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Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Background/Objectives: Erythromelalgia is a rare condition characterized by burning pain, redness, and warmth primarily in the extremities, usually worsened by heat and alleviated by cold. The objective of this study was to identify the top 10 priorities in pediatric erythromelalgia from multiple perspectives, including clinicians, people with lived experience of childhood-onset erythromelalgia, and their family members. Methods: A modified James Lind Alliance Priority-Setting Process was conducted. The top priorities were identified through four phases: (1) an international online survey to gather priorities, (2) data processing, (3) an interim prioritization online survey, and (4) a virtual workshop to set the final priorities. Results: In phase 1, 185 potential priorities were submitted by 74 respondents (53% patients, 24% family members, and 23% clinicians) that were developed into 68 unique research questions (phase 2). In phase 3, of the 68 questions, 50 were rated for importance by 58 participants (38% patients, 36% family members, and 26% clinicians), reducing the list to 25 questions. In phase 4, the top 10 was reached through consensus by 12 participants (33% patients, 25% family members, and 42% clinicians) across Canada, South Africa, the United States of America, and the United Kingdom. Conclusions: The final priorities focused on the treatment of erythromelalgia, understanding underlying mechanisms, the association of erythromelalgia with various body systems, and generating awareness. This list is the first international patient-centered research agenda for childhood-onset erythromelalgia and a call to action from key partners to improve future research and care.

Introduction: Transthyretin (TTR) amyloid cardiomyopathy (ATTR-CM) arises from amyloidogenic aggregates of destabilized TTR protein in variant (ATTRv-CM) or acquired wild-type TTR (ATTRwt-CM). The p.V142I (V122I) variant is the most common pathogenic TTR allele in the USA and has higher mortality vs wild type. Acoramidis, an oral TTR stabilizer achieving ≥90% stabilization, is approved in USA, UK, Europe, and Japan for treating ATTR-CM in adults. In ATTRibute-CM (NCT03860935), acoramidis showed a reduction in all-cause mortality (ACM) or first cardiovascular-related hospitalization (CVH) vs placebo (PBO), with consistent benefit in ATTRwt-CM and ATTRv-CM (all variants). We report clinical outcomes in participants with p.V142I ATTRv-CM. Research Question: What was the efficacy of acoramidis for clinical outcomes (ACM, CVH) in participants with p.V142I ATTRv-CM in ATTRibute-CM? Methods: In ATTRibute-CM, 632 participants were randomized 2:1 to receive acoramidis HCl 800 mg or PBO twice daily for 30 months. All participants enrolled in open-label extension (OLE) received acoramidis only. Exploratory post hoc analyses were done in the p.V142I ATTRv-CM subgroup. Time-to-event analyses used a stratified Cox proportional hazards model using treatment group as an explanatory factor and baseline 6MWD as a covariate, stratified by randomization factors: serum NT-proBNP and eGFR. ACM was analyzed at Month 42 (ATTRibute-CM 30 months + 12 months OLE). Results: Of the 59 patients with ATTRv-CM reported at randomization, 35 (59.3%) had p.V142I (23 acoramidis, 12 PBO) with comparable baseline characteristics; 4 were homozygous for p.V142I (1 acoramidis, 3 PBO). Through Month 30, ACM/first CVH occurred in 43.5% (10/23) of acoramidis vs 83.3% (10/12) in PBO (HR 0.311; 95% CI 0.120–0.805; Figure 1 ). Through Month 42, ACM occurred in 26.1% (6/23) of continuous acoramidis vs 66.7% (8/12) in PBO to acoramidis (HR 0.307; 95% CI 0.097–0.973; Figure 2 ). Conclusions: In participants with p.V142I ATTRv-CM, acoramidis use was associated with 69% risk reduction in ACM/first CVH through Month 30 and ACM through Month 42 vs PBO. This is the first report of clinical benefit of this magnitude observed in this high-risk population. These findings have biologic plausibility and may reflect the near-complete stabilization observed experimentally with acoramidis in p.V142I ATTR fibrils. These observations require confirmation in larger cohort studies.

Background: Sudden cardiac death (SCD) is a leading cause of mortality in the U.S., with emerging evidence pointing to racial disparities and the impact of social vulnerability. Yet, geographic patterns integrating race and county-level vulnerability remain underexplored. Objective: To identify U.S. counties where socially vulnerable communities, stratified by race/ethnicity, experience disproportionate burdens of SCD-related mortality. Methods: We analyzed county-level data (1999-2020), integrating age-adjusted mortality rates (AAMR) for SCD with the 2020 CDC Social Vulnerability Index (SVI). Counties were categorized into SVI quartiles (Q1: Low to Q4: High Social Vulnerability). Analyses were stratified by race/ethnicity: Black or African American, Hispanic/Latino, White, American Indian/Alaska Native (AI/AN), and Asian/Pacific Islander (API). We used RStudio (v2023.06.1) for data cleaning, ANOVA testing, and descriptive analysis. “Unreliable” mortality values were handled as missing or set to zero, with only valid AAMR > 0 included. Hotspot counties were identified by selecting the top decile of AAMR SCD within Q4 SVI counties. Results: Significant disparities emerged across SVI quartiles for Black (p = 0.0003), Hispanic (p < 0.0001), and White (p < 0.0001) groups. Mean AAMR more than doubled from low to high SVI counties in Black communities (17.0 to 39.4 per 100,000). White and Hispanic groups showed smaller but consistent increases. API (p = 0.60) or AI/AN (p = 0.63) groups showed no significant trends. Madison Parish, LA appeared in the top-10 highest-burden counties across all groups. Black populations faced extreme rates in some SVI counties (e.g., Madison Parish, LA: 351.4 per 100,000), while API groups had low AAMR even in vulnerable areas. Data misclassification limited interpretation in the Hispanic group. Conclusions: Black, Hispanic, and White populations showed significant differences in SCD mortality tied to social vulnerability. Black populations in the most vulnerable areas experienced more than twice the rate of mortality compared to those in less vulnerable areas, suggesting a strong correlation between social vulnerability and SCD mortality in Black communities. API and AI/AN groups showed no significant associations, likely due to small sample sizes. Madison Parish, LA reflects the compounded impact of structural disadvantage. Findings support targeted interventions in socially and racially vulnerable counties to reduce preventable cardiac deaths.

Background: One of the most troublesome complications of acute pericarditis is recurrence. Non-steroidal anti-inflammatory drugs (NSAIDs) and colchicine form the cornerstone treatment, with the addition of steroids in cases of incomplete response. Recent evidence also suggests a role for interleukin-1 (IL-1) antagonists in challenging cases of recurrence. However, with an increasing number of potential therapies, our study aims to examine the relative efficacy of these anti-inflammatory treatments for recurrent pericarditis risk reduction. Methods: We searched Medline, Embase, and the Cochrane Central Register of Controlled Trials in October 2023. We included randomized controlled trials (RCTs) and prospective cohort studies of patients with pericarditis treated with a drug with anti-inflammatory properties compared with those treated with a control. The main outcome evaluated was pericarditis recurrence. Results: A total of 6,831 studies were screened, of which 25 articles were included (14 RCTs and 11 cohort studies) for a total number of patients of 3,561. The mean age across studies was 54.82 years for adults and 9.04 years for children (females = 40.55%). The average follow-up duration was 20.03 months. Bayesian network meta-analysis was performed to calculate risk estimates using a random effects model (Figure 1). Goflikicept, a fusion protein that neutralizes IL-1, showed a significant reduction in recurrent pericarditis rates (OR: 0.00, 95% Credible Limits [Crl]: 0.00-0.08). Similarly, anakinra (OR: 0.01, 95% Crl: 0.00-0.13), rilonacept (OR: 0.02, 95% Crl: 0.00-0.22) and colchicine (OR: 0.35, 95% Crl: 0.19-0.64) were associated with a significant reduction in recurrent pericarditis events. High dose colchicine (OR: 0.70, 95% Crl: 0.13-4.12) was not superior to regular dose colchicine (1 mg vs 0.6 mg twice daily, respectively). Interestingly, there was not enough data to make a meaningful comparison between steroids and control. Conclusion: In our analysis, goflikicept, rilonacept, and anakinra were most effective at reducing recurrent pericarditis rates. However, the evidence is based on a small number of studies. Our analysis also corroborated evidence regarding the efficacy of colchicine in reducing pericarditis recurrence. For a comprehensive analysis of the benefits and harms of anti-inflammatory therapies, larger comparative studies or network meta-analyses of patient-level data are required.

Background: Pulmonary hypertension (PH) is a life-threatening disease affecting up to 1% of the global population. Diagnosis can be challenging and is often delayed due to the need for advanced imaging and invasive procedures. The use of artificial intelligence applied to ECGs (ECG-AI) has been shown to detect subtle patterns in voltage-time data and may be a valuable tool for the early detection of PH. Hypothesis and Purpose: To evaluate the performance of a previously trained, ECG-AI algorithm to detect PH (ECG-AI PH) using real-world data (RWD) collected in a multicenter, validation study. A joint primary hypothesis required sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) to exceed the null values of 76%, 70%, 10% and 90%. Study Design and Methods: This retrospective validation study was conducted at 5 geographically diverse U.S. health systems. Adult subjects were eligible for inclusion if they had a 12-lead ECG paired with an echocardiogram (Echo) in which tricuspid regurgitation velocity (TRV) was recorded, following presentation with dyspnea. Patients were classified according to echocardiographic criteria as either PH (PH+, TRV >3.4 m/s) or controls (PH-, TRV ≤2.8 m/s) to simulate the real-world use of ECG-AI, where a positive result could lead to a follow-up Echo. The study database was locked before processing the digital ECGs with ECG-AI PH. Performance was also estimated in a subset of subjects that later had a right heart catheterization using mPAP ≥ 20mmHg as the definition of PH. Results: A total of 14281 subjects (53% female, 63% aged 50+ years) met the inclusion criteria, including 3019 PH+ cases and 11262 PH- controls (Figure). Sn and Sp were 84.0% (95% CI: 82.6%, 85.3%) and 71.7% (95% CI: 70.9%, 72.6%), respectively. The positive and negative predictive values were 18.9% (95% CI: 18.4%, 19.4%) and 98.3% (95% CI: 98.1%, 98.4%), respectively, at 7.3% prevalence. Each endpoint met pre-defined performance criteria. In the subset of 1683 subjects with a follow up RHC, performance remained robust (Sn 85% (1155/1358); Sp 46% (151/325)). Conclusion: While ECG-AI PH was first developed as an investigational tool to detect PH, continued development as software as a medical device for clinical use demonstrated that the algorithm retained strong performance to detect PH in diverse, non-overlapping clinical settings and patient populations.

Importance The prevalence of cardiovascular disease differs substantially across neighborhoods. However, few studies have examined the contribution of neighborhood-level structural racism to inequities in cardiovascular health. Objective To investigate the association between neighborhood-level manifestations of structural racism and the prevalence of cardiovascular clinical and behavioral risk factors and cardiovascular diseases. Design, Setting, and Participants This cross-sectional study consisted of 71 915 US census tracts. The Structural Racism Effect Index (SREI) was appended to the 2020 Centers for Disease Control and Prevention’s PLACES dataset. Race and ethnicity were self-reported and obtained from the 2019 American Community Survey 5-year estimates. Data analysis was conducted from June 2024 to October 2024. Exposure The SREI is a composite score of census tract measures within 9 domains affected by structural racism (built environment, criminal justice, education, employment, housing, income and poverty, social cohesion, transportation, and wealth). The SREI scores were categorized into distribution-based quintiles, where higher quintiles represented greater neighborhood structural racism. Main Outcomes and Measures Neighborhood-level prevalence of cardiovascular clinical (high blood pressure, high cholesterol, obesity, and diabetes) and behavioral (current cigarette smoking and no leisure-time physical activity) risk factors and cardiovascular disease (coronary heart disease and stroke). Multilevel-linear mixed models, adjusting for confounders, were used to estimate adjusted prevalence rate ratios (aPRR). Results Among 71 915 census tracts, neighborhoods in the highest quintiles of structural racism were more likely than neighborhoods in the lowest quintile to be in the southern region (quintile 1, 19.9% vs quintile 5, 56.8%). The proportion of the population that was Black was largest in neighborhoods in the highest quintile of structural racism (quintile 1, 2.2% vs quintile 5, 23.0%). After adjustment, compared with the lowest quintile of structural racism, the highest quintile had significantly higher prevalence rates of cardiovascular clinical risk factors, including high blood pressure (aPRR, 1.37; 95% CI, 1.37-1.38), obesity (aPRR, 1.40; 95% CI, 1.39-1.40), and diabetes (aPRR, 1.80; 95% CI, 1.79-1.81). Similarly, for cardiovascular behavioral risk factors, the highest quintile of structural racism had significantly higher prevalence rates of current cigarette smoking (aPRR, 1.84; 95% CI, 1.83-1.85) and no leisure-time physical activity (aPRR, 1.88; 95% CI, 1.87-1.89). Additionally, for cardiovascular diseases, the highest quintile of structural racism had higher prevalence rates of coronary heart disease (aPRR, 1.80; 95% CI, 1.79-1.82) and stroke (aPRR, 1.99; 95% CI, 1.98-2.00). Conclusions and Relevance In this cross-sectional study, structural racism was associated with inequities in neighborhood cardiovascular health, highlighting opportunities for place-based prevention efforts.

Background: The incidence of lymphedema may be as high as 65% among breast cancer patients, varying according to the diagnostic method and locoregional treatment. Therefore, investigations of preventive methods are highly welcomed. Our goal was to conduct a systematic review of the literature about the use of axillary reverse mapping to prevent lymphedema during breast cancer treatment. We hypothesized that identification of arm-draining lymph nodes may decrease the incidence of lymphedema. Methods: On October 7, 2019, we conducted a systematic review of studies in PubMed, Cochrane Clinical Answers, and Cochrane Central Register of Controlled Trials, without time frame or language limitations, on the use of axillary reverse mapping to prevent lymphedema during breast cancer treatment. We excluded articles that investigated other uses of lymphoscintigraphy, such as lymphedema diagnosis or treatment evaluation. Results: Of 104 potential articles found in the literature, 5 studies fulfilled the eligibility criteria. A total of 501 patients were included. Reverse mapping was done with radiography or single-photon emission computed tomography/computed tomography. Moreover, the examination was applied with different treatments, such as axillary lymph node dissection or radiotherapy, allowing preservation of noncompromised lymph nodes. Axillary reverse mapping also had prognostic value and was used with sentinel lymph node biopsy to identify patients at higher risk for lymphedema. Only one study compared the incidence of lymphedema between patients who received standard care or reverse mapping, showing significant benefits of its use. Conclusions: Use of axillary reverse mapping to prevent lymphedema is feasible and seems to provide valuable information for breast cancer treatment. Future studies that compare reverse mapping and standard care are still necessary.

Introduction Implementation science research increases the uptake of evidence-based interventions, which may improve health equity among racial and ethnic minorities. However, it is unclear how anti-racism and anti-colonialism practices have been integrated into implementation science research. The objectives of this scoping review are to describe the current conceptualisations of racism and colonialism within the USA, examine racism or colonialism-conscious approaches and analyse gaps in the operationalisation of anti-racism or anti-colonialism within implementation science studies. Methods and analysis This scoping review will be conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping reviews guidelines. The Center for Chronic Disease Reduction and Equity Promotion Across Minnesota conceptual framework and an implementation science anti-racism lens will guide the study design and analysis. To determine study eligibility for the scoping review, articles will undergo abstract and full-text screening by two independent reviewers and discrepancies will be settled together. Data charting will be extracted from included articles by eight independent reviewers. The search strategy will use controlled vocabulary and natural language keywords related to health equity, health disparities and anti-racism/colonialism on six databases. The scoping review will include studies that applied implementation science theories, models or frameworks among US-based populations. Additionally, included studies will report any of the following implementation activities: implementation strategies, implementation outcomes, adaptations to evidence-based interventions, or evaluations of pre-implementation or implementation context. Ethics and dissemination No ethical approval was required for the scoping review. Dissemination will be through publication in a peer-reviewed journal and conference presentations.