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Abstract Background Hypertrophic cardiomyopathy (HCM) is a heritable cardiac disorder characterized by increased left ventricular (LV) wall thickness, often leading to heart failure (HF). The role of cardiovascular magnetic resonance (CMR) imaging in predicting new onset of HF symptoms in patients with HCM remains unknown. This study aimed to identify CMR predictors of new-onset HF symptoms in individuals with HCM. Methods This study was a single-centre retrospective cohort study of HCM patients treated at a tertiary referral centre in the USA who underwent CMR examination between 1998 and 2018, had no HF symptoms at baseline CMR, and at least 1 year of follow-up. Clinical data were collected by review of electronic medical records, and CMR images were analyzed by a blinded expert cardiac radiologis. The primary outcome was new onset of HF symptoms, defined as New York Heart Association (NYHA) class ≥ II at follow-up. Kaplan–Meier analyses and Cox proportional hazard analyses were performed. Results Of 1462 patients diagnosed with HCM who had at least 1 CMR, 276 HCM patients without HF symptoms (average age 52.7 years, 33.3% female),median maximum left ventricular (LV) wall thickness was 19 mm ([IQR] 17–22) with a and median LV ejection fraction of 71% (IQR 66–77). Late gadolinium enhancement was detected in 56.2%) patients (60.7% had mild; 30.7% moderate; 8.6% severe). During a median follow-up period of 6.3 years, 93 patients developed HF symptoms (NYHA class II in 56 (60.2%); class III in 31 (33.3%); and class IV in 6 (6.5%). Multivariable analysis adjusted for age showed that LA enlargement (HR 1.626; 95% CI 1.01–2.62; P = .045) and LV mass index (HR 1.014; 95% CI 1.007–1.022; P≤ .001) and sex (HR 1.7; 95% CI 1.074–2.691; P = .023) were independent predictors of new onset of HF symptoms in patients with HCM. Conclusions Nearly half of the patients with HCM developed HF symptoms within 6.3 years. Left atrial enlargement, LV mass index, and sex were independent predictors of new onset of HF symptoms in HCM patients. These findings emphasize the value of CMR in HF risk stratification.

BACKGROUND/OBJECTIVES Pediatric hospital medicine (PHM) is a growing field with a unique scholarly perspective and evolving role in academic leadership. Since the last systematic assessment of PHM research in 2009, predating subspecialty certification in 2016 and fellowship accreditation in 2020, the research infrastructure within PHM has not been reevaluated. We sought to assess the current state of PHM research by assessing the number, scope, and scholarly domains of research faculty, as well as research funding and support. METHODS Using the Pediatrics Research in Inpatient Settings Network, we distributed a cross-sectional survey to PHM group leaders across the United States and Canada. The 16-item instrument, adapted from prior PHM and adult hospital medicine surveys, assessed program demographics, faculty effort allocation, research support, funding, and scholarly domains. Surveys were distributed via REDCap with follow-up reminders. Descriptive statistics were used. RESULTS 49 programs responded (51% response rate), representing 1702 faculty (∼40% of US pediatric hospitalists). Fewer than half of programs (n = 21, 43%) reported faculty with more than 50% research effort. One-hundred and ninety faculty members (11%) had dedicated research time, and 72% of those conducting quality improvement research did so without any protected effort. Most PHM programs (n = 27, 55%) received less than $100 000 in total annual research funding. CONCLUSIONS Despite recent PHM subspecialty designation and pediatric hospitalist desire to conduct research, dedicated time and associated supports are uncommon in PHM groups. Improvements in the PHM research pipeline will require understanding institutional financial constraints and diversifying and strengthening research funding.

e16405 Background: Pancreatic cancer remains one of the most lethal malignancies, with a rising incidence and persistently poor survival outcomes. Gemcitabine plus nab-paclitaxel is an established standard regimen for advanced disease, however, the conventional triweekly schedule is frequently associated with significant toxicity. Biweekly dosing has been proposed to enhance tolerability while maintaining efficacy, although evidence remains limited and heterogeneous. The objective was to evaluate the efficacy and safety of biweekly versus standard gemcitabine/nab-paclitaxel in patients with advanced pancreatic cancer. Methods: A systematic search of PubMed, Embase, and the Cochrane Library was conducted to identify studies comparing Biweekly versus Standard Triweekly: gemcitabine / nab-paclitaxel in patients with advanced pancreatic cancer. The primary outcomes of interest included partial response, and treatment-related toxicities, specifically anemia, neutropenia, and use of growth factors. Statistical analyses were performed using Review Manager. Heterogeneity was assessed using the I 2 statistic, and risk of bias was evaluated using the ROBINS-I tool. Results: A total of 1357 patients from eight observational studies were included. Comparative analysis showed no significant difference in partial response between biweekly and standard triweekly gemcitabine/nab-paclitaxel in patients with advanced pancreatic cancer with a risk ratio (RR) of 0.77 (95% CI 0.57,1.04, p = 0.09). Similarly, no significant differences were observed between regimens in the incidence of anemia (RR = 1.09; 95% CI 0.74–1.59; p = 0.66) or neutropenia (RR = 1.09; 95% CI 0.86–1.37; p = 0.48). however, growth factor use was significantly lower with biweekly dosing (RR = 0.71; 95% CI 0.58–0.87; p = 0.0009). Overall survival was comparable between groups RR = 1.02 (95% CI 0.71, 1.45 p = 0.93). Conclusions: Administration of gemcitabine/nab-paclitaxel biweekly yielded clinical outcomes and safety profiles comparable to the conventional regimen, while significantly reducing the need for growth factors as supportive care. These data suggest that a biweekly regimen could be an effective alternative; however, further prospective randomized studies are necessary to verify these findings and better understand their clinical application.

Abstract Background High‐resolution MRI is essential for accurate diagnosis and treatment planning, but its clinical acquisition is often constrained by long scanning times, which increase patient discomfort and reduce scanner throughput. While super‐resolution (SR) techniques offer a post‐acquisition solution to enhance resolution, existing deep learning approaches face trade‐offs between reconstruction fidelity and computational efficiency, limiting their clinical applicability. Purpose This study aims to develop an efficient and accurate deep learning framework for MRI SR that preserves fine anatomical detail while maintaining low computational overhead, enabling practical integration into clinical workflows. Materials and Methods We propose a novel SR framework based on multi‐head selective state‐space models (MHSSM) integrated with a lightweight channel multilayer perceptron (MLP). The model employs 2D patch extraction with hybrid scanning strategies (vertical, horizontal, and diagonal) to capture long‐range dependencies while mitigating pixel forgetting. Each MambaFormer block combines MHSSM, depthwise convolutions, and gated channel mixing to balance local and global feature representation. The framework was trained and evaluated on two distinct datasets: 7T brain T1 MP2RAGE maps (142 subjects) and 1.5T prostate T2w MRI (334 subjects). Performance was compared against multiple baselines including Bicubic interpolation, GAN‐based (CycleGAN, Pix2pix, SPSR), transformer‐based (SwinIR), Mamba‐based (MambaIR), and diffusion‐based (I 2 SB, Res‐SRDiff) methods. Results The proposed model demonstrated superior performance across all evaluation metrics while maintaining exceptional computational efficiency. On the 7T brain dataset, our method achieved the highest structural similarity (SSIM: ) and peak signal‐to‐noise ratio (PSNR: dB), along with the best perceptual quality scores (LPIPS: ; GMSD: ). These results represented statistically significant improvements over all baselines (), including a 2.1% SSIM gain over SPSR and a 2.4% PSNR improvement over Res‐SRDiff. For the prostate dataset, the model similarly outperformed competing approaches, achieving SSIM of , PSNR of dB, LPIPS of , and GMSD of . Notably, our framework accomplished these results with only 0.9 million parameters and 57 GFLOPs, representing reductions of 99.8% in parameters and 97.5% in computational operations compared to Res‐SRDiff, while also substantially outperforming SwinIR and MambaIR in both accuracy and efficiency metrics. Conclusion The proposed framework provides a computationally efficient yet accurate solution for MRI SR, delivering well‐defined anatomical details and improved perceptual fidelity across anatomically distinct datasets. By significantly reducing computational demands while maintaining state‐of‐the‐art performance, the model offers strong potential for feasibility toward clinical translation and scalable integration into future imaging workflows.

12010 Background: BWEL (Alliance A011401; NCT02750826) is a Phase III trial that randomizes patients (pts) with stage II-III breast cancer and body mass index (BMI) ≥27 kg/m 2 1:1 to a 24-month (mo) lifestyle-based WLI + health education (HE) or HE alone. Here we report prespecified secondary outcomes of the impact of the WLI on patient-reported QOL and symptoms. Methods: The first 540 BWEL pts (randomized between 9/2016 and 7/2017) were included in this substudy that collected PROMIS 29 Profile 2.0 and Global Health scores at enrollment, 6 and 24 mos. Adjusting for baseline scores, mean physical function (predefined substudy primary outcome), global physical and mental health, fatigue and other scores were compared at 6 and 24 mos using analysis of covariance (ANCOVA). P-values <0.05 were considered significant. Positive differences in positive attributes (e.g., physical function) and negative differences in negative attributes (e.g., anxiety) represented better outcomes in the WLI arm. Results: At baseline, median BMI was 32.9 kg/m 2 (26.5 – 69.1), median age was 53 (25 - 78) years; 83.9% of pts were non-Hispanic White, 10.7% were Black and 5.9% were Hispanic. At 6 mos, the WLI (vs HE) arm had significantly better physical function (ANCOVA-based mean difference between arms 1.9 [95% CI 0.8, 3.0]; p<0.001), global physical health (2.0 [95% CI 0.9, 3.0]; p<0.001), global mental health (1.30 [95% CI 0.2, 2.4], p=0.03), social roles and activities (2.3 [95% CI 1.1, 3.6]; p<0.001), and fatigue (-1.7 [95% CI -3.1, -0.4], p=0.01) (Table). Improvements were generally maintained at 24 mos. Similar findings were seen in analyses using longitudinal mixed modeling. Conclusions: The BWEL WLI demonstrated QOL benefits for patients with breast cancer, resulting in significantly better physical function, global physical and mental health, and symptoms. Future analyses will evaluate which populations experienced the most benefit, as well as the relationships among QOL, symptoms, and weight loss. Support: U10CA180821, U10CA180882, UG1CA189823; U10CA180820; U10CA180868; U10CA180863, CCS 707213; U10CA180888; UG1CA189858; https://acknowledgments.alliancefound.org. Clinical trial information: NCT02750826 . Analysis of covariance-adjusted least squares means values at 6-mos adjusted for baseline scores. QOL/Symptom Attributes HE WLI Between arm difference (95% CI)* P value Physical Function 47.1 49.0 1.9 (0.8, 3.0) <0.001 Global Physical Health 46.2 48.1 2.0 (0.9, 3.0) <0.001 Global Mental Health 48.6 49.9 1.3 (0.2, 2.4) 0.03 Social Roles and Activities 52.7 55.0 2.3 (1.1, 3.6) <0.001 Anxiety 50.2 50.0 -0.2 (-1.6, 1.2) 0.77 Depression 47.5 47.5 -0.0 (11.2, 1.2) 0.96 Fatigue 50.6 48.9 -1.7 (-3.1, -0.4) 0.01 Sleep Disturbance 51.0 51.1 0.1 (-0.6, 0.8) 0.80 Pain Interference 51.3 50.3 -1.0 (-2.4, 0.4) 0.15 *Positive differences in positive attributes and negative differences in negative attributes favor WLI arm.

10522 Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality. While antiviral and metabolic therapies have reduced incidence, scalable pharmacologic strategies for primary prevention (PP) remain a critical unmet need. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have demonstrated preclinical antitumor activity and the potential to mitigate hepatic lipotoxicity while promoting metabolic reprogramming to stabilize cirrhosis. However, while chemoprevention signals are observed in metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes, the efficacy of GLP-1RAs for PP across diverse liver disease etiologies remains underexplored. To address this gap, we conducted a global, multicenter analysis on the efficacy and safety of GLP-1RAs for the PP of HCC in a pan-etiology high-risk cohort. Methods: A retrospective cohort study was conducted using the TriNetX database (150M patients across 108 health organizations). Adults 18–90 years at elevated HCC risk with ≥ 1 risk factor (chronic viral hepatitis, cirrhosis, MASLD, alcohol use disorder, or hereditary liver disorders) were identified. Cohort A (≥3 months of GLP-1RA) was propensity score-matched 1:1 with Cohort B (non-users) on demographics, HbA1c, BMI, and MELD-Na scores. The primary endpoint was incident HCC, and secondary endpoints were incidence of gastrointestinal (GI) side effects. We employed a 3-month lag period to mitigate immortal time bias. Time-to-event outcomes were assessed via Kaplan-Meier analysis and Cox proportional hazards models. Sensitivity & subgroup analyses were performed to confirm robustness across non-metabolic etiologies. Results: After matching, 592,718 patients were analyzed (296,359 per cohort). Median follow-up was 2,450 days for GLP-1RA users vs 2,114 days for non-users. GLP-1RA use was associated with a 73% reduction in incident HCC (140/296,345 events vs 432/296,198) [HR 0.271 (0.224-0.328)], (NNT=1,015). Notably, the protective effect was most pronounced in non-diabetics [HR 0.179 (0.140-0.229)] and lean patients (BMI < 29) [HR 0.161 (0.103-0.252)]. Risk reductions were sustained across all etiologies, including alcohol liver disease (HR 0.379), cirrhosis (HR 0.456), chronic viral hepatitis (HR 0.477), and MASLD (HR 0.605). GLP-1RA use was associated with a significant increase in GI adverse events. Conclusions: GLP-1RA use was associated with a 73% reduction in incident HCC, consistent across subgroups. The enhanced benefit in non-diabetic and lean cohorts suggests a direct anti-neoplastic mechanism independent of weight loss or glycemic control. The NNT of 1,015 highlights the substantial public health impact of GLP-1RA therapy in preventing a high-mortality malignancy. These findings warrant prospective validation.

10520 Background: Therapeutic options for breast cancer (BC) prevention for high-risk women remain limited, and not all eligible patients opt for endocrine therapy due to concerns related to adverse events (AEs). GLP1RAs are widely used for obesity and type 2 diabetes mellitus; their role in BC primary prevention (PP) in high-risk women with obesity has not been evaluated. Methods: Using the TriNetX Global Network (150 million patients, 108 organizations), we analyzed de-identified records of high-risk women aged 18–90 years with a BMI ≥ 30 who had health care encounters between January 1, 2000, and January 1, 2025, identified via ICD-10 codes. High risk was defined as at least one of the following: genetic predisposition to BC, family history of BC, atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, or dense breasts. Patients were grouped as having GLP1-RA use or no GLP-1RA use. Patients with a prior history of BC or use of endocrine therapy were excluded. GLP-1RA users were propensity score-matched 1:1 with non-users based on demographics, comorbidities, social determinants of health, lifestyle factors, BMI, HbA1c, and prior breast imaging. Incident BC served as the primary endpoint, with key AEs as secondary measures. Kaplan–Meier analysis and Cox proportional hazards models were utilized to assess outcomes, which were further validated through subgroup and sensitivity analyses. Results: Among 80,480 high-risk women with a BMI ≥ 30, 46,581 were assigned to each cohort. Baseline demographics were balanced between cohorts (mean age: 46 years, 70% White, 21% Black). Median follow-up was 2,790 vs 2,630 days for GLP-1RA users and non-users, respectively. BC incidence was 2.95% in GLP-1RA users (1,164/39,495 cases) vs 3.01% in non-users (1,200/39,057 cases) (3.27 vs. 3.57 cases per 1,000 person-years; HR 0.844; 95% CI, 0.779–0.915). GLP-1RA users exhibited an increased risk of endometrial cancer (HR 1.273; 95% CI, 1.088–1.491) and osteoporosis (HR 1.124; 95% CI, 1.054–1.199). No significant association was observed for venous thromboembolism. Gastrointestinal AEs were significantly higher in the GLP-1RA cohort. Conclusions: GLP-1RA use was associated with a modest reduction in BC incidence among high-risk women with obesity in this real-world study. Prospective randomized trials are needed to validate these associations.

10507 Background: Despite advances in understanding leukemogenesis, no validated primary prevention strategies exist. Obesity is a dose-dependent risk factor for leukemia. Emerging data implicate epigenetic regulators, specifically the histone methyltransferase GLP (EHMT1), as a driver of leukemic survival; its inhibition induces cell death in CLL and promotes differentiation in AML. We present the first real-world analysis evaluating GLP-1 receptor agonists (GLP-1RA) for the primary prevention of leukemia in high-risk populations. Methods: Using the TriNetX global research network (150 million patients across 108 healthcare organizations), we identified adults at elevated leukemia risk based on ≥1 factor (prior chemo/radiation, MDS, MPN, family history, genetic syndromes, tobacco use, or BMI ≥30). Patients with ≥2 months of GLP-1RA use were propensity-matched 1:1 to non-users by demographics, comorbidities, and prior chemotherapy. The primary endpoint was the incidence of ALL, AML, CLL, or CML; secondary endpoints were adverse events related to GLP-1RA. Individuals with pre-existing leukemia were excluded. Cox proportional hazards models and sensitivity analyses were used to assess associations. Sensitivity and subgroup analysis confirmed robustness. Results: Of 426,670 high-risk individuals, 213,335 were matched to each cohort; standardized mean differences were <0.1 for all covariates. Across >1.2 million person-years of follow-up, GLP-1RA use was associated with a 63% risk reduction in incident AML (47/213,300 vs 75/213,261; HR 0.37, 95% CI 0.26–0.53; p < 0.001) and a 50% reduction in ALL (42/213,304 vs 53/213,277; HR 0.50, 95% CI 0.33–0.75; p = 0.001). The protective effect for AML remained significant when restricted to patients with prior chemotherapy exposure and was independent of baseline BMI. No significant reductions were observed for CML or CLL. While GI adverse events were higher in the GLP-1RA cohort, the protective signal was consistent across age and ethnic subgroups. Conclusions: This is the first large-scale study to demonstrate a significant reduction in incident AML and ALL using GLP-1 receptor agonists in high-risk patients. By linking clinical metabolic intervention to the EHMT1 epigenetic pathway, these findings provide a novel, scalable pharmacologic strategy for the primary prevention of acute leukemias, potentially transforming the management of high-risk and obese populations.

Background: Ketamine and esketamine ((es)ketamine) rapidly reduce depressive symptoms and suicidal ideation (SI) in treatment-resistant depression (TRD), but whether early SI improvement during the acute phase of the treatment predicts reduced suicide-associated emergency department (SAED) visits over the longer term remains unclear. Objectives: To examine whether early improvements in SI, measured using item 12 of the Quick Inventory of Depressive Symptomatology – Self Reported (QIDS-SR), following (es)ketamine treatment are associated with SAED visits over 6 months Design: Retrospective cohort study. Methods: Individuals with TRD who had available data on SI measured using the QIDS-SR during the acute phase, as well as data on SAED visits over 6 months, were included. Participants were classified based on changes in SI as resolved, partially improved, or unchanged/worsened using the QIDS-SR item 12 during acute treatment (up to six intravenous (IV) or eight intranasal (IN) treatments) and were followed for SAED visits. Results: Among 96 patients with SI data, 73 (76%) had baseline SI. Following acute-phase treatment, 36 (49%) achieved SI resolution, 14 (19%) partially improved, and 23 (32%) were unchanged/worsened. During the 6-month follow-up, 8 (11%) had post-acute SAED visits. While not statistically significant, patients with resolved SI had lower odds of post-acute ED visits (OR = 0.16, p = 0.12). Kaplan–Meier estimates of SAED visit-free survival across three SI change groups trended toward significance ( p = 0.066), suggesting lower cumulative healthcare (ED) utilization in more favorable change groups. Secondary analysis among 57 patients who received IV ketamine and had baseline SI showed that, after two infusions, 33 (47.2%) demonstrated a reduction in SI. Early SI improvement (⩾50% reduction in SI) was associated with a lower likelihood of any post-treatment SAED visit at 6 months after adjusting for pre-treatment SAED (OR = 0.17, 95% CI: 0.02–0.98, p = 0.047), corresponding to numbers needed to treat of 4.3. Conclusion: Early SI changes may have prognostic implications, though larger studies are needed to confirm clinical significance.

Abstract Background Ultra‐high‐field 7 Tesla (7T) magnetic resonance imaging (MRI) provides improved resolution and signal‐to‐noise ratio (SNR) over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce additional challenges such as susceptibility artifacts. Purpose We propose an efficient transformer‐based model (7T‐Restormer) to synthesize 7T‐like MRI (quantitative T1 MP2RAGE maps) from routine 1.5T or 3T T1‐weighted (T1W) images. Methods The proposed method leverages an efficient restoration transformer backbone and spatial attention layers to capture long‐range dependencies and generate high‐quality 7T‐like images. Our model was validated on an institutional dataset, comprised of 35 1.5T and 108 3T T1w MRI paired with corresponding 7T T1 maps of patients with confirmed multiple sclerosis (MS). A total of 141 patient cases (32 128 slices) were randomly divided into 105 (25 1.5T and 80 3T) training cases (19 204 slices), 19 (5 1.5T and 14 3T) validation cases (3476 slices), and 17 (5 1.5T and 12 3T) test cases (3145 slices). The synthetic 7T T1 maps were evaluated by comparing their similarity to the ground truth volumes using peak signal‐to‐noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean squared error (NMSE), and were compared against ResViT and ResShift. In addition, a blinded reader study was performed in which three clinicians scored the diagnostic image quality of each method on a 5‐point Likert scale (1 = non‐acceptable, 5 = excellent). Statistical significance ( α = 0.05) was assessed using two‐sided paired t ‐tests with Holm correction for multiple comparisons and Wilcoxon signed‐rank tests with Holm correction for reader scores. Effect sizes (Cohen's for paired data) were also computed to quantify practical significance. We interpreted and as small, medium, and large effects. Results For 1.5T inputs, 7T‐Restormer achieved an NMSE of 0.018 ± 0.003, PSNR of 25.0 ± 0.6 dB, and SSIM of 0.870 ± 0.019; for 3T inputs, the corresponding values were 0.019 ± 0.006, 24.5 ± 1.2 dB, and 0.874 ± 0.027. Across both field strengths, 7T‐Restormer provided the lowest NMSE and highest PSNR and SSIM among the three methods, reducing NMSE by approximately 5% and 25% relative to ResShift and ResViT at 1.5T and by 14% and 24% at 3T, respectively, and increasing PSNR by 0.5–1.5 dB (Holm‐adjusted p < 0.05, paired Cohen's = 1.37–6.84). Training on mixed 1.5T+3T data improved performance for 1.5T inputs compared with 1.5T‐only training (e.g., NMSE 0.018 vs. 0.019; p = 0.001, ), without degrading performance for 3T inputs ( p = 0.630, for NMSE). In the blinded reader study, 7T‐Restormer received higher diagnostic quality scores (3.50 ± 0.28) than ResShift (3.00 ± 0.27) and ResViT (2.33 ± 0.27), corresponding to mean improvements of 0.5–1.2 points on the 5‐point scale (Holm‐adjusted p = 0.014 and 0.004; paired Cohen's and 3.24, respectively). Conclusion We propose a novel method for predicting quantitative 7T MP2RAGE maps from 1.5T and 3T T1W scans with higher quality than existing state‐of‐the‐art methods. Future development and application of our approach may enhance diagnostic accuracy, treatment planning, and facilitate downstream tasks by making the benefits of 7T MRI more accessible to standard clinical workflows.