Abstract Recent Findings Black and Hispanic patients carry higher burden of kidney disease, yet have lower access to LDKT. Until recently, these differences were thought to be due to medical co-morbidities and variation in transplant center practices. However, recent studies have shown that systemic and structural inequities related to race may be one of the major drivers. Purpose of Review In this paper, we examine the definition of race and systemic racism, then describe patient-, transplant center–, and society-level barriers to LDKT. We identify how social determinants, cultural biases and mistrust in medical system, influence behaviors, and provider racial profiling affects all phases of transplant evaluation. Finally, we discuss initiatives to overcome some of these barriers, starting from federal government, national organizations, transplant centers, and community partners. Summary Examining structural biases in transplant practices is an important step to developing solutions to address disparities in health care access and outcomes for patients who need and receive transplants.
There are no established regulations governing patient selection for simultaneous heart-kidney (SHK) transplantation, creating the potential for significant center-level variations in clinical practice.Using the United Network for Organ Sharing (UNOS) Standard Transplant Analysis and Research (STAR) file, we examined practice trends and variations in patient selection for SHK at the center level between January 1, 2004 and March 31, 2019.Overall, SHK is becoming more common with most centers performing heart transplants also performing SHK. Among patients who underwent heart transplant who were receiving dialysis, the rate of SHK varied from 22% to 86% at the center level. Among patients not on dialysis, the median estimated glomerular filtration rate (eGFR) of patients receiving SHK varied between 19 and 59 mL/min/1.73 m2 . When adjusting for other factors, the odds of SHK varied 57-fold between the highest and lowest SHK performing centers.Variation in SHK at the center level suggests the need for national guidelines around the selection of patients for SHK.
Key Points Incidence of ESKD in the first year after primary organ transplant ranges from 2.4% to 3.6% and from 1.4% to 1.8% in the second year post-transplant. National data sources do not currently collect sufficiently reliable follow-up data to identify pretransplant predictors of ESKD. Background Careful selection of multiorgan transplant candidates is required to avoid unintended consequences to patients waiting for kidney transplant alone. The need for a safety net among heart and lung transplant recipients is unknown. The objective of this study was to quantify the incidence of kidney failure after liver, heart, or lung transplantation and identify pretransplant predictors of post-transplant kidney failure. Methods A retrospective cross-sectional study of adults who received liver, heart, or lung transplant between January 1, 2008, and December 31, 2018, was conducted using data from the Scientific Registry of Transplant Recipient and the United States Renal Data System. Post-transplant renal failure was defined as ( 1 ) new start of dialysis, ( 2 ) eGFR of <25 ml/min, ( 3 ) a new waitlisting for a kidney transplant, or ( 4 ) receipt of a kidney transplant. Results The final descriptive cohort included 53,620 liver transplant recipients, 22,042 heart transplant recipients, and 10,688 lung transplant recipients. In the first year post-transplant, the probability of ESKD was comparable among heart transplant recipients (0.036; 95% confidence interval [CI], 0.033 to 0.038) and liver transplant recipients (0.033; 95% CI, 0.031 to 0.035) but was markedly lower in lung transplant recipients (0.024; 95% CI, 0.021 to 0.027). In the second year post-transplant, the probability of ESKD was comparable among liver (0.016; 95% CI, 0.015 to 0.017), lung (0.018; 95% CI, 0.015 to 0.021), and heart transplant recipients (0.014; 95% CI, 0.013 to 0.016). Conclusions Candidates for thoracic transplant would likely benefit from a safety net policy similar to the one enacted in 2017 for liver transplant so as to maintain judicious patient selection for simultaneous multiorgan transplant. National data sources do not currently collect sufficiently reliable follow-up data to identify pretransplant predictors of ESKD, pointing to a need for transplant centers to consistently report kidney impairment data to national databases.
The impact of pre-donation obesity on long-term outcomes of living kidney donors remains controversial. Published guidelines offer varying recommendations regarding BMI (kg/m2) thresholds for donor acceptance. We examined temporal and center-level variation in BMI of accepted donors across US transplant centers. Using national transplant registry data, we performed multivariate hierarchical logistic regression modeling using pairwise comparisons (overweight, BMI: 25-29.9; mildly obese, BMI: 30-34.9; very obese, BMI: ≥35; versus normal BMI: 18.5-24.9). Metrics of heterogeneity, including median odds ratio (MOR), were calculated. Among 90 013 living kidney donors, 2001-2016, proportions who were very obese decreased and proportions who were mildly obese or overweight increased. Significant center-level heterogeneity was noted in BMI of accepted donors; the MOR varied from 1.10 for overweight to 1.93 for very obese donors. At centers located in the 10 states with the highest general population obesity rates, adjusted odds of very obese donor status were 185% higher (reference: normal BMI) than in states with the lowest obesity rates. Although there is a declining trend in acceptance of very obese living kidney donors, variation across centers is significant. Furthermore, local population obesity rates may affect the decision to accept obese individuals as donors. The impact of pre-donation obesity on long-term outcomes of living kidney donors remains controversial. Published guidelines offer varying recommendations regarding BMI (kg/m2) thresholds for donor acceptance. We examined temporal and center-level variation in BMI of accepted donors across US transplant centers. Using national transplant registry data, we performed multivariate hierarchical logistic regression modeling using pairwise comparisons (overweight, BMI: 25-29.9; mildly obese, BMI: 30-34.9; very obese, BMI: ≥35; versus normal BMI: 18.5-24.9). Metrics of heterogeneity, including median odds ratio (MOR), were calculated. Among 90 013 living kidney donors, 2001-2016, proportions who were very obese decreased and proportions who were mildly obese or overweight increased. Significant center-level heterogeneity was noted in BMI of accepted donors; the MOR varied from 1.10 for overweight to 1.93 for very obese donors. At centers located in the 10 states with the highest general population obesity rates, adjusted odds of very obese donor status were 185% higher (reference: normal BMI) than in states with the lowest obesity rates. Although there is a declining trend in acceptance of very obese living kidney donors, variation across centers is significant. Furthermore, local population obesity rates may affect the decision to accept obese individuals as donors.
Hospital-acquired infections add considerable morbidity and mortality to patient care. However, a detailed economic analysis of these infections on an individual case basis has been lacking. The authors examined both the hospital revenues and expenses in 54 cases of patients with central line-associated bloodstream infections (CLABs) over 3 years in 2 intensive care units and compared these financial data with patients who were matched for age, severity of illness on admission, and principal diagnosis. The average payment for a case complicated by CLAB was $64 894, and the average expense was $91733 with gross margin of -$26 839 per case and a total loss from operations of $1 449 306 in the 54 cases. The costs of CLABs and the associated complications averaged 43% of the total cost of care. The elimination of these preventable infections constitutes not only an opportunity to improve patient outcomes but also a significant financial opportunity.
Objective: To observe the prevalence and distribution of ideal cardiovascular health metrics in middle-aged men living in Su-Xi-Chang region and explore the relationship between health behavior and health factors. Methods: A total of 27 824 middle-aged men, who took part in health examination in the Center for Healthcare Management, Taihu Rehabilitation Hospital of Jiangsu Province from January 2014 to June 2015, were enrolled in this cross-sectional study. The ideal cardiovascular health metrics were defined by the American Heart Association criteria with minor modification in that the amount of vegetable intake was replaced by salt intake. The prevalence and distribution of ideal cardiovascular health metrics as well as the association between ideal cardiovascular health metrics and health factors were analyzed in this cohort. Results: The body mass index in the whole cohort was (25.1±3.0) kg/m2, waist circumference was (87.3±8.42) cm; the percent of subjects with all seven ideal cardiovascular health metrics was only 0.5% (n=133). The highest proportion of ideal metric was total cholesterol (68.5%, n=19 056), followed by fasting glucose (66.9%, n=18 616), body mass index (50.2%, n=13 963), physical exercise (45.6%, n=12 697), smoking (40.3%, n=11 216), blood pressure (22.5%, n=6 257) and salt intake (15.6%, n=4 351). The proportion of ideal cardiovascular health metrics reduced gradually and the proportion of poor cardiovascular health metrics status increased gradually with aging(χ2=106.746, P=0.000). The total cholesterol level of non-smokers was significantly lower than that of smokers(F=8.571, P=0.000); total cholesterol, blood pressure and fasting glucose levels increased in proportion with increasing body mass index(all P<0.01); total cholesterol and fasting blood glucose of subjects with regular active physical exercise were significantly lower than those with inactive physical exercise(all P<0.01); total cholesterol and blood pressure of subjects with high salt intake were significantly higher than those with low salt intake(all P<0.01). Conclusions: The proportion of subjects with ideal cardiovascular health metrics is very low in middle-aged men living in Su-Xi-Chang region, and the downtrend with poor cardiovascular health metrics increases with aging. Overweight or obese, smoking, high salt diet and poor control of blood pressure are the major cardiovascular risk factors in this cohort.
