Faculty Bibliography

We recently elucidated risk factors for early hospital readmission (EHR) following kidney transplantation (KT). We now sought to quantify the independent associations between EHR and post-KT outcomes, including late hospital readmission (LHR: 1 year after EHR window), death-censored graft loss and mortality, among Medicare-primary KT recipients (2000-2005). Of 32961 KT recipients, 7.7% had at least one readmission within 3 days of discharge, 14.8% within 7 days, 22.4% within 14 days and 30.5% within 30 days of discharge after the initial KT hospitalization. KT recipients who experienced EHR within 30 days of discharge after the initial KT hospitalization were more likely to have experienced LHR (29.6% vs. 9.0%, p<0.001) and were at 3.02 times higher (95% CI: 2.82-3.23, p<0.001) risk of LHR. Additionally, EHR was associated with death-censored graft loss (deceased donor recipients hazard ratio [HR]: 1.43, 95% CI: 1.36-1.51, p<0.001 and live donor recipients HR: 1.54, 95% CI: 1.40-1.70, p<0.001) and mortality (deceased donor recipients HR: 1.50, 95% CI: 1.43-1.58, p<0.001 and live donor recipients HR: 1.45, 95% CI: 1.32-1.60, p<0.001). Thirty days posttransplant represents a high-risk window for KT recipients and the readmissions during this window are strong predictors of adverse sequelae, particularly LHRs. Efforts should be made to implement and improve systems to reduce LHR and subsequent graft loss and mortality among recipients with EHR.

BACKGROUND:Increased serum urate levels are associated with poor outcomes including but not limited to gout. It is unclear whether serum urate levels are the sole predictor of incident hyperuricemia or whether demographic and clinical risk factors also predict the development of hyperuricemia. The goal of this study was to identify risk factors for incident hyperuricemia over 9 years in a population-based study, ARIC. METHODS:ARIC recruited individuals from 4 US communities; 8,342 participants who had urate levels <7.0 mg/dL were included in this analysis. Risk factors (including baseline, 3-year, and change in urate level over 3 years) for 9-year incident hyperuricemia (urate level of >7.0 g/dL) were identified using an AIC-based selection approach in a modified Poisson regression model. RESULTS:The 9-year cumulative incidence of hyperuricemia was 4%; men = 5%; women = 3%; African Americans = 6% and whites = 3%. The adjusted model included 9 predictors for incident hyperuricemia over 9 years: male sex (RR = 1.73 95% CI: 1.36-2.21), African-American race (RR = 1.79 95% CI: 1.37-2.33), smoking (RR = 1.27, 95% CI: 0.97-1.67), <HS education (RR = 1.27, 95% CI: 0.99-1.63), hypertension (RR = 1.65, 95% CI: 1.30-2.09), CHD (RR = 1.57, 95% CI: 0.99-2.50), obesity (class I RR = 2.37, 95% CI: 1.65-3.41 and ≥ class II RR = 3.47, 95% CI: 2.33-5.18), eGFR < 60 (RR = 2.85, 95% CI: 1.62-5.01) and triglycerides (Quartile 4 vs. Quartile 1: RR = 2.00, 95% CI: 1.38-2.89). In separate models, urate levels at baseline (RR 1 mg/dL increase = 2.33, 95% CI: 1.94-2.80) and 3 years after baseline (RR for a 1 mg/dL increase = 1.92, 95% CI: 1.78-2.07) were associated with incident hyperuricemia after accounting for demographic and clinical risk factors. CONCLUSION/CONCLUSIONS:Demographic and clinical risk factors that are routinely collected as part of regular medical care are jointly associated with the development of hyperuricemia.

BACKGROUND:Patients undergoing hemodialysis are at high risk of falls, with subsequent complications including fractures, loss of independence, hospitalization, and institutionalization. Factors associated with falls are poorly understood in this population. We hypothesized that insights derived from studies of the elderly might apply to adults of all ages undergoing hemodialysis; we focused on frailty, a phenotype of physiological decline strongly associated with falls in the elderly. METHODS:In this prospective, longitudinal study of 95 patients undergoing hemodialysis (1/2009-3/2010), the association of frailty with future falls was explored using adjusted Poisson regression. Frailty was classified using the criteria established by Fried et al., as a combination of five components: shrinking, weakness, exhaustion, low activity, and slowed walking speed. RESULTS:Over a median 6.7-month period of longitudinal follow-up, 28.3% of study participants (25.9% of those under 65, 29.3% of those 65 and older) experienced a fall. After adjusting for age, sex, race, comorbidity, disability, number of medications, marital status, and education, frailty independently predicted a 3.09-fold (95% CI: 1.38-6.90, P=0.006) higher number of falls. This relationship between frailty and falls did not differ for younger and older adults (P=0.57). CONCLUSIONS:Frailty, a validated construct in the elderly, was a strong and independent predictor of falls in adults undergoing hemodialysis, regardless of age. Our results may aid in identifying frail hemodialysis patients who could be targeted for multidimensional fall prevention strategies.

Early hospital readmission (EHR) after kidney transplantation (KT) is associated with increased morbidity and higher costs. Registry-based recipient, transplant and center-level predictors of EHR are limited, and novel predictors are needed. We hypothesized that frailty, a measure of physiologic reserve initially described and validated in geriatrics and recently associated with early KT outcomes, might serve as a novel, independent predictor of EHR in KT recipients of all ages. We measured frailty in 383 KT recipients at Johns Hopkins Hospital. EHR was ascertained from medical records as ≥1 hospitalization within 30 days of initial post-KT discharge. Frail KT recipients were much more likely to experience EHR (45.8% vs. 28.0%, p = 0.005), regardless of age. After adjusting for previously described registry-based risk factors, frailty independently predicted 61% higher risk of EHR (adjusted RR = 1.61, 95% CI: 1.18-2.19, p = 0.002). In addition, frailty improved EHR risk prediction by improving the area under the receiver operating characteristic curve (p = 0.01) as well as the net reclassification index (p = 0.04). Identifying frail KT recipients for targeted outpatient monitoring and intervention may reduce EHR rates.

OBJECTIVES/OBJECTIVE:To quantify the prevalence of frailty in adults of all ages undergoing chronic hemodialysis, its relationship to comorbidity and disability, and its association with adverse outcomes of mortality and hospitalization. DESIGN/METHODS:Prospective cohort study. SETTING/METHODS:Single hemodialysis center in Baltimore, Maryland. PARTICIPANTS/METHODS:One hundred forty-six individuals undergoing hemodialysis enrolled between January 2009 and March 2010 and followed through August 2012. MEASUREMENTS/METHODS:Frailty, comorbidity, and disability on enrollment in the study and subsequent mortality and hospitalizations. RESULTS:At enrollment, 50.0% of older (≥ 65) and 35.4% of younger (<65) individuals undergoing hemodialysis were frail; 35.9% and 29.3%, respectively, were intermediately frail. Three-year mortality was 16.2% for nonfrail, 34.4% for intermediately frail, and 40.2% for frail participants. Intermediate frailty and frailty were associated with a 2.7 times (95% confidence interval (CI) = 1.02-7.07, P = .046) and 2.6 times (95% CI = 1.04-6.49, P = .04) greater risk of death independent of age, sex, comorbidity, and disability. In the year after enrollment, median number of hospitalizations was 1 (interquartile range 0-3). The proportion with two or more hospitalizations was 28.2% for nonfrail, 25.5% for intermediately frail, and 42.6% for frail participants. Although intermediate frailty was not associated with number of hospitalizations (relative risk = 0.76, 95% CI = 0.49-1.16, P = .21), frailty was associated with 1.4 times (95% CI = 1.00-2.03, P = .049) more hospitalizations independent of age, sex, comorbidity, and disability. The association between frailty and mortality (interaction P = .64) and hospitalizations (P = .14) did not differ between older and younger participants. CONCLUSIONS:Adults of all ages undergoing hemodialysis have a high prevalence of frailty, more than five times as high as community-dwelling older adults. In this population, regardless of age, frailty is a strong, independent predictor of mortality and number of hospitalizations.

OBJECTIVE:To test for a urate gene-by-diuretic interaction on incident gout. METHODS:The Atherosclerosis Risk in Communities Study is a prospective population-based cohort of 15 792 participants recruited from four US communities (1987-1989). Participants with hypertension and available single nucleotide polymorphism (SNP) genotype data were included. A genetic urate score (GUS) was created from common urate-associated SNPs for eight genes. Gout incidence was self-reported. Using logistic regression, the authors estimated the adjusted OR of incident gout by diuretic use, stratified by GUS median. RESULTS:Of 3524 participants with hypertension, 33% used a diuretic and 3.1% developed gout. The highest 9-year cumulative incidence of gout was in those with GUS above the median and taking a thiazide or loop diuretic (6.3%). Compared with no thiazide or loop diuretic use, their use was associated with an OR of 0.40 (95% CI 0.14 to 1.15) among those with a GUS below the median and 2.13 (95% CI 1.23 to 3.67) for those with GUS above the median; interaction p=0.006. When investigating the genes separately, SLC22A11 and SLC2A9 showed a significant interaction, consistent with the former encoding an organic anion/dicarboxylate exchanger, which mediates diuretic transport in the kidney. CONCLUSIONS:Participants who were genetically predisposed to hyperuricaemia were susceptible to developing gout when taking thiazide or loop diuretics, an effect not evident among those without a genetic predisposition. These findings argue for a potential benefit of genotyping individuals with hypertension to assess gout risk, relative in part to diuretic use.

Early hospital readmission (EHR) is associated with increased morbidity, costs and transition-of-care errors. We sought to quantify rates of and risk factors for EHR after kidney transplantation (KT). We studied 32 961 Medicare primary KT recipients (2000-2005) linked to Medicare claims through the United States Renal Data System. EHR was defined as at least one hospitalization within 30 days of initial discharge after KT. The association between EHR and recipient and transplant factors was explored using Poisson regression; hierarchical modeling was used to account for study center-level differences. The overall EHR rate was 31%, and 19 independent patient-level factors associated with EHR were identified: recipient factors included older age, African American race and various comorbidities; transplant factors included ECD, length of stay and lack of induction therapy. The unadjusted rate of EHR by center ranged from 18% to 47%, but conventional center-level factors (percent African American, percent age > 60, percent deceased donor and percent expanded criteria donor) were not associated with EHR. However, intermediate total volume and average length of stay were associated with increased EHR risk. Better identification of patients at risk for early hospital readmission following KT may guide discharge planning and early posttransplant outpatient monitoring.