABOi LDKT) in older individuals have not been established.

METHODS

This multicentric observational study, using data from the Korean Organ Transplantation Registry database, included 634 older patients (≥60 years) undergoing kidney transplantation. We compared clinical outcomes of ABOi LDKT (n = 80) with those of ABO-compatible LDKT (ABOc LDKT, n = 222) and deceased donor kidney transplantation (DDKT, n = 332) in older patients.

RESULTS

Death-censored graft survival was similar between the three groups (P = 0.141). Patient survival after ABOi LDKT was similar to that after ABOc LDKT (P = 0.489) but higher than that after DDKT (P = 0.038). In multivariable analysis, ABOi LDKT was not risk factor (hazard ratio [HR] 1.73, 95% confidence interval [CI] 0.29-10.38, P = 0.548), while DDKT was significant risk factor (HR 3.49, 95% CI 1.01-12.23, P = 0.049) for patient survival. Although ABOi LDKT showed higher biopsy-proven acute rejection than ABOc LDKT, the difference was not significant after adjustment with covariates. However, ABOi LDKT was significant risk factor for infection (HR 1.66, 95% CI 1.12-2.45, P = 0.012).

CONCLUSIONS

In older patients, ABOi LDKT was not inferior to ABOc LDKT and was superior to DDKT for patient survival. ABOi LDKT can be recommended for older patients, rather than waiting for DDKT.

Quantifying the Treatment Effect of Kidney Transplantation Relative to Dialysis on Survival Time: New Results Based on Propensity Score Weighting and Longitudinal Observational Data from Sweden

Using observational data to assess the treatment effects on outcomes of kidney transplantation relative to dialysis for patients on renal replacement therapy is challenging due to the non-random selection into treatment. This study applied the propensity score weighting approach in order to address the treatment selection bias of kidney transplantation on survival time compared with dialysis for patients on the waitlist. We included 2676 adult waitlisted patients who started renal replacement therapy in Sweden between 1 January 1995, and 31 December 2012. Weibull and logistic regression models were used for the outcome and treatment models, respectively. The potential outcome mean and the average treatment effect were estimated using an inverse-probability-weighted regression adjustment approach. The estimated survival times from start of renal replacement therapy were 23.1 years (95% confidence interval (CI): 21.2-25.0) and 9.3 years (95% CI: 7.8-10.8) for kidney transplantation and dialysis, respectively. The survival advantage of kidney transplantation compared with dialysis was estimated to 13.8 years (95% CI: 11.4-16.2). There was no significant difference in the survival advantage of transplantation between men and women. Controlling for possible immortality bias reduced the survival advantage to 9.1-9.9 years. Our results suggest that kidney transplantation substantially increases survival time compared with dialysis in Sweden and that this consequence of treatment is equally distributed over sex.

Outcomes of Patients Suspended From the National Kidney Transplant Waiting List in the United Kingdom Between 2000 and 2010

BACKGROUND

In the United Kingdom, 1 in 3 patients on the National Kidney Transplant Waiting List (NKTWL) is suspended from the list at least once during their wait. The mortality of this large cohort of patients remains underreported and poorly described.

METHODS

We linked patient records from the UK transplant registry to mortality data from the Office of National Statistics and evaluated the impact of a clinically induced suspension event by estimating hazard ratios (HRs) that compared mortality and graft survival between those who had experienced a suspension event and those who had not.

RESULTS

Between January 1, 2000, and December 31, 2010, 16.7% (2221/13 322) of all patients registered on the NKTWL were suspended. Forty-eight percent (588/1225) of those who were suspended and who were never transplanted died, most often from cardiothoracic causes. A suspension event was associated with increased mortality from the time of listing (adjusted HR [aHR], 1.79; 1.64-1.95) and from the time of transplantation (aHR, 1.20; 1.06-1.37; P = 0.005). Graft survival was also poorer in those who had been suspended (aHR, 1.13; 1.01-1.28; P = 0.04).

CONCLUSIONS

Patients suspended on the NKTWL have a significantly higher rate of mortality both on the waiting list and following transplantation. Earlier prioritization of patients at risk of experiencing a suspension event may improve their outcomes.

Waiting List and Kidney Transplant Vascular Risk: An Ongoing Unmet Concern

BACKGROUND

Chronic kidney disease (CKD) is an important independent risk factor for adverse cardiovascular events in patients waitlisted for kidney transplantation (KT). Although KT reduces cardiovascular risk, these patients still have a higher all-cause and cardiovascular mortality than the general population. This concerning situation is due to a high burden of traditional and nontraditional risk factors as well as uremia-related factors and transplant-specific factors, leading to 2 differentiated processes under the framework of CKD, atherosclerosis and arteriosclerosis. These can be initiated by insults to the vascular endothelial endothelium, leading to vascular calcification (VC) of the tunica media or the tunica intima, which may coexist. Several pathogenic mechanisms such as inflammation-related endothelial dysfunction, mineral metabolism disorders, activation of the renin-angiotensin system, reduction of nitric oxide, lipid disorders, and the fibroblast growth factor 23-klotho axis are involved in the pathogenesis of atherosclerosis and arteriosclerosis, including VC.

SUMMARY

This review focuses on the current understanding of atherosclerosis and arteriosclerosis, both in patients on the waiting list as well as in kidney transplant recipients, emphasizing the cardiovascular risk factors in both populations and the inflammation-related pathogenic mechanisms. Key Message: The importance of cardiovascular risk factors and the pathogenic mechanisms related to inflammation in patients waitlisted for KT and kidney transplant recipients.

Living Donor Kidney Transplantation Should Be Promoted Among "Elderly" Patients

Age criteria for kidney transplantation have been liberalized over the years resulting in more waitlisted elderly patients. What are the prospects of elderly patients on the waiting list?

Kidney transplant registries: How to optimise their utility?

The scientific Registries (RE) in renal transplantation (Tx) are very useful since they allow us to identify risk factors in this population and facilitate contrasting the information with other national and international registries, contributing to establishing strategies which improve outcomes in terms of survival. They constitute an organised and planned system that uses observational methods and standardised systematic processes, including adjusted risk models, to essentially evaluate survival outcomes. The scientific RE are complemented with clinical trials providing scientific evidence, but inexcusably need adequate statistical analysis to generate reliable clinical data that contribute to optimising the prognosis of the transplant population. In addition, scientific RE provide valuable information on the performance of Tx programmes and help generate prognostic indexes, which could contribute to improving survival. Under these prerequisites, this review will assess the following aspects related to the scientific RE in the Tx: 1) the concept and importance of implementing RE in Tx; 2) the measures that are needed for the correct execution of the scientific RE; 3) the benefits, quality and limitations of RE; 4) the statistical tools for the adequate analysis of survival; and 5) utility of RE in the evaluation of performance, quality and surveillance of transplant programmes and the generation of comorbidity índices.

Comorbidity, Frailty, and Waitlist Mortality among Kidney Transplant Candidates of All Ages

BACKGROUND

Kidney transplantation (KT) candidates often present with multiple comorbidities. These patients also have a substantial burden of frailty, which is also associated with increased mortality. However, it is unknown if frailty is merely a surrogate for comorbidity, itself an independent domain of risk, or if frailty and comorbidity have differential effects. Better understanding the interplay between these 2 constructs will improve clinical decision making in KT candidates.

OBJECTIVE

To test whether comorbidity is equally associated with waitlist mortality among frail and nonfrail KT candidates and to test whether measuring both comorbidity burden and frailty improves mortality risk prediction.

METHODS

We studied 2,086 candidates on the KT waitlist (November 2009 - October 2017) in a multicenter cohort study, in whom frailty and comorbidity were measured at evaluation. We quantified the association between Charlson comorbidity index (CCI) adapted for end-stage renal disease and waitlist mortality using an adjusted Cox proportional hazards model and tested whether this association differed between frail and nonfrail candidates.

RESULTS

At evaluation, 18.1% of KT candidates were frail and 51% had a high comorbidity burden (CCI score ≥2). Candidates with a high comorbidity burden were at 1.38-fold (95% CI 1.01-1.89) increased risk of waitlist mortality. However, this association differed by frailty status (p for interaction = 0.01): among nonfrail candidates, a high comorbidity burden was associated with a 1.66-fold (95% CI 1.17-2.35) increased mortality risk; among frail candidates, here was no statistically significant association (HR 0.75, 95% CI 0.44-1.29). Adding this interaction between comorbidity and frailty to a mortality risk estimation model significantly improved prediction, increasing the c-statistic from 0.640 to 0.656 (p < 0.001).

CONCLUSIONS

Nonfrail candidates with a high comorbidity burden at KT evaluation have an increased risk of waitlist mortality. Importantly, comorbidity is less of a concern in already high-risk patients who are frail.

Survival in Southern European patients waitlisted for kidney transplant after graft failure: A competing risk analysis

Background

Whether patients waitlisted for a second transplant after failure of a previous kidney graft have higher mortality than transplant-näive waitlisted patients is uncertain.

Methods

We assessed the relationship between a failed transplant and mortality in 3851 adult KT candidates, listed between 1984–2012, using a competing risk analysis in the total population and in a propensity score-matched cohort. Mortality was also modeled by inverse probability weighting (IPTW) competing risk regression.

Results

At waitlist entry 225 (5.8%) patients had experienced transplant failure. All-cause mortality was higher in the post-graft failure group (16% vs. 11%; P = 0.033). Most deaths occurred within three years after listing. Cardiovascular disease was the leading cause of death (25.3%), followed by infections (19.3%). Multivariate competing risk regression showed that prior transplant failure was associated with a 1.5-fold increased risk of mortality (95% confidence interval [CI], 1.01–2.2). After propensity score matching (1:5), the competing risk regression model revealed a subhazard ratio (SHR) of 1.6 (95% CI, 1.01–2.5). A similar mortality risk was observed after the IPTW analysis (SHR, 1.7; 95% CI, 1.1–2.6).

Conclusions

Previous transplant failure is associated with increased mortality among KT candidates after relisting. This information is important in daily clinical practice when assessing relisted patients for a retransplant.

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.

Peripheral Vascular Disease and Death in Southern European Kidney Transplant Candidates: A Competing Risk Modeling Approach

BACKGROUND

The association between peripheral vascular disease (PVD) and survival among kidney transplant (KT) candidates is uncertain.

METHODS

We assessed 3851 adult KT candidates from the Andalusian Registry between 1984 and 2012. Whereas 1975 patients received a KT and were censored, 1876 were on the waiting list at any time. Overall median waitlist time was 21.2 months (interquartile range, 11-37.4). We assessed the association between PVD and mortality in waitlisted patients using a multivariate Cox regression model, with a competing risk approach as a sensitivity analysis.

RESULTS

Peripheral vascular disease existed in 308 KT candidates at waitlist entry. The prevalence of PVD among nondiabetic and diabetic patients was 4.5% and 25.3% (P < 0.0001). All-cause mortality was higher in candidates with PVD (45% vs 21%; P < 0.0001). Among patients on the waiting list (n = 1876) who died (n = 446; 24%), 272 (61%) died within 2 years after listing. Cumulative incidence of all-cause mortality at 2 years in patients with and without PVD was 23% and 6.4%, respectively (P < 0.0001); similar differences were observed in patients with and without diabetes. By competing risk models, PVD was associated with a 1.9-fold increased risk of mortality (95% confidence interval [95% CI], 1.4-2.5). This association was stronger in waitlisted patients without cardiac disease (subhazard ratio, 2.2; 95% CI, 1.6-3.1) versus those with cardiac disorders (subhazard ratio, 1.5; 95% CI, 0.9-2.5). No other significant interactions were observed. Similar results were seen after excluding diabetics.

CONCLUSIONS

Peripheral vascular disease is a strong predictor of mortality in KT candidates. Identification of PVD at list entry may contribute to optimize targeted therapeutic interventions and help prioritize high-risk KT candidates.

Impact of comorbidity on outcome in kidney transplant recipients: a retrospective study in Italy

The aim of this study was to relate in-hospital mortality (IHM), cardiovascular events (CVEs) and non-immunologic comorbidity evaluated on the basis of International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codification, in Italian kidney transplant recipients (KTRs). We evaluated IHM and admissions due to CVEs between 2000 and 2013 recorded in the database of the region Emilia Romagna. The Elixhauser score was calculated for evaluation of non-immunologic comorbidity. Three main outcomes (i.e. IHM, admission due to major CVEs and combined outcome) were the dependent variables of the multivariate models, while age, gender and Elixhauser score were the independent ones. During the examined period, a total of 9063 admissions in 3648 KTRs were recorded; 1945 patients were males (53.3 %) and 1703 females (46.7 %) and the mean age was 52.9 ± 13.1 years. The non-immunological impaired status of the KTRs, examined by the Elixhauser score, was 3.88 ± 4.29. During the 14-year follow-up period, IHM for any cause was 3.2 % (n = 117), and admissions due to CVEs were 527 (5.8 %). Age and comorbidity were independently associated with CVEs, IHM and the combined outcome. Male gender was independently associated with IHM and combined outcome, but not with CVEs. Evaluation of non-immunological comorbidity is important in KTRs and identification of high-risk patients for major clinical events could improve outcome. Moreover, comorbidity could be even more important in chronic kidney disease patients who are waiting for a kidney transplant.

A High Comorbidity Score Should Not be a Contraindication for Kidney Transplantation

BACKGROUND

Currently, potential kidney transplant patients more often suffer from comorbidities. The Charlson Comorbidity Index (CCI) was developed in 1987 and is the most used comorbidity score. We questioned to what extent number and severity of comorbidities interfere with graft and patient survival. Besides, we wondered whether the CCI was best to study the influence of comorbidity in kidney transplant patients.

METHODS

In our center, 1728 transplants were performed between 2000 and 2013. There were 0.8% cases with missing values. Nine pretransplant comorbidity covariates were defined: cardiovascular disease, cerebrovascular accident, peripheral vascular disease, diabetes mellitus, liver disease, lung disease, malignancy, other organ transplantation, and human immunodeficiency virus positivity. The CCI used was unadjusted for recipient age. The Rotterdam Comorbidity in Kidney Transplantation score was developed, and its influence was compared to the CCI. Kaplan-Meier analysis and multivariable Cox proportional hazards analysis, corrected for variables with a known significant influence, were performed.

RESULTS

We noted 325 graft failures and 215 deaths. The only comorbidity covariate that significantly influenced graft failure censored for death was peripheral vascular disease. Patient death was significantly influenced by cardiovascular disease, other organ transplantation, and the total comorbidity scores. Model fit was best with the Rotterdam Comorbidity in Kidney Transplantation score compared to separate comorbidity covariates and the CCI. In the population with the highest comorbidity score, 50% survived more than 10 years.

CONCLUSIONS

Despite the negative influence of comorbidity, patient survival after transplantation is remarkably good. This means that even patients with extensive comorbidity should be considered for transplantation.

Current state of clinical end-points assessment in transplant: Key points

Solid organ transplantation is the treatment of choice for patients with end-stage organ disease. However, organ transplantation can stress the cardiovascular system and decrease immune surveillance, leading to early mortality and graft loss due to multiple underlying comorbidities. Clinical end-points in transplant include death and graft failure. Thus, generating accurate predictive models through regression models is crucial to test for definitive clinical post-transplantation end-points. Survival predictive models should assemble efficient surrogate markers or prognostic factors to generate a minimal set of variables derived from a proper modeling strategy through regression models. However, a few critical points should be considered when reporting survival analyses and regression models to achieve proper discrimination and calibration of the predictive models. Additionally, population-based risk scores may underestimate risk prediction in transplant. The application of predictive models in these patients should therefore incorporate both classical and non-classical risk factors, as well as community-based health indicators and transplant-specific factors to quantify the outcomes in terms of survival properly. This review focuses on assessment of clinical end-points in transplant through regression models by combining predictive and surrogate variables, and considering key points in these analyses to accurately predict definitive end-points, which could aid clinicians in decision making.