Dementia is a relative contraindication to transplantation; however, there are no guidelines for evaluating cognitive impairment in transplant candidates when the degree of cognitive impairment does not fulfill the diagnostic criteria for dementia. Cognitive impairment is increasingly recognized as a risk factor for adverse outcomes in older adults, including adults reaching end-stage renal disease (ESRD).1 In the community-dwelling geriatric population, cognitive impairment is associated with an increased risk of mortality,2,3 hospitalization,4 admission to an intensive care unit,5 and discharge to a nursing home after hospitalization.4,6 We previously reported that incident dementia and Alzheimer disease are associated with an elevated risk of graft loss and mortality in older adults after kidney transplantation (KT).7 Cognitive impairment, which often precedes dementia, detected before KT has not been well characterized and might also be independently associated with graft loss and mortality in KT recipients.
Studies of chronic kidney disease (CKD) patients have shown that cognitive impairment increases in prevalence and severity as kidney function declines.8-13 Cognitive changes across multiple domains, including executive function and memory, begin early in CKD progression and continue after reaching ESRD.13 As a result, patients with ESRD have twice the prevalence of moderate to severe cognitive impairment as the general population.14,15 Additionally, dialysis initiation has been associated with a decrease in executive function in a multicenter cohort study.16 Cognitive impairment in dialysis patients has been independently associated with an elevated risk of mortality,1,17,18 emphasizing the importance of transplantation in this population.
Because the prevalence of cognitive impairment in ESRD patients is high, cognitive impairment is likely also prevalent but underdiagnosed in KT recipients. We hypothesized that baseline cognitive impairment might be independently associated with graft loss and mortality after KT. Using a prospective, longitudinal, 2-center cohort of KT recipients, we measured global cognitive function and estimated the association between cognitive impairment and all-cause graft loss (ACGL), adjusting for recipient, donor, and transplant characteristics.
MATERIALS AND METHODS
Prospective Cohort Data Source
This study used data from a prospective, longitudinal 2-center cohort study at the Johns Hopkins Hospital (N = 798), Baltimore, Maryland and the University of Michigan Hospital (N = 66), Ann Arbor, Michigan, which has been described elsewhere.19-22 Briefly, study participants were enrolled before KT and consented to medical record abstraction to allow for the identification of demographics and comorbidities. All study participants underwent cognitive testing including the Modified Mini-Mental State (3MS) exam upon admission for KT. The clinical and research activities being reported are consistent with the Declaration of Helsinki and Declaration of Istanbul. The Institutional Review Boards of Johns Hopkins Hospital and the University of Michigan approved this study, and all participants provided written informed consent.
National Registry Data Source
This study also used data from the Scientific Registry of Transplant Recipients (SRTR) external release made available in September 2017. The SRTR data system includes data on all donors, waitlist candidates, and transplant recipients in the United States, submitted by members of the Organ Procurement and Transplantation Network (OPTN), and has been previously described.23 The Health Resources and Services Administration, US Department of Health and Human Services provides oversight to the activities of the OPTN and SRTR contractors. Using SRTR, we identified 101718 adults (age ≥ 18 years) recipients who underwent KT between August 2009 and July 2016. We cross-validated key recipient, donor, and transplant factors in the linkage between our prospective cohort data source and the SRTR. All recipients were successfully linked with SRTR based on age, sex, unique transplant ID, and date of transplant. We rely on the national registry’s capture of data for all analytic variables and outcomes with the exception of cognitive impairment and additional comorbidity statuses (described below).
Global Cognitive Function
The 3MS examination, a validated assessment of global cognitive function,24 was administered to study participants at admission for KT, which was a median (interquartile range [IQR]) of 1 (0–1) day before KT. Scores for the 3MS examination range between 0 and 100 (lower scores indicate worse cognition) based on responses to 15 exam components including temporal and spatial orientation, multistage commands, and recall. Although there are no standardized thresholds for cognitive impairment in the KT candidate population, it is common in the literature to use standard deviation (SD) thresholds to define cognitive impairment in novel populations.24,25 Consistent with this convention, we defined any cognitive impairment as a 3MS score less than 80 (-1 SD) and severe cognitive impairment as a 3MS score less than 60 (-2 SD). By definition, participants with severe cognitive impairment were a subset of those with cognitive impairment and were therefore included in both groups for the purposes of analyses. In sensitivity analyses, we considered cutoffs for cognitive impairment stratified by age and educational attainment based on normative data from an external population of community-dwelling adults26 (SDC, Materials and Methods, http://links.lww.com/TP/B630).
Model Variable Selection
We used Cox proportional hazards regression to assess the independent association between cognitive impairment and ACGL, defined as graft loss or mortality. The independent association between cognitive impairment and death-censored graft failure (DCGF) and mortality, evaluated separately, are presented in supplemental materials using Cox proportional hazards regression (Tables S1, S2, SDC, http://links.lww.com/TP/B630). All analyses were stratified by living or deceased donor status, given the differences in the relevant risk factors. For example, cold ischemia time (CIT) is known to be an important risk factor for graft failure among deceased donor recipients, but CIT is not associated with graft failure in living donor recipients.27 Stratification is also consistent with the SRTR risk-adjustment models.28 In addition to traditional Cox regression, we also present results from hybrid registry-augmented Cox regression models, a statistically efficient method that brings precisely estimated coefficients from the national registry model into the prospective cohort model.29,30
Potential confounders were identified using the SRTR risk-adjustment models.28 Covariates included in the final multivariable models were selected to optimize goodness-of-fit as assessed by the log-likelihood test. For living donor kidney transplant (LDKT) recipients, we adjusted for recipient characteristics (age, Black race, Hispanic ethnicity, years on dialysis, diabetes status, panel reactive antibody [PRA] at transplant, college education, employment status, public insurance status, hepatitis C virus [HCV] infection, body mass index [BMI], hypertension status, history of transplantation, and Charlson Comorbidity Index [CCI]), donor characteristics (age, BMI), and transplant characteristics (recipient and donor both male, zero HLA mismatches, blood type incompatibility, and transplant date).31 For deceased donor kidney transplant (DDKT) recipients, we adjusted for recipient factors (age, sex, Black race, Hispanic ethnicity, years on dialysis, diabetes status, PRA at transplant, college education, BMI, hypertension status, history of transplantation, and CCI), donor factors (Kidney Donor Profile Index [KDPI]),32 and transplant factors (CIT and transplant date).
Handling of Missingness
Variable missingness in the national registry data was quite low: CIT (5.2%), education (4.6%), PRA at transplant (2.8%), recipient BMI (1.6%), donor BMI (1.1%), time on dialysis (0.6%), HLA mismatch (0.2%), all other variables <0.1%. We handled missing covariate values using multiple imputation by chained equations (SDC, Materials and Methods).
For participants in the prospective cohort, differences in recipient, donor, and transplant characteristics by cognitive impairment were assessed using the χ2 (categorical variables) and Mann-Whitney rank-sum (continuous variables) tests. We report frailty as measured by Fried33; recipients were classified as frail if they had at least 3 of the 5 frailty components as we have previously published.34-37 Low functional status captures recipients unable to perform normal activities. Functional status is reported to the OPTN on a percent scale; we classified low functional status as 70% or lower, which is the point at which a patient is unable to perform normal activity. We classified induction agents as antibody depleting (muromonab-CD3, equine antilymphocyte globulin, lymphocyte immune globulin, thymoglobulin, rabbit antithymocyte globulin, alemtuzumab), or nonantibody depleting (daclizumab, basiliximab, and rituximab). Differences in the survivor function were assessed using the log-rank test. Functional forms of continuous variables were empirically derived using Martingale residuals. Proportional hazards were confirmed visually by graphing the log-log plot of survival and statistically using Schoenfeld residuals. We used a 2-sided α of 0.05 to indicate a statistically significant difference. We report adjusted hazard ratio (aHR) 95% confidence intervals as per the method of Louis and Zeger.38 This method shows the lower 95% confidence interval first as a subscript, then the point estimate, and finally the upper 95% confidence interval as a subscript. All analyses were performed using Stata 15/MP for Linux (College Station, Texas).
Prospective Cohort Study Population
Participants in our prospective, longitudinal 2-center cohort were followed for a median (IQR) of 3.3 (2.0–5.2) years and contributed a total of 2640 person-years at risk. Among the 864 KT recipients in our cohort, 362 underwent LDKT and 502 underwent DDKT. There were a total of 134 ACGL events (40 among LDKT recipients and 94 among DDKT recipients). Median (IQR) recipient age was 53 (42–63) years, median (IQR) BMI was 28.0 (24.0–32.0), median (IQR) time on dialysis before KT was 1.9 (0.2–4.2) years, 39.4% were female, 39.1% were Black, 2.3% were Hispanic, 65.8% were college educated, 46.6% were employed, 50.7% had public insurance, 7.1% were positive for HCV, 17.4% had a history of diabetes, 29.8% had a history of hypertension, 21.4% had a history of previous transplant, and 10.5% had a PRA > 80 at the time of transplant. Median (IQR) donor age was 41 (29–51) years, median (IQR) BMI was 26.9 (23.8–30.6), 50.3% were female, 18.1% were Black, and 4.1% were Hispanic. Deceased KT donors had a median (IQR) KDPI of 43.5 (27.2–64.5) and a median (IQR) CIT of 11.8 (2.0–26.4) hours. There were 5.7% recipient-donor pairs with zero HLA mismatches. Characteristics of the registry study population can be found in supplemental materials (SDC, Materials and Methods, http://links.lww.com/TP/B630).
Prevalence of Cognitive Impairment in Prospective Cohort
Living donor KT recipients in our prospective cohort had a median (IQR) 3MS score of 96 (92–99) and DDKT recipients had a median (IQR) 3MS score of 94 (87–97) (Figure 1). The overall prevalence of cognitive impairment was 10.0% (6.6% in LDKT recipients and 12.4% in DDKT recipients), and the prevalence of severe cognitive impairment was 2.9% (3.3% in LDKT recipients and 2.6% in DDKT recipients). LDKT recipients with cognitive impairment were younger (P = 0.03) and had lower BMI (P < 0.01) than those without cognitive impairment (Table 1). The DDKT recipients with cognitive impairment were more likely to be Black (P = 0.04), older (P = 0.03), and have diabetes (P = 0.04) and less likely to be college educated (P < 0.001) than those without cognitive impairment. DDKT recipients with cognitive impairment received kidneys with a higher median KDPI (P = 0.049) (Table 2).
Post-KT Outcomes, LDKT Recipients
The LDKT recipients with any cognitive impairment had higher unadjusted rates of graft loss compared to those without cognitive impairment (P < 0.01); however, there were no detectable differences by severe cognitive impairment status in LDKT recipients in unadjusted analyses (P = 0.1) (Figure 2). All-cause graft loss for LDKT recipients with any cognitive impairment was 45.5% at 5 years versus 10.6% at 5 years for LDKT recipients without cognitive impairment. All-cause graft loss for LDKT recipients with severe cognitive impairment was 37.5% at 5 years versus 11.6% at 5 years for LDKT recipients without severe cognitive impairment (Table 3). After adjusting for recipient, donor, and transplant factors using Cox regression, any cognitive impairment in LDKT recipients was associated with a 5.40-fold increased risk of ACGL (aHR, 1.785.4016.34, P < 0.01) and severe cognitive impairment was associated with a 5.57-fold increased risk of ACGL (aHR, 1.295.5724.00, P = 0.02). After adjusting for recipient, donor, and transplant factors using hybrid registry-augmented regression (Table S6, SDC, http://links.lww.com/TP/B630), any cognitive impairment in LDKT recipients was associated with a 3.22-fold increased risk of ACGL (aHR, 18.104.22.168; P = 0.02); however, there was no statistically significant difference by severe cognitive impairment (aHR, 0.843.2212.36; P = 0.09) (Table 4). In sensitivity analyses where cognitive impairment was defined based on an external population, the magnitudes of the associations between cognitive impairment and ACGL increased in LDKT recipients, but our inferences were unchanged (Table S3, SDC, http://links.lww.com/TP/B630).
In sensitivity analyses, any cognitive impairment was associated with a 3.01-fold increased risk of mortality among LDKT recipients (aHR, 1.333.016.80; P < 0.01) after adjusting for recipient, donor and transplant factors using hybrid registry augmented regression. We did not detect an association between severe impairment and mortality among LDKT recipients (Table S1, SDC, http://links.lww.com/TP/B630). When cognitive impairment was defined based on an external population of community dwelling older adults, the association between any cognitive impairment and mortality was slightly attenuated (aHR, 1.062.757.11; P = 0.04) (Table S4, SDC, http://links.lww.com/TP/B630). We did not detect an association between cognitive impairment and DCGF among LDKT recipients using hybrid registry augmented regression with either internally or externally defined cognitive impairment (Tables S2, S5, SDC, http://links.lww.com/TP/B630).
Post-KT Outcomes, DDKT Recipients
The DDKT recipients with any cognitive impairment had similar rates of graft loss as individuals without cognitive impairment (P = 0.6); however, DDKT recipients with severe cognitive impairment had higher rates of graft loss, compared with DDKT recipients without severe cognitive impairment (P = 0.046) (Figure 3). All-cause graft loss for DDKT recipients with any cognitive impairment was 26.8% at 5 years versus 24.9% at 5 years for DDKT recipients without cognitive impairment. All-cause graft loss for DDKT recipients with severe cognitive impairment was 53.0% at 5 years versus 24.2% at 5 years for DDKT recipients without severe cognitive impairment (Table 3). After adjusting for recipient, donor, and transplant factors using Cox regression, severe cognitive impairment in DDKT recipients was associated with a 2.92-fold increased risk of ACGL (aHR, 1.132.927.50; P = 0.03); however, there was no statistically significant difference by any cognitive impairment (aHR, 0.581.051.89; P = 0.9). After adjusting for recipient, donor, and transplant factors in DDKT recipients using hybrid registry-augmented regression (Table S7, SDC, http://links.lww.com/TP/B630), severe cognitive impairment in DDKT recipients was associated with a 2.93-fold increased risk of ACGL (aHR, 1.352.936.35; P < 0.01); however, there was no statistically significant difference by any cognitive impairment (aHR, 0.591.041.84; P = 0.9) (Table 4). In sensitivity analyses where cognitive impairment was defined based on an external population, the magnitude of the associations between cognitive impairment and ACGL increased in DDKT recipients, but our inferences were unchanged (Table S3, SDC, http://links.lww.com/TP/B630).
In sensitivity analyses, we did not detect an association between cognitive impairment and mortality or DCGF among DDKT recipients (Tables S1, S2, SDC, http://links.lww.com/TP/B630). However, in sensitivity analyses, where cognitive impairment was defined based on an external population, there was an association between severe cognitive impairment and mortality (aHR, 1.0032.265.09; P = 0.049) (Table S4, SDC, http://links.lww.com/TP/B630). We did not detect an association between cognitive impairment and DCGF using cognitive impairment definitions defined in the external population (Table S5, SDC, http://links.lww.com/TP/B630).
In this prospective, longitudinal 2-center cohort study of 864 KT recipients, we found that pretransplant cognitive impairment was common and was associated with an elevated risk of ACGL (a composite of graft loss and mortality). The prevalence of cognitive impairment in our study population was 10.0%. Any cognitive impairment was associated with a 5.40-fold higher risk of ACGL in LDKT recipients (aHR, 1.785.4016.34). Severe cognitive impairment was associated with a 5.57-fold higher risk of ACGL in LDKT recipients (aHR, 1.295.5724.00) and with a 2.92-fold higher risk of ACGL in DDKT recipients (aHR, 1.132.927.50).
A nationally representative survey in the United States estimated that the prevalence of cognitive impairment was 16% among adults without dementia age 71 to 79 years.39 In our 2-center cohort, the prevalence of cognitive impairment was 22.9% among adults aged 71 to 79 years (N = 61), possibly pointing to the increased risk of cognitive impairment among patients with CKD. Although older age was associated with cognitive impairment in our study, the prevalence of cognitive impairment across the study population (median age, 53 years; IQR, 42–63 years) was noteworthy. Previous studies have identified an association between dialysis initiation and duration with progressively worsening cognitive function15,16,18,40 likely through the buildup of uremic toxins, inflammation, and cerebral hypotension and hypoxia during dialysis sessions.41,42 These mechanisms lead to a higher risk of cognitive impairment in kidney transplant candidates of all ages, as we observed in our study. This underscores the need to consider screening for cognitive impairment in KT candidates, even those who would not otherwise be considered at risk due to age alone.
Our observed association of higher graft loss in kidney transplant recipients with cognitive impairment is consistent with prior studies that have shown cognitive impairment to be associated with inferior medical outcomes. One possible mechanism that might explain their elevated risk of ACGL is poorer medication adherence among recipients with cognitive impairment. Because adherence to the immunosuppressive medication regimen affects the longevity and function of the transplanted allograft, cognitive impairment might indirectly cause inferior posttransplant outcomes. The level of cognitive impairment observed in these studies is severe enough to interfere with adherence to medication and treatment regimens as seen in studies of dialysis patients14 and nontransplant surgical patients.43-45 This potential pathway warrants further study, as it may represent a target for intervention to improve KT outcomes in this vulnerable population.46
A limitation of this study was the relatively small sample size of our 2-center cohort compared to national transplant recipient datasets. To address this limitation, we were able to adjust for important donor, recipient, and transplant characteristics using hybrid registry-augmented regression; however, future multicenter cohort studies will be necessary to improve the generalizability of our findings. Our study used 3MS thresholds based on algorithmically defined cutoffs for cognitive impairment. Given the lack of normative data on 3MS scores in KT candidates, cognitive impairment status might have been misclassified. In sensitivity analyses, we used 3MS thresholds based on an external population with detailed normative data and also stratified by educational attainment and age and found that our inferences did not change (Table S3, SDC, http://links.lww.com/TP/B630). Another notable limitation of this study is that we were only able to identify an association between cognitive impairment and ACGL, not causation. However, we believe that the relationship between cognitive impairment and inferior outcomes is plausible and warrants further study. Although we present results for the association of cognitive impairment and mortality and DCGF (evaluated separately) in the supplemental material, these analyses were likely underpowered based on the sample size and number of events. We were not able to account for social support or other important elements of social context. Strengths of this study include the prospective measurement of global cognitive impairment using a validated instrument (3MS) and reliable ascertainment of posttransplant outcomes using the national registry. Using prospectively collected data, we were also able to adjust for a wider range of comorbidities than is available in the national registry.
In summary, we found that cognitive impairment was common in KT recipients and was associated with an elevated risk of a composite outcome of graft loss and mortality. These findings underscore the importance of elucidating potential mechanisms underlying the relationship between cognitive impairment and inferior posttransplant outcomes, such as medication nonadherence, and emphasize the need for designing interventions to improve outcomes. Transplant centers may consider screening for cognitive impairment to identify higher-risk KT recipients and to inform pretransplant and posttransplant clinical management of these patients. Screening processes might combine a test of global function, like 3MS, with other validated tools specific to the ESRD population, such as the Kidney Disease Quality of Life Cognitive Function scale.47 Further study of the effect of pretransplant interventions to preserve or improve cognitive function, such as cognitive or exercise training, is also warranted.
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