Frailty and the Kidney Transplant Wait List: Protocol for a Multicenter Prospective Study

Old Age and Frailty in Deceased Organ Transplantation and Allocation-A Plea for Geriatric Assessment and Prehabilitation

Due to demographic ageing and medical progress, the number and proportion of older organ donors and recipients is increasing. At the same time, the medical and ethical significance of ageing and old age for organ transplantation needs clarification. Advanced age is associated with the frailty syndrome that has a negative impact on the success of organ transplantation. However, there is emerging evidence that frailty can be modified by suitable prehabilitation measures. Against this backdrop, we argue that decision making about access to the transplant waiting list and the allocation of donor organs should integrate geriatric expertise in order to assess and manage frailty and impairments in functional capacity. Prehabilitation should be implemented as a new strategy for pre-operative conditioning of older risk patients' functional capacity. From an ethical point of view, advanced chronological age per se should not preclude the indication for organ transplantation and the allocation of donor organs.

A cross-validation statistical framework for asymmetric data integration

The proliferation of biobanks and large public clinical data sets enables their integration with a smaller amount of locally gathered data for the purposes of parameter estimation and model prediction. However, public data sets may be subject to context-dependent confounders and the protocols behind their generation are often opaque; naively integrating all external data sets equally can bias estimates and lead to spurious conclusions. Weighted data integration is a potential solution, but current methods still require subjective specifications of weights and can become computationally intractable. Under the assumption that local data are generated from the set of unknown true parameters, we propose a novel weighted integration method based upon using the external data to minimize the local data leave-one-out cross validation (LOOCV) error. We demonstrate how the optimization of LOOCV errors for linear and Cox proportional hazards models can be rewritten as functions of external data set integration weights. Significant reductions in estimation error and prediction error are shown using simulation studies mimicking the heterogeneity of clinical data as well as a real-world example using kidney transplant patients from the Scientific Registry of Transplant Recipients.

Development of an Administrative Data-Based Frailty Index for Older Adults Receiving Dialysis

Background

Frailty is present in ≥50% of older adults receiving dialysis. Our objective was to a develop an administrative data–based frailty index and assess the frailty index’s predictive validity for mortality and future hospitalizations.

Methods

We used United States Renal Data System data to establish two cohorts of adults aged ≥65 years, initiating dialysis in 2013 and in 2017. Using the 2013 cohort (development dataset), we applied the deficit accumulation index approach to develop a frailty index. Adjusting for age and sex, we assessed the extent to which the frailty index predicts the hazard of time until death and time until first hospitalization over 12 months. We assessed the Harrell’s C-statistic of the frailty index, a comorbidity index, and jointly. The 2017 cohort was used as a validation dataset.

Results

Using the 2013 cohort (n=20,974), we identified 53 deficits for the frailty index across seven domains: disabilities, diseases, equipment, procedures, signs, tests, and unclassified. Among those with ≥1 deficit, the mean (SD) frailty index was 0.30 (0.13), range 0.02–0.72. Over 12 months, 18% (n=3842) died, and 55% (n=11,493) experienced a hospitalization. Adjusted hazard ratios for each 0.1-point increase in frailty index in models of time to death and time to first hospitalization were 1.41 (95% confidence interval, 1.37 to 1.44) and 1.33 (95% confidence interval, 1.31 to 1.35), respectively. For mortality, C-statistics for frailty index, comorbidity index, and both indices were 0.65, 0.65, and 0.66, respectively. For hospitalization, C-statistics for frailty index, comorbidity index, and both indices were 0.61, 0.60, and 0.61, respectively. Data from the 2017 cohort were similar.

Conclusions

We developed a novel frailty index for older adults receiving dialysis. Further studies are needed to improve on this frailty index and validate its use for clinical and research applications.

Outcomes of patients with COVID-19 on kidney replacement therapy: a comparison among modalities in England

BACKGROUND

Chronic kidney disease is a recognized risk factor of poor outcomes from coronavirus disease 2019 (COVID-19).

METHODS

This retrospective cohort study used the UK Renal Registry database of people on kidney replacement therapy (KRT) at the end of 2019 in England and who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between 1 March 2020 and 31 August 2020 to analyse the incidence and outcomes of COVID-19 among different KRT modalities. Comparisons with 2015-2019 mortality data were used to estimate excess deaths.

RESULTS

A total of 2783 individuals on KRT tested positive for SARS-CoV-2. Patients from more-deprived areas {most deprived versus least deprived hazard ratio [HR] 1.20 [95% confidence interval (CI) 1.04-1.39]} and those with diabetes compared with those without [HR 1.51 (95% CI 1.39-1.64)] were more likely to test positive. Approximately 25% of in-centre haemodialysis and transplanted patients died within 28 days of testing positive compared with 36% of those on home therapies. Mortality was higher in those ≥80 years of age compared with those 60-79 years [odds ratio (OR) 1.71 (95% CI 1.34-2.19)] and much lower in those listed for transplantation compared with those not listed [OR 0.56 (95% CI 0.40-0.80)]. Overall, excess mortality in 2020 for people on KRT was 36% higher than the 2015-2019 average. Excess deaths peaked in April 2020 at the height of the pandemic and were characterized by wide ethnic and regional disparities.

CONCLUSIONS

The impact of COVID-19 on the English KRT population highlights their extreme vulnerability and emphasizes the need to protect and prioritize this group for vaccination. COVID-19 has widened underlying inequalities in people with kidney disease, making interventions that address health inequalities a priority.

Physical Inactivity: A Modifiable Risk Factor for Morbidity and Mortality in Kidney Transplantation

In patients with chronic kidney disease, sedentary behavior is widely recognized as a significant risk factor for cardiovascular disease, diabetes, obesity, osteoporosis, cancer, and depression. Nevertheless, the real impact of physical inactivity on the health of kidney transplant (KT) recipients remains uncertain. Over the last decade, there has been a renewed interest in exploring the effects of regular physical exercise on transplant-related outcomes. There is now mounting evidence that physical activity may reduce the burden of cardiovascular risk factors, preserve allograft function, minimize immunosuppression requirement, and ameliorate the quality of life of KT recipients. Many positive feedbacks can be detected in the early stages of the interventions and with a minimal exercise load. Despite these encouraging results, the perceived role of physical activity in the management of KT candidates and recipients is often underrated. The majority of trials on exercise training are small, relatively short, and focused on surrogate outcomes. While waiting for larger studies with longer follow-up, these statistical limitations should not discourage patients and doctors from initiating exercise and progressively increasing intensity and duration. This narrative review summarizes current knowledge about the deleterious effects of physical inactivity after KT. The benefits of regular physical exercise are also outlined.

Prevalence of Frailty in Patients Referred to the Kidney Transplant Waitlist

Background

Comparisons between frailty assessment tools for waitlist candidates are a recognized priority area for kidney transplantation. We compared the prevalence of frailty using three established tools in a cohort of waitlist candidates.

Methods

Waitlist candidates were prospectively enrolled from 2016 to 2020 across five centers. Frailty was measured using the Frailty Phenotype (FP), a 37-variable frailty index (FI), and the Clinical Frailty Scale (CFS). The FI and CFS were dichotomized using established cutoffs. Agreement was compared using κ coefficients. Area under the receiver operating characteristic (ROC) curves were generated to compare the FI and CFS (treated as continuous measures) with the FP. Unadjusted associations between each frailty measure and time to death or waitlist withdrawal were determined using an unadjusted Cox proportional hazards model.

Results

Of 542 enrolled patients, 64% were male, 80% were White, and the mean age was 54±14 years. The prevalence of frailty by the FP was 16%. The mean FI score was 0.23±0.14, and the prevalence of frailty was 38% (score of ≥0.25). The median CFS score was three (IQR, 2-3), and the prevalence was 15% (score of ≥4). The κ values comparing the FP with the FI (0.44) and CFS (0.27) showed fair to moderate agreement. The area under the ROC curves for the FP and FI/CFS were 0.86 (good) and 0.69 (poor), respectively. Frailty by the CFS (HR, 2.10; 95% CI, 1.04 to 4.24) and FI (HR, 1.79; 95% CI, 1.00 to 3.21) was associated with death or permanent withdrawal. The association between frailty by the FP and death/withdrawal was not statistically significant (HR, 1.78; 95% CI, 0.79 to 3.71).

Conclusion

Frailty prevalence varies by the measurement tool used, and agreement between these measurements is fair to moderate. This has implications for determining the optimal frailty screening tool for use in those being evaluated for kidney transplant.