Citations

Background Mortality in adults with congenital heart disease (CHD) is strongly driven by disease complexity. Social determinants of health (SDOH) influence adult CHD (ACHD) health outcomes but their impact on mortality is unclear. This study examined the influence of clinical factors and SDOH on all‐cause mortality in patients with ACHD. Methods Single‐center retrospective cohort study of patients with ACHD in the Mayo ACHD Registry who had a verifiable residential address between January 1, 2004 and December 31, 2023. Clinical and SDOH indicators were extracted, including insurance type, language, rural–urban commuting area code, and a housing‐based socioeconomic index, an individual‐level measure of socioeconomic status derived from 4 objective housing characteristics and categorized into quartiles (Q1–Q4). Cox proportional‐hazards models were fitted to evaluate associations with mortality, incorporating CHD severity, arrhythmias, SDOH indicators, and other comorbidities. County of residence was included as a random effect, and model discrimination was assessed using the concordance statistic. Results Among 6134 patients with ACHD, the mean age was 38±16 years; 51% were male; 78.7% were White and 44.9% had rural residence. Independent predictors of mortality included cyanotic CHD (adjusted hazard ratio [aHR], 5.70 [95% CI, 2.90–11.23]), Fontan palliation (aHR, 4.98 [95% CI, 2.56–9.70]), ventricular tachycardia (aHR, 1.71 [95% CI, 1.16–2.52]), older age at first visit (aHR, 1.05 per year [95% CI, 1.04–1.05]), male sex (aHR, 1.19 [95% CI, 1.03–1.39]), public insurance (aHR, 1.60 [95% CI, 1.35–1.90]), rural residence (aHR, 1.25 [95%, CI 1.06–1.47]), and non‐English language (aHR 1.75 [95% CI 1.38–2.23]). The housing‐based socioeconomic index quartile was not associated with mortality. The final model achieved a concordance statistic of 0.77. Conclusions Mortality in patients with ACHD is strongly influenced by both clinical factors and SDOH, independent of socioeconomic status. Addressing barriers to care such as language, insurance, and geography is essential for improving ACHD survival particularly in those at increased mortality risk.

Abstract Models that estimate the probability of an adverse clinical outcome require an operational cutoff to translate continuous estimated probabilities into discrete labels that can trigger clinical action. Although statistical methods identify ‘optimal’ cut-offs, threshold selection ultimately reflects value judgments regarding harm tolerance, resource allocation, and workflow feasibility. We describe a governance-informed approach to selecting a deployment threshold for an asthma exacerbation (AE) prediction model integrated into clinical workflows. Using prevalence-adjusted performance metrics and real-world provider capacity modeling, we evaluated multiple candidate thresholds and quantified downstream workload and missed-event trade-offs. We demonstrate that statistically optimal thresholds may produce operationally infeasible alert volumes or unacceptable miss rates. We propose a structured threshold governance framework integrating statistical performance, clinical utility, stakeholder input, and human oversight safeguards. This case illustrates how threshold decisions should be treated as organizational governance processes rather than purely technical optimizations.

Asthma is a heterogeneous chronic respiratory disease driven by diverse inflammatory pathways that vary across patients. The recognition of distinct molecular endotypes has led to the development of targeted biologic therapies that have transformed the management of moderate-to-severe asthma. However, selecting the most appropriate biologic therapy for each patient remains challenging. Health providers often rely on trial-and-error approaches that may delay disease control, increase costs, and expose patients to unnecessary side effects. Biomarkers are key to precision asthma care, as they provide objective measures of underlying disease mechanisms. Established biomarkers such as blood eosinophil count, fractional exhaled nitric oxide, and serum total immunoglobulin E are important for identifying type 2-high asthma. Sputum biomarkers offer direct insight into airway inflammation, but their use is limited by technical complexity and availability across centers. Emerging biomarkers, including proteomic, transcriptomic, metabolomic, and genomic biomarkers, show promise in further refining biologic therapy selection. In addition, digital biomarkers derived from electronic health records, wearable devices, and artificial intelligence-based algorithms offer new opportunities to capture real-world changes in disease and treatment response. Non-medical drivers of health, particularly socioeconomic factors, are increasingly recognized as modifiers of biologic effectiveness and may also be helpful in selecting biologic therapies. This review summarizes the existing evidence on established and emerging biomarkers used to guide biologic therapy selection in asthma. Integrating multiple biomarkers will be essential to improve biological selection, monitor response, and ultimately achieve the goal of remission in asthma.

Key Points Pediatric preemptive kidney transplantation rates in the United States vary by socioeconomic status (SES). The HOUsing-based index of SES, an individual-level SES measure derived from residential addresses, effectively predicts pediatric preemptive kidney transplant rates. Background Preemptive kidney transplantation in children is associated with better patient and graft survival compared with transplants after dialysis. However, preemptive kidney transplantation rates in children remain low. This study aimed to evaluate the effect of socioeconomic status (SES) on preemptive transplantation in children. Methods Our study included 173 Minnesota-resident pediatric kidney transplant recipients (younger than 18 years) transplanted at the University of Minnesota from 2010 to 2020. Using the HOUsing-based index of SES (HOUSES) index, a validated, individual SES measure based on housing units categorized into quartiles (Q1: lower SES; Q2–Q4: higher SES), we applied mixed-effects multivariable logistic models to examine the effects of HOUSES on preemptive kidney transplants and pretransplant dialysis duration. Results Of 173 pediatric kidney transplant recipients, 46 (26.6%) received a preemptive transplant, and of 109 recipients with dialysis duration data, 39 (35.8%) received dialysis for >1 year. After adjusting for age at kidney failure, sex, donor type, insurance type, and underlying cause of kidney failure, we observed significantly lower odds of preemptive transplantation among Q1 recipients compared with Q2–4 recipients (adjusted odds ratio, 0.31; 95% confidence interval, 0.11 to 0.90; P = 0.03). Conclusions Using the HOUSES index, we found significant socioeconomic disparities in preemptive kidney transplantation rates among children.

Abstract Background/Objective: Decentralized research has many advantages; however, little is known about the representativeness of a source population in decentralized studies. We recruited participants aged 18-64 years from four states from June to December 2022 for a prospective cohort study to assess viral epidemiology. Our aim was to determine the association between age, gender, race/ethnicity, rurality, and socioeconomic status (SES) on study participation in a decentralized prospective cohort study. Methods: We consented 9,286 participants from 231,099 (4.0%) adults with the mean age of 45.6 years (±12.0). We used an electronic decentralized approach for recruitment. Consented participants were more likely to be non-Hispanic White, female, older, urban residents, have more health conditions, and possessed higher socioeconomic status (SES) compared to those non-consented. Results: We observed an interaction between SES and race-ethnicity on the odds of consent (P = 0.006). Specifically, SES did not affect non-Hispanic white participation rates(OR 1.24 95% CI 1.16 – 1.32] for the highest SES quartile compared to those with the lowest SES quartile) as much as it did participants combined across the other races (OR 1.73; 95% CI 1.45 – 2.98]) Conclusion: The relationship between SES and consent rates might be disproportionately greater in historically disadvantaged groups, compared to non-Hispanic White. It suggests that instead of focusing on enrollment of specific minority groups in research, there is value in future research exploring and addressing the diversity of barriers to trials within minority groups. Our study highlights that decentralized studies need to address social determinants of health, especially in under-resourced populations.

Objectives/Goals: This proposal outlines the successful deployment of a research training initiative to support the formation of a Learning Healthcare System. Mayo Clinic Health System (MCHS) rural providers were offered the opportunity to the fundamentals of clinical research via Clinical and Translational Science Awards core curriculum, mentorship, and an online seminar series. Methods/Study Population: MCHS funded 4 key introductory research courses: 1) Manuscript Writing, 2) Grant Writing, 3) Basic Biostatistics, and 4) Essentials of Clinical and Translations Science Program. In addition to course offerings, a Research Interest Group was formed to guide novice rural researchers on topic selection and study design. This cultivated interest to create a 16-month clinical research webinar series offering CME credits. Subsequently, an internal MCHS RFA was launched seeking early-stage investigator pilot proposals focused on rural health. Results/Anticipated Results: In 2023, over 140 MCHS providers enrolled in 324 CCaTS research courses. This training led to the submission of 53 proposals to the inaugural MCHS 2023 RFA, of which 15 were awarded. Additionally, 14 MCHS extramural grants were submitted in 2023. Training efforts expanded in 2024 to include an online research seminar series covering various study topics and providing CME credit, with an approximate attendance up to 196 attendees per session. The second annual MCHS RFA resulted in 4 internal awards, with an additional 22 extramural grant submissions. These collective efforts have increased the number of MCHS first and last author publications and the number of MCHS providers with academic rank. Discussion/Significance of Impact: Leadership’s commitment of resources to educate, mentor, and engage clinicians was crucial to our success and demonstrated a strong return on investment. To maximize impact in community-based practice, continued commitment is needed in the form of protected research time, funding, and research administration support of projects of interest

Objectives/Goals: Community-based practices have limited research opportunities for providers. As a rural community-based health system, Mayo Clinic Health System (MCHS) sought to create intramural funding mechanisms to help early-stage researchers conduct pilot research so they are more competitive to compete for more robust extramural funding opportunities. Methods/Study Population: We created a Research Seed Grant Program infrastructure across our four MCHS regions (Southwest and Southeast Minnesota, Northwest and Southwest Wisconsin). This model program featured an initial research funding announcement call based on 6 prioritized programs (AI Validation & Stewardship, Cancer, Health Equity, Population Health, Rural Health, Learning Healthcare System [LHS]), with submissions uploaded to a central electronic repository. Proposal review and ranking was organized on a regional basis, with ranking of all proposals by at least 2 clinical scientist reviewers according to the NIH domain-specific framework (i.e., 1.0 best > 9.0 worst). Awards were competitively selected by conformity to prioritized research areas and through ranking of most competitive overall application scores. Results/Anticipated Results: For our inaugural RFA, we received 55 grant application submissions across the MCHS regions. Fifteen of the most highly ranked applications were selected for awards on a per region basis, providing direct funding as well as protected investigator research time of 10% for up to six months. The selected projects address several research priorities including improving access, reducing health disparities, improving behavioral health in our communities, increasing cancer screening and prevention, and community-based pragmatic trials and interventions. Outcomes from these now completed pilot projects remain pending at this time. Funding for this seed grant program was supported by philanthropy, Mayo Clinic Research Administration, Mayo Clinic Comprehensive Cancer Center, and the Mayo Clinic CCaTS Rural Core. Discussion/Significance of Impact: We present this framework for a LHS-focused Seed Grant program model for consideration of adoption by other national/international LHS. Future plans include tracking of outcome metrics (e.g., published peer review articles, extramural grant applications) of this initial cycle and future expansion of this program to support the goals of our LHS.

Background. The limitations of conventional measures of socioeconomic status (SES) limit our ability to elucidate the role of SES as a key element of social determinants of health in kidney transplantation. This study’s objective was to use an innovative SES measure, the HOUsing-based SES measure (HOUSES) index, to examine the effects of social determinants of health on access to and outcomes of kidney transplantation. Methods. Our study included residents of Minnesota (age older than 18 y) who underwent kidney transplantation at a single center between 2010 and 2020. SES was determined using the HOUSES index, categorized into quartiles (Q1 for lower, Q2–Q4 for higher SES). We used mixed-effects multivariable logistic and Cox models to examine the effects of HOUSES on preemptive transplants, pretransplant dialysis duration, and death-censored graft loss, adjusting for covariates. Results. Among 1975 eligible patients, 29.4% received preemptive transplants, 34.9% underwent pretransplant dialysis for >3 y, and 15.1% experienced death-censored graft loss for a median follow-up of 7.15 (interquartile range, 4.25–11.38) y. Lower SES recipients (Q1) demonstrated decreased preemptive transplant likelihood (adjusted odds ratio [aOR]: 0.74; 95% confidence interval [CI], 0.57-0.97; P = 0.03), longer dialysis duration (>3 y; aOR: 1.43; 95% CI, 1.01-2.03; P = 0.046), and higher death-censored graft loss (adjusted hazard ratio 1.36; 95% CI, 1.02-1.12; P = 0.036) versus higher SES recipients (Q2–Q4). Conclusions. We observed significant socioeconomic disparities in kidney transplant access, dialysis duration, and graft survival. The HOUSES index may be a promising tool for individual-based targeted interventions as it identifies SES on an individual rather than an area-level basis.

Abstract Background The incidence of respiratory syncytial virus (RSV)–acute respiratory infection (ARI) in community-dwelling adults after the Omicron variant of the COVID-19 pandemic is unknown. Our aim was to assess the incidence of RSV-ARI in adults aged 18 to 64 years over 2 consecutive RSV seasons (October–April 2022–2024) in 4 US states. Methods This community-based prospective cohort study comprised 7501 participants in Minnesota, Wisconsin, Florida, and Arizona. We calculated RSV-ARI and RSV–lower respiratory tract disease (LRTD) incidence and attack rates. We reported unadjusted incidence by age group, gender, race and ethnicity, Charlson Comorbidity Index, socioeconomic status, residential state, and rural/urban setting. Results Seasons 1 and 2 had 2250 and 2377 ARI episodes, respectively, with an RSV-ARI positivity rate of 5.5% for season 1 and 5.8% for season 2 among those tested. In season 1, the overall incidence of RSV-ARI was 27.71 (95% CI, 22.82–33.34) per 1000 person-years (1.49% attack rate). Almost half (49.0%) had RSV-LRTD, with an incidence of 13.53 (95% CI, 10.19–17.61) per 1000 person-years (0.73% attack rate). In season 2, the RSV-ARI and RSV-LRTD incidence rates were 26.39 (95% CI, 21.73–31.75) per 1000 person-years (1.51% attack rate) and 12.43 (95% CI, 9.31–16.26) per 1000 person-years (0.72% attack rate). RSV-ARI incidence peaked in November 2022 and December 2023. Conclusions Our observations suggest that RSV-ARI incidence and seasonal pattern are shifting to prepandemic RSV epidemiology.