Racial Equity in Living Donor Kidney Transplant Centers, 2008-2018.

Importance: It is unclear whether center-level factors are associated with racial equity in living donor kidney transplant (LDKT). Objective: To evaluate center-level factors and racial equity in LDKT during an 11-year time period. Design, Setting, and Participants: A retrospective cohort longitudinal study was completed in February 2023, of US transplant centers with at least 12 annual LDKTs from January 1, 2008, to December 31, 2018, identified in the Health Resources Services Administration database and linked to the US Renal Data System and the Scientific Registry of Transplant Recipients. Main Outcomes and Measures: Observed and model-based estimated Black-White mean LDKT rate ratios (RRs), where an RR of 1 indicates racial equity and values less than 1 indicate a lower rate of LDKT of Black patients compared with White patients. Estimated yearly best-case center-specific LDKT RRs between Black and White individuals, where modifiable center characteristics were set to values that would facilitate access to LDKT. Results: The final cohorts of patients included 394 625 waitlisted adults, of whom 33.1% were Black and 66.9% were White, and 57 222 adult LDKT recipients, of whom 14.1% were Black and 85.9% were White. Among 89 transplant centers, estimated yearly center-level RRs between Black and White individuals accounting for center and population characteristics ranged from 0.0557 in 2008 to 0.771 in 2018. The yearly median RRs ranged from 0.216 in 2016 to 0.285 in 2010. Model-based estimations for the hypothetical best-case scenario resulted in little change in the minimum RR (from 0.0557 to 0.0549), but a greater positive shift in the maximum RR from 0.771 to 0.895. Relative to the observed 582 LDKT in Black patients and 3837 in White patients, the 2018 hypothetical model estimated an increase of 423 (a 72.7% increase) LDKTs for Black patients and of 1838 (a 47.9% increase) LDKTs for White patients. Conclusions and Relevance: In this cohort study of patients with kidney failure, no substantial improvement occurred over time either in the observed or the covariate-adjusted estimated RRs. Under the best-case hypothetical estimations, modifying centers' participation in the paired exchange and voucher programs and increased access to public insurance may contribute to improved racial equity in LDKT. Additional work is needed to identify center-level and program-specific strategies to improve racial equity in access to LDKT.

Residential Structural Racism and Prevalence of Chronic Health Conditions.

Importance: Studies elucidating determinants of residential neighborhood-level health inequities are needed. Objective: To quantify associations of structural racism indicators with neighborhood prevalence of chronic kidney disease (CKD), diabetes, and hypertension. Design, Setting, and Participants: This cross-sectional study used public data (2012-2018) and deidentified electronic health records (2017-2018) to describe the burden of structural racism and the prevalence of CKD, diabetes, and hypertension in 150 residential neighborhoods in Durham County, North Carolina, from US census block groups and quantified their associations using bayesian models accounting for spatial correlations and residents' age. Data were analyzed from January 2021 to May 2023. Exposures: Global (neighborhood percentage of White residents, economic-racial segregation, and area deprivation) and discrete (neighborhood child care centers, bus stops, tree cover, reported violent crime, impervious areas, evictions, election participation, income, poverty, education, unemployment, health insurance coverage, and police shootings) indicators of structural racism. Main Outcomes and Measures: Outcomes of interest were neighborhood prevalence of CKD, diabetes, and hypertension. Results: A total of 150 neighborhoods with a median (IQR) of 1708 (1109-2489) residents; median (IQR) of 2% (0%-6%) Asian residents, 30% (16%-56%) Black residents, 10% (4%-20%) Hispanic or Latino residents, 0% (0%-1%) Indigenous residents, and 44% (18%-70%) White residents; and median (IQR) residential income of $54 531 ($37 729.25-$78 895.25) were included in analyses. In models evaluating global indicators, greater burden of structural racism was associated with greater prevalence of CKD, diabetes, and hypertension (eg, per 1-SD decrease in neighborhood White population percentage: CKD prevalence ratio [PR], 1.27; 95% highest density interval [HDI], 1.18-1.35; diabetes PR, 1.43; 95% HDI, 1.37-1.52; hypertension PR, 1.19; 95% HDI, 1.14-1.25). Similarly in models evaluating discrete indicators, greater burden of structural racism was associated with greater neighborhood prevalence of CKD, diabetes, and hypertension (eg, per 1-SD increase in reported violent crime: CKD PR, 1.15; 95% HDI, 1.07-1.23; diabetes PR, 1.20; 95% HDI, 1.13-1.28; hypertension PR, 1.08; 95% HDI, 1.02-1.14). Conclusions and Relevance: This cross-sectional study found several global and discrete structural racism indicators associated with increased prevalence of health conditions in residential neighborhoods. Although inferences from this cross-sectional and ecological study warrant caution, they may help guide the development of future community health interventions.

A comparison of deprivation indices and application to transplant populations.

The choice of deprivation index can influence conclusions drawn regarding the extent of deprivation within a community and the identification of the most deprived communities in the United States. This study aimed to determine the degree of correlation among deprivation indices commonly used to characterize transplant populations. We used a retrospective cohort consisting of adults listed for liver or kidney transplants between 2008 and 2018 to compare 4 deprivation indices: neighborhood deprivation index, social deprivation index (SDI), area deprivation index, and social vulnerability index. Pairwise correlation between deprivation indices by transplant referral regions was measured using Spearman correlations of population-weighted medians and upper quartiles. In total, 52 individual variables were used among the 4 deprivation indices with 25% overlap. For both organs, the correlation between the population-weighted 75th percentile of the deprivation indices by transplant referral region was highest between SDI and social vulnerability index (liver and kidney, 0.93) and lowest between area deprivation index and SDI (liver, 0.19 and kidney, 0.15). The choice of deprivation index affects the applicability of research findings across studies examining the relationship between social risk and clinical outcomes. Appropriate application of these measures to transplant populations requires careful index selection based on the intended use and included variable relevance.

Geospatial Analysis of Organ Transplant Referral Regions.

Importance: System and center-level interventions to improve health equity in organ transplantation benefit from robust characterization of the referral population served by each transplant center. Transplant referral regions (TRRs) define geographic catchment areas for transplant centers in the US, but accurately characterizing the demographics of populations within TRRs using US Census data poses a challenge. Objective: To compare 2 methods of linking US Census data with TRRs-a geospatial intersection method and a zip code cross-reference method. Design, Setting, and Participants: This cohort study compared spatial congruence of spatial intersection and zip code cross-reference methods of characterizing TRRs at the census block level. Data included adults aged 18 years and older on the waiting list for kidney transplant from 2008 through 2018. Exposures: End-stage kidney disease. Main Outcomes and Measures: Multiple assignments, where a census tract or block group crossed the boundary between 2 hospital referral regions and was assigned to multiple different TRRs; misassigned area, the portion of census tracts or block groups assigned to a TRR using either method but fall outside of the TRR boundary. Results: In total, 102 TRRs were defined for 238 transplant centers. The zip code cross-reference method resulted in 4627 multiple-assigned census block groups (representing 18% of US land area assigned to TRRs), while the spatial intersection method eliminated this problem. Furthermore, the spatial method resulted in a mean and median reduction in misassigned area of 65% and 83% across all TRRs, respectively, compared with the zip code cross-reference method. Conclusions and Relevance: In this study, characterizing populations within TRRs with census block groups provided high spatial resolution, complete coverage of the country, and balanced population counts. A spatial intersection approach avoided errors due to duplicative and incorrect assignments, and allowed more detailed and accurate characterization of the sociodemographics of populations within TRRs; this approach can enrich transplant center knowledge of local referral populations, assist researchers in understanding how social determinants of health may factor into access to transplant, and inform interventions to improve heath equity.

Concordance of Preoperative 3D Templating in Stemless Anatomic Total Shoulder Arthroplasty.

INTRODUCTION: Recent advances in preoperative 3D templating software allow surgeons to plan implant size and position for stemless total shoulder arthroplasty (TSA). Whether these preoperative plans accurately reflect intraoperative decisions is yet unknown, and the purpose of this study was to evaluate concordance between planned and actual implant sizes in a series of patients undergoing stemless TSA. METHODS: A retrospective cohort of consecutive, anatomic, stemless TSA cases performed by two surgeons between September 2019 and February 2021 was examined. Preoperative templated plans were collected using 3D planning software, and the sizes of planned glenoid, humeral head, and nucleus "stem" implants and other procedural data were recorded, along with sociodemographic information. These predicted parameters were compared with the implant sizes, and the concordance of these templated plans was quantified by direct comparison and bootstrapped simulations. RESULTS: Fifty cases met inclusion criteria, among which perfect concordance across all three implants was observed in 11 cases (22%). The glenoid implant had the highest concordance (80%) relative to the humeral head and nucleus implants (38% and 60%, respectively), which was statistically significant ( P < 0.001). Planned humeral head implants were more often oversized relative to their actual implanted size. However, 84% of the planned humeral heads were within 1 diameter size; in addition, 98% of the planned glenoid implants were within one size and all were within 10 mm of the implanted glenoid backside radius. All nucleus implants were within one size. DISCUSSION: Final implant sizes demonstrated variable concordance relative to preoperative plans, with glenoid implants having the highest accuracy and humeral heads having the highest variability. Multiple factors contributed to the varying concordances for the different implants, suggesting possible areas of improvement in this technology. These results may have implications for logistics, intraoperative efficiency, and overall cost and underscore the potential value of this technology. LEVEL OF EVIDENCE: Level III.

Co-occurring Fungal Functional Groups Respond Differently to Tree Neighborhoods and Soil Properties Across Three Tropical Rainforests in Panama.

Abiotic and biotic drivers of co-occurring fungal functional guilds across regional-scale environmental gradients remain poorly understood. We characterized fungal communities using Illumina sequencing from soil cores collected across three Neotropical rainforests in Panama that vary in soil properties and plant community composition. We classified each fungal OTU into different functional guilds, namely plant pathogens, saprotrophs, arbuscular mycorrhizal (AM), or ectomycorrhizal (ECM). We measured soil properties and nutrients within each core and determined the tree community composition and richness around each sampling core. Canonical correspondence analyses showed that soil pH and moisture were shared potential drivers of fungal communities for all guilds. However, partial the Mantel tests showed different strength of responses of fungal guilds to composition of trees and soils. Plant pathogens and saprotrophs were more strongly correlated with soil properties than with tree composition; ECM fungi showed a stronger correlation with tree composition than with soil properties; and AM fungi were correlated with soil properties, but not with trees. In conclusion, we show that co-occurring fungal guilds respond differently to abiotic and biotic environmental factors, depending on their ecological function. This highlights the joint role that abiotic and biotic factors play in determining composition of fungal communities, including those associated with plant hosts.