Citations

Introduction: Acoramidis, an oral transthyretin (TTR) stabilizer achieving near-complete (≥90%) TTR stabilization, is now approved in the USA, EU, Japan, and UK for the treatment of TTR amyloid cardiomyopathy (ATTR-CM). In the 30-month phase 3 ATTRibute-CM study, acoramidis reduced all-cause mortality (ACM) or first cardiovascular-related hospitalization (CVH) vs placebo. Through Month 42 (M42) of the open-label extension (OLE; 30 months ATTRibute-CM + 12 months OLE), the clinical benefit of acoramidis was sustained, resulting in a 36% and 43% risk reduction in ACM and ACM/first CVH, respectively, compared with the placebo to acoramidis group Research Question: Are the long-term clinical benefits of acoramidis on ACM and ACM/first CVH in ATTR-CM over 42 months consistent across patient subgroups? Methods: ATTRibute-CM study design has been previously described. At the end of the 30-month double-blind period, patients enrolled into OLE continued acoramidis or switched from placebo to acoramidis; all patients received open-label acoramidis HCI 800 mg BID. Data cut was performed after 12 months in OLE. Subgroup analysis for ACM and ACM/first CVH through M42 were conducted for randomization stratification factors (genotype, NT-proBNP, and eGFR levels) and other pre-specified subgroups. ACM included death due to any cause, cardiac mechanical assist device placement, and heart transplant. CVH included CV hospitalizations (≥24 h) and urgent visits (<24 h) for decompensated heart failure requiring IV diuretics and was adjudicated by an independent Clinical Events Committee. Results: Overall, 389 patients enrolled in the OLE (263 continuous acoramidis and 126 placebo to acoramidis). The analyses of ACM/first CVH ( Figure 1 ) and ACM ( Figure 2 ) through M42 consistently favored patients initially randomized to acoramidis across all patient subgroups, including those based on sex, age, country, ATTR-CM genotype, baseline NT-proBNP, baseline eGFR, NYHA class, and NAC stage. The largest effect size for the reduction in ACM/first CVH (HR <0.50) was observed in the following subgroups: female, non-Caucasian patients, variant ATTR-CM, or NAC stage 2. Conclusions: The long-term benefit of acoramidis was consistently shown in patients initially randomized to acoramidis treatment compared with placebo to acoramidis switch after 30 months across multiple clinically relevant subgroups, underscoring the importance of early initiation of acoramidis to reduce the long-term risk of ACM or CVH.

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.

Introduction: PH increases RV afterload, often leading to RV systolic and diastolic failure. The metabolic mechanisms underlying RV dysfunction remain poorly understood and are largely unexplored across non-PAH forms of PH. Aims: We aimed to identify which metabolites and metabolic pathways associated with imaging measures of RV systolic function. Methods: We analyzed data from the multi-center PVDOMICS cohort, which includes echo, CMR, invasive hemodynamics, clinical phenotyping, and untargeted plasma metabolomics (via Metabolon). RV systolic function metrics selected as the outcome measures for this study were fractional area change (echo), global longitudinal strain (echo), and RVEF (CMR). Associations between non-xenobiotic, named metabolites and RV function measures were assessed using linear regression adjusted for age, sex, BMI, and PH group, with significance defined by FDR <0.05. Metabolite set enrichment analysis (MSEA) was performed to identify significantly enriched pathways (FDR <0.20). To complement MSEA, we conducted mean-aggregation analysis: we averaged metabolite concentrations within each pathway and tested associations with RV function using the same covariate adjustments (FDR <0.05). Results: We identified 979 participants with plasma metabolomics and at least one available outcome measure (317 Group 1 PH; 106 Group 2 PH; 140 Group 3 PH; 51 Group 4 PH; 26 Group 5 PH; 81 Healthy Controls; 258 Disease Comparators). Linear regression identified 170 metabolites from the 647 named metabolites significantly associated with all 3 RV metrics (Top 10 by average ranked p-value displayed in Image 1 ). MSEA revealed seven enriched pathways across all RV metrics: Androgenic Steroids, Pregnenolone Steroids, Progestin Steroids, Fatty Acid Metabolism (Acyl Choline), Histidine metabolism, Vitamin A metabolism, Gamma-glutamyl Amino Acid ( Image 2) . Mean aggregation analysis showed that higher concentrations of Androgenic/Pregnenolone Steroids and Vitamin A metabolites strongly associated with improved RV function, while higher levels of Fatty Acid Metabolism (Acyl Carnitine) and Acetylated Peptides associated with worse function ( Image 3 ). Conclusions: Using data from the multi-institutional PVDOMICS cohort, we provide a blueprint of metabolites and metabolic pathways associated with RV systolic function across the spectrum of PH. Steroid hormones as well as Vitamin A and fatty acid metabolites emerged as central to RV systolic function.

Introduction: Higher mtDNA-CN reflects better mitochondrial function, while lower levels indicate mtDNA release and increased inflammation. Although mtDNA-CN serves as a marker of cardiovascular health, the importance and mechanism of risk associated with mtDNA in high-risk individuals with chronic coronary artery disease (CAD) remains poorly understood. To address this gap, we leveraged the ISCHEMIA Biorepository to: (1) evaluate the association between mtDNA-CN and all-cause death (ACD); and (2) define a transcriptomic profile associated with high mtDNA-CN and ACD risk for high-risk patients with CAD. Hypothesis: Higher mtDNA-CN is associated with reduced ACD risk and inflammation in high-risk patients enrolled in the ISCHEMIA Biorepository. Methods: Low pass whole genome sequencing and whole blood RNA-Seq were performed on 594 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. Data were processed using the NYU deciphEHR pipeline and mtDNA was quantified using mitoAnalyzer. mtDNA-CN was median split, with samples having values ≤ median classified as the 'low' group and those > median as the 'high' group. Unadjusted group differences were assessed using Chi-squared tests. Survival analysis was performed using Cox proportional hazard models, adjusted for age, sex, diabetes, eGFR, dialysis status, ischemia severity, and left ventricular ejection fraction. Adjusted differential gene expression (DGE) and gene set enrichment analysis (GSEA) were performed to explore molecular mechanisms underlying mtDNA-CN. Results: Median age was 67 (IQR: 57–78); 19% were female, 84% white, and 6% Hispanic. Hypertension (84%), diabetes (43%), and obesity (45%) were common; 26% had eGFR <60 mL/min/1.73 m 2 . Median mtDNA-CN was 153 counts per sample. After multivariate adjustment , mtDNA-CN > median was associated with a 48% reduction in ACD (aHR = 0.52, 95% CI: 0.30–0.90; P = 0.020) (Figure 1A) . DGE revealed downregulation of inflammatory genes in the mtDNA-CN group, including S100A9 (FC=-.41, p=3.32e-10) and S100A12 (FC=-.56, p=3.32e-10). Inflammatory pathways such as the inflammasome complex (NES=-2.17, p=9.32e-03) and interleukin-1 production (NES= -2.02, p=6.60e-03) were downregulated among participants in the high mtDNA-CN ( Figure 1B) . Conclusion: Higher mtDNA-CN is associated with lower risk of ACD and reduced inflammasome activity, suggesting that enhanced mitochondrial health may mitigate inflammasome-related pathology linked to ACD in patients with CAD.

Objective To evaluate outcomes in patients with type 2 endoleak (T2E) and the impact of treatment outside the device instructions for use (IFU). Methods This retrospective single-center study included abdominal aortic aneurysms (AAA) patients who underwent EVAR (2011- 2024). Primary outcomes were 30-day and mid-term complications, reintervention, and mortality by T2E status. Propensity score matching was applied and secondary analysis stratified outcomes by IFU compliance, comparing within ( in IFU) or outside( out IFU) IFU in each T2E group. Results Among 154 EVAR patients (137 men (89.1%) and 17 women (11.0%); mean age 77.5 ± 7.6 years), 77 were T2E(−), and 77 were T2E(+). Baseline characteristics were similar. Thirty-day complications were comparable (T2E(−): 5, 6.4% vs T2E(+): 2, 2.56%, P = 0.72). The mean follow-up duration was 2.7 ± 2.4 years. Sac diameter change (Δ) decreased in the T2E(−) (7.7 ± 8.4 mm) and enlarged in the T2E(+) (1.79 ± 12.5 mm; P < 0.01). Mid-term graft-related complications (T2E(−): 3, 3.8% vs T2E(+): 49, 62.8%, P < 0.01) and reinterventions (T2E(−): 3, 3.8%, vs T2E(+): 20, 25.6% P < 0.01) were higher in the T2E(+) with no difference in mortality ( P = 1.00). These findings remained after excluding type 1 endoleaks. Among the T2E(+), those treated out IFU had longer hospital stays ( out IFU: 3.0 ± 2.8 days vs in IFU: 1.8 ± 2.0 days, P = 0.03), higher T1E ( out IFU: 3, 33.3% vs in IFU: 1, 4.34%, P < 0.01), higher rates of reintervention ( out IFU: 9, 100.0% vs in IFU:17; 24.6%, P < 0.01) and higher all-cause mortality than those within IFU criteria ( out IFU: 5, 55.0% vs in IFU: 13, 18.8%, P < 0.01). IFU status did not significantly affect outcomes in T2E(−) patients. Conclusions T2E is associated with sac growth and increased reinterventions, but not higher mortality. On subgroup analysis, those T2E(+) treated out IFU had longer hospitalizations, higher T1E rates, more reinterventions, and higher all-cause; but not aneurysmal-related mortality.

Abstract Artificial intelligence (AI) encompasses the development of systems that can perform human‐like tasks, such as treatment guidance, decision‐making, pattern recognition and understanding language. Within AI, machine learning and deep learning play pivotal roles in diagnosis and outcome prediction, while natural language processing aids in synthesising large datasets from the electronic medical record. In orthopaedics, AI has demonstrated success in various areas, including image evaluation, surgical planning, outcome prediction, cohort identification and administrative tasks. The purpose of this manuscript was to provide an overview of the benefits of AI implementation within the field of orthopaedics. An additional goal was to address the challenges associated with producing high quality AI‐based research in a rapidly developing field. Level of Evidence Level IV.

Abstract INTRODUCTION The Genetic Frontotemporal Initiative (GENFI) and Advancing Research and Treatment in Frontotemporal Lobar Degeneration (ARTFL)‐Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Longitudinal Frontotemporal Lobar Degeneration Study (ALLFTD) consortia developed Clinical Dementia Rating (CDR)‐derived scales with a motor domain to overcome systematic underestimation of disease severity by the CDR. We calculated disease severity scores using these scales in a mixed neurodegenerative cohort and correlated them with objective motor measures. METHODS The CDR plus National Alzheimer's Coordinating Center (NACC) Frontotemporal Lobar Degeneration (FTLD), CDR + NACC FTLD‐M (Motor), and Multidomain Impairment Rating (MIR) scores and motor measures were determined and correlated in 242 participants. RESULTS Both CDR + NACC FTLD‐M and MIR showed increased disease severity scores and correlated with motor measures. These findings were held in 81 amyotrophic lateral sclerosis (ALS) participants and correlated with the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale. Including a motor domain required fewer study participants in a simulated clinical trial sample size calculation. DISCUSSION With a motor domain, CDR + NACC FTLD‐M and MIR improve disease severity classification and correlate with quantitative motor assessments. This addition more fully captures the extent of symptoms across the FTD‐ALS spectrum and improves clinical trial efficiency. Highlights CDR + NACC FTLD‐M and MIR strongly correlate with objective motor measures. The enhanced scales improve disease severity classification in FTD and ALS. Greater clinical trial efficiency is achieved using these enhanced scales.

ABSTRACT Suicidality contributes substantially to global morbidity and mortality, yet despite its heritability, its biological etiology remains largely elusive. We conducted multi-ancestry genome-wide association study meta-analyses of suicidal ideation (259,747 cases), suicide attempt (64,993 cases), suicide death (9,197 cases), and suicidal behavior (suicide attempt/ death, 75,300 cases), across 54 cohorts (e.g., the Psychiatric Genomics Consortium, Million Veteran Program, UK Biobank). We identified 77 significant loci across meta-analyses, including 59 previously unreported for suicidality. SNP-based heritability ranged from 2.0-6.7% and there were strong, yet incomplete, genetic correlations between suicidality phenotypes (0.70-0.88). Fine-mapping prioritized putative causal SNPs and 20 credible genes. Enrichment analyses implicated synaptic pathways and neuronal populations predominantly in subcortical brain regions (e.g., amygdala excitatory, medium spiny, hippocampal CA1-3). Together, these findings establish suicidality as a polygenic set of traits with both shared and distinct genetic influences, providing a foundation for future studies of suicide biology and etiology.

Abstract Disclosure: I. Bancos: AstraZeneca. A. Ben-Shlomo: AstraZeneca. O. Hamidi: Recordati Rare Diseases, Neurocrine Biosciences, Corcept Therapeutics, Crinetics, Camurus, Xeris. A. Hamrahian: AstraZeneca. W. Huang: None. L.S. Kirschner: Corcept Therapeutics, AstraZeneca, Crinetics, Sparrow Pharma, Spruce Biosciences. R. Sam: AstraZeneca. A.F. Turcu: AstraZeneca. A. Lihn: AstraZeneca. A. Mallappa: AstraZeneca. S. Perl: AstraZeneca. B. Tuyishimire: AstraZeneca. M.J. Brown: GlaxoSmithKline, Pfizer, Inc., Bristol-Myers Squibb, AstraZeneca. Introduction: Mineralocorticoid receptor antagonist (MRA) treatment for primary aldosteronism (PA) has limited efficacy in some patients. Highly selective, competitive aldosterone synthase inhibitors (ASIs) offer an alternative therapeutic approach. SPARK (NCT04605549) was a Phase 2, open-label, multicenter trial of the ASI baxdrostat in patients with PA. Methods: Eligibility entailed: aged ≥18 years; diagnosis of PA; willingness to discontinue MRA up to 4 weeks before baxdrostat initiation; and systolic blood pressure (SBP) rise ≥20 mmHg or SBP ≥160 mmHg after discontinuation of MRA, or SBP ≥150 mmHg for patients with newly diagnosed PA who had not taken MRAs in the past 12 weeks. Patients entered a 12-week treatment period (Part 1) of once daily baxdrostat 2 mg, up-titrated to 4 mg or 8 mg at week (W) 4 or W8, respectively, if there was no significant risk of hypotension. Baxdrostat could be down-titrated to 2 mg or continued at 4 mg as needed. After W12, patients could continue baxdrostat up to W72 (Part 2) with doses at investigators’ discretion. Primary endpoints were safety, tolerability and change from baseline in mean seated SBP at W12. Results: Fifteen patients enrolled and completed Part 1; 14 patients continued to Part 2. Median (range) age was 54 (32, 75) years, 67% of patients were male, 47% were White, and median (range) body mass index was 32.0 (24.4, 41.4) kg/m2. At baseline, plasma renin activity (PRA) was &lt;1 ng/mL/h in 12/15 (80%) patients, and 8/15 (53%) patients had hypokalemia (serum potassium &lt;3.5 mmol/L). Mean (range) baseline SBP was 151.5 (130, 174) mmHg; diastolic BP (DBP) was 90.3 (74, 103) mmHg. At W12, mean (range) SBP change from baseline was –29.5 (–47, –12), –24.4 (–31, –17), and –23.9 (–47, –8) mmHg for patients on baxdrostat 2 mg (n=2), 4 mg (n=5), and 8 mg (n=7), respectively; DBP change was –8.0 (–14, –2), –10.4 (–20, 0), and –11.6 (–25, 7) mmHg, respectively. Overall, 11/15 (73%) patients achieved BP &lt;140/90 mmHg and 6/15 (40%) achieved BP &lt;130/80 mmHg at W12; reduced BP persisted in Part 2. No deaths were reported. Nine out of 15 (60%) patients had a treatment-emergent adverse event (TEAE) during W4–W12 of Part 1 (all mild/moderate), including 1/15 (7%) patient with hyperkalemia; no serious TEAEs were reported. In Part 2, 14/14 (100%) patients had a TEAE (most mild/moderate), including 5/14 (36%) patients with hyperkalemia; one serious TEAE of hyperkalemia was reported. Mean (standard deviation, SD) serum potassium levels increased from 3.9 (0.6) mEq/L at baseline to 4.7 (0.5) mEq/L at W12. Mean (SD) 24-h urine aldosterone excretion at baseline and W12 were 30.3 (17.5) and 3.2 (2.7) µg/day, respectively. At W12, 7/15 (47%) patients had achieved unsuppressed PRA (≥1.0 ng/mL/h). Conclusions: Baxdrostat, an ASI, was well tolerated and led to reduced BP and unsuppressed renin in patients with PA. Inhibiting aldosterone synthase may be an alternative to MRAs for treating PA. Presentation: Sunday, July 13, 2025