Citations

Background: Heart transplantation is the definitive treatment of end-stage heart failure and is a complex process involving coordination in procurement, preservation, and transport of a donor organ to a recipient. There are different heart transport methods, including the traditional static methods of Cooler and Ryobi and advanced dynamic methods, including SherpaPak and the Organ Care System (OCS). The aim of the study is to compare the post-transplant outcome of these in patients bridged with Impella 5.5. Method: A retrospective study was conducted between 2020 and 2025 after IRB approval. Patient demographics and clinical data was extracted from the medical record. Cox proportional hazards regression model was applied to identify independent predictors of mortality across 30-day, 90-day, and 1-year intervals. Results: 123 patients were included in the analysis. Age, EF and Race were similar between all groups. The transport method was a significant predictor of 1-year mortality. Use of OCS (HR=0.022, p value <0.05) and SherpaPak (HR=0.066, p value <0.05) was associated with a significant decrease in mortality compared to traditional cooler use. Across 30-day, 90-day, and 1-year intervals, OCS showed the strongest survival benefit, while SherpaPak also demonstrated reduced mortality, but less significant compared to OCS. Conclusion: Transport method is a strong predictor of 1-year post-transplant mortality, with OCS showing the most pronounced effect in reducing the risk of 1-year mortality as well as mortality across 30-day and 90-day intervals. These findings support broader adoption of advanced transport systems in clinical practice to improve post-transplant outcomes.

Background: Acute myocardial infarction (AMI) represents a significant component of cardiovascular disease (CVD) mortality among the young and middle-aged populations of the United States (US). Research Question: To analyze the long-term trends and the impact of the COVID-19 pandemic on AMI-related mortality among the young and middle-aged populations of the US. Methods: Data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) multiple causes of death database were used to analyze death certificates from 1999 to 2023 for AMI-related deaths among the young and middle-aged population (aged 25-64) of the US. Age-adjusted mortality rates (AAMRs) per 100,000 people and associated annual percent changes (APCs) and average APC (AAPCs) were analyzed using Joinpoint regression analysis. Mortality trends were stratified by sex, race/ethnicity, and census region. Results: From 1999 to 2023, there were 970,454 AMI-related deaths among U.S. adults aged 25-64 years. The annual number of AMI-related deaths decreased from 44,040 in 1999 to 31,522 in 2023. The overall AAMR per 100,000 decreased from 31.02 deaths (95% CI, 30.73 to 31.31) in 1999 to 15.29 (95% CI, 15.11 to 15.46) in 2023 (AAPC -2.92%, 95% CI -3.22 to -2.75). The AAMR per 100,000 declined at a faster rate from 31.02 in 1999 to 19.57 in 2010 (1999-2010, APC -4.26), followed by a slower rate from 19.57 in 2010 to 16.67 in 2019 (2010-2019, APC -1.41), The declining trend was disrupted by a transient increase during the COVID-19 pandemic, with a peak AAMR of 19.73 (95% CI, 19.53 to 19.93) in 2021 (2019-2021, APC 8.52). The declining trend resumed from 2021 to 2023, with AAMR decreasing to the lowest levels of 15.29 in 2023 (2021-2023, APC -12.58). Heterogeneity across demographic and regional groups has narrowed during these 25 years. However, they are still prevalent, with men ( figure 1 ), non-Hispanic (NH) Black or African American, NH American Indian or Alaska Native ( figure 2 ), and the residents of the Southern United States ( figure 3 ) having higher mortality rates. Conclusion: Over the past 25 years, AMI-related mortality has declined in the young and middle-aged population of the US, although rates spiked during the COVID-19 pandemic before resuming their decline in 2022. While disparities among demographic and regional groups have narrowed, they still exist, necessitating comprehensive efforts to improve cardiovascular health outcomes.

Background: Arrhythmogenic and dilated cardiomyopathies (ACM/DCM) are associated with adverse cardiovascular outcomes, including sudden death. Artificial intelligence (AI)-enabled electrocardiographic aging algorithms estimate biological age from 12-lead tracings and predict cardiovascular outcomes in the general population. However, their utility in genetic ACM/DCM has not been studied. Methods: Retrospective review of 1,045 genotype-positive ACM/DCM patients was used to identify those with a pathogenic/likely pathogenic variant in ClinGen-classified definitive/strong evidence ACM/DCM-susceptibility genes. Following exclusion of patients without a baseline ECG for analysis (e.g. paced rhythms), the AI-ECG age gap (AI-EAG) was calculated by subtracting chronological from AI-ECG age. Genes were grouped into functional categories: desmosomal ( PKP2, DSP, DSG2, DSC2, JUP ), nuclear envelope ( LMNA ), sarcomeric ( TTN, MYH7, TNNT2 ), cytoskeleton/Z-disc ( FLNC, DES, DMD, BAG3 ), and regulatory/ion channel ( PLN, RBM20, SCN5A ). Cardiac MRI data included left ventricular structure, function, and late gadolinium enhancement (LGE) presence and pattern. Mann-Whitney U was used for group comparisons; results are shown as median (IQR). Results: Overall, 824 patients (52.8% male; median age of 40.7 years, IQR 26.5–53.4; and median AI-EAG of 7.49 years, IQR 0.43–15.26) were included. DES variant-positive patients had the highest (19.98 years, IQR 9.66–23.21) and BAG3 variant-positive patients the lowest (–0.95 years, IQR -6.05–7.61) AI-EAGs. Among gene groups, nuclear envelope had the highest (15.12 years, IQR 6.79–25.17) and sarcomeric the lowest (5.75 years, IQR -0.69-14.01) AI-EAGs. Cardiac MRI was available for 538/824 (65%) of which 233/538 (43.3%) had LGE. No significant difference in AI-EAG was observed between LGE-positive and -negative patients (6.99 vs. 7.94 years; p=0.831). However, several LGE patterns were associated with significantly higher AI-EAGs: subepicardial (9.88 vs. 6.84; p=0.004), transmural (13.83 vs. 7.25; p=0.012), apical (12.89 vs. 7.17; p=0.002), and septal (8.91 vs. 7.19; p=0.016). Conclusion: AI-EAG varies by gene and functional group, possibly reflecting gene-specific myocardial remodeling. While certain LGE patterns were linked to increased biological aging, overall LGE status was not. These findings suggest AI-EAG may capture disease activity that is distinct from LGE and could serve as a complementary, non-invasive biomarker in genetic ACM/DCM.

Background: Renal dysfunction is a known prognostic factor in advanced heart failure and among patients receiving temporary mechanical circulatory support (tMCS). However, the predictive value of post-Impella creatinine in determining healthcare resource utilization in patients bridged to transplant with Impella 5.5 remains unclear. This study aimed to evaluate the association between post-Impella creatinine and key hospitalization metrics in this population. Methods: We performed a retrospective cohort study of patients who received Impella 5.5 as a bridge-to-transplant between January 2020 and January 2025. Serum creatinine was collected 72 hours after Impella placement. The primary outcome was device-to-discharge time. Secondary outcomes included transplant-to-discharge time, post-transplant ICU length of stay (LOS), and total LOS (admission-discharge). Univariate and multivariable linear regressions were used to examine the association between post-Impella creatinine and each outcome, adjusting for age, gender, BMI, and LVEF. Results: 133 patients were supported with the Impella 5.5 as BTT and were included (median age 58 years (51–65), 82.7% were male, and 71.4% presented with non-ischemic cardiomyopathy. The median BMI was 27.7 (24.3–32.3), LVEF 17% (15–22), and post-Impella creatinine 1.32 mg/dL (0.96–1.71). The median device-to-discharge time was 45 days (29-64), transplant-to-discharge time was 14 days (12–19), ICU LOS post-transplant was 6 days (4–8), and total LOS was 58 days (42–76). Higher post-Impella creatinine was significantly associated with longer device-to-discharge time (β = 6.67, p = 0.004), longer transplant-to-discharge duration (β = 3.42 p = 0.003), longer ICU LOS (β = 2.19, p = 0.007), and longer total LOS (β = 7.24, p = 0.002) on univariate analysis. Post-impella creatinine remained significantly associated with device-to-discharge time in the multivariate model after adjusting for confounders (β = 6.33, p = 0.006). Importantly, this suggests that patients with lower post-Impella creatinine levels may experience shorter hospitalizations and faster recovery trajectories following transplant. Conclusions: Post-Impella creatinine is a significant predictor of prolonged hospitalization in patients supported with Impella 5.5 as a bridge to transplant. These findings emphasize the prognostic importance of early renal function assessment and may guide risk stratification and resource planning in advanced heart failure care.

Introduction: Heart failure (HF) affects interstitial lung structure and function. AI-assisted quantitative computed tomography (qCT) offers possibility of objective assesment of lung structure, allowing to detect the presence and the severity of HF. Hypothesis: Can automated qCT analysis discriminate HF from controls and identify tissue structures most linked to degree of congestion ? Methods: Subjects underwent right heart catheterization (RHC), native CT chest imaging (full inspiration/expiration) by Naeotom-α photon-counting CT scanner (Siemens), lab testing, echocardiography. Automated AI-based analysis (VIDA Diagnostics) was employed to evaluate lung volumes, densities and tissue texture. Image series were used in mediastinal and lung window reconstruction with slice thickness 0,8 mm and increments 0,5 mm. Results: 186 HF patients (85% HFrEF, NYHA 2.8±0.5, 58 y, 80% males, NTproBNP 4491 pg/ml, LVEF 26%) and 43 controls of similar sex and BMI were analyzed; both groups free of primary lung disease. In HF, 85 % had PH (mPAP>20mmHg). HF patients had comparable inspiratory lung volume, reduced air volume and increased lung tissue volume, compared to controls. Mean lung density (-782±50 vs -832±25 HU, p<0.0001), density variability and estimated lung fluid content (21.3 vs 16.7%, p<0.0001) were all higher in HF compared to controls. Across various density cut-offs, the most notable difference was at lung tissue density < -856 HU at inspiration. Lung tissue density corelated with mean PA pressure (r=0.49, p<0.0001), and less with pulmonary vascular resistance (r=0.21, p=0.006). Insp/exp scan analysis showed no difference in air trapping, but reduced lung tissue compliance (Jacobian strain: 1.8±0.4 vs 1.6±0.3, p=0.0005) in HF. Lung texture analysis showed increased ground-glass opacity (GGO) mass (48.8 g vs 9.1 g; p < 0.001), reticulation (42.2 g vs. 8.4 g; p < 0.001) and consolidation (0.5 g vs 0.2 g; p=0.0011) in HF compared to controls, with no difference in honeycombing. GGO mass correlated strongly with pulmonary capillary wedge pressure (PCWP) (r=0.48, p<0.001) and mitral regurgitation grade (r=0.28,<0.0001), but not with inflammation (hsCRP, IL6, WBC), smoking exposure or oncotic pressure. Conclusions: qCT distinguished HF patients from controls by increased lung tissue mass, reduced air volume, increased lung density and increased mass of GGO and reticulation. GGO mass in HF strongly reflects increased hydrostatic pressure, but not inflammation.

Background: Chronic Achilles tendon ruptures (CATRs) pose a clinical challenge because guidelines on optimal treatment modalities are lacking. This meta-analysis aims to investigate the use of Flexor Hallucis Longus (FHL) tendon transfer as a treatment option. Methods: A literature search was performed across multiple databases from inception until 31 July 2025. The databases searched included Ovid MEDLINE®, EMBASE (Elsevier), Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews. Included studies presented CATR patients of all ages, with no previous surgeries to the ankle, who were managed with an FHL tendon transfer (PROSPERO ID: CRD42023489724). Results: Sixteen studies met the eligibility criteria with 323 patients. For functionality, baseline AOFAS-AH (American Orthopaedic Foot & Ankle Society—Ankle Hindfoot) scores were 56.85 (95% CI: 51.03–62.68, I2 = 96%). At ≥12 months post-operative follow-up, AOFAS-AH scores were 91.46 (95% CI: 88.45, 94.48, I2 = 93%). ATRS (Achilles Tendon Rupture Score) at baseline was reported as 31.04 (95% CI: 5.80, 56.28, I2 = 99%). At ≥12 months post-operative follow-up, ATRS amounted to 90.73 (95% CI: 83.69, 97.77, I2 = 89%). Overall complication rates were 7.5% (CI: 0.04,0.11, I2 = 40%), consisting of superficial infections at 4.2% (95% CI: 0.01, 0.07, I2 = 0%), activity limitations at 4% (95% CI: 0.01, 0.08, I2 = 0%) and disturbed wound healing at 3.8% (95% CI: 0.01, 0.06, I2 = 0%). The minimum clinically important difference (MCID) for ATRS was achieved at 12 months onwards. Conclusions: Surgical management of CATR patients with FHL tendon transfer appears to improve functionality and subjective outcomes, supporting its use amongst the treatment modalities available.

Abstract Understanding tumor cell dynamics can improve prognosis and treatment but remains limited for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA sequencing data from 684 NS-LUAD cases and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histologic data further characterized the subtypes. “Steady,” marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver gene alterations, is linked to prolonged survival and low immune evasion. “Proliferative” shows high proliferation markers, TP53 mutations, and gene fusions. “Chaotic,” with high epithelial-to-mesenchymal transition markers, has the worst prognosis, even within stage I tumors. Lacking known molecular or histologic characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the classification and predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving early-stage NS-LUAD prognostication in clinical settings. Significance: The transcriptome of 684 NS-LUAD identifies three subtypes with different cellular dynamics and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a potential clinically applicable tool for treatment decision-making in patients with NS-LUAD. See related commentary by Azizi et al., p. 423

Abstract INTRODUCTION M0 images were missing in Siemens ASL data in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, prohibiting cerebral blood flow (CBF) quantification. METHODS A conditional latent diffusion model was trained and evaluated on in‐house datasets, then applied to the Siemens data in ADNI‐3. Regional CBF differences by Alzheimer's disease (AD) stages, their accuracy for AD classification, and CBF trajectory slopes were compared between generated data (Siemens) and acquired data (General Electric). RESULTS The diffusion model generated M0 images with high fidelity (SSIM = 0.918 ± 0.023, PSNR = 31.361 ± 2.537) and minimal CBF bias (mean difference is 0.21 ± 1.58 mL/100 g/min). Both generated and acquired CBF showed similar spatial patterns and decreasing trends with AD progression in specific AD‐related regions. Generated CBF also improved accuracy in classifying AD stages compared to qualitative perfusion images. CONCLUSION This study shows the potential of diffusion models for imputing missing modalities in large‐scale studies exploring the use of ASL as a biomarker of AD. Highlights Using latent diffusion model, we can generate M0 image from control image in arterial spin labeling (ASL) with high fidelity. The generated M0 can be used for cerebral blood flow (CBF) quantification in Alzheimer's Disease Neuroimaging Initiative dataset. The performance of classification between Alzheimer's disease (AD) patients and cognitive normal people is better when using generated CBF maps than using non‐quantitative perfusion images. ASL CBF decreases with AD progression in key AD‐related brain regions.

Abstract Purpose: Mouse models demonstrate a role for RANK and its ligand, RANKL, in osteosarcoma. The primary objective of this single-arm, open-label phase 2 trial was to determine whether denosumab, a RANKL mAb, improved disease control in recurrent osteosarcoma relative to benchmarks derived from historic Children’s Oncology Group clinical trial data. Patients and Methods: Skeletally mature patients ages 11 to 49 years old with measurable disease were eligible for cohort 1, and those with complete surgical resection of all sites of disease were eligible for cohort 2. Patients received denosumab 120 mg subcutaneously every 4 weeks with calcium and vitamin D supplementation. The primary endpoints were RECIST response and remaining event-free for 4 months for cohort 1 and remaining event-free for 12 months for cohort 2. Toxicity, pharmacokinetics, and pharmacodynamic effects were additional endpoints. Results: Fifteen patients in cohort 1 and 38 in cohort 2 were eligible and evaluable for the primary endpoint. One of 15 cohort 1 patients remained event-free at 4 months. There were no objective responses. Ten of 38 cohort 2 patients were event-free at 12 months. The predefined efficacy criteria were not met in either cohort. The most common ≥ grade 3 adverse events were hypocalcemia and hypophosphatemia (8% and 11%, respectively). At steady state, mean serum denosumab trough concentrations were 23.7 to 31 μg/mL in cycles 2 to 7. Serum c-telopeptide and urine n-telopeptide decreased on treatment. Conclusions: Denosumab was well-tolerated with anticipated side effects and pharmacokinetic and pharmacodynamic parameters but had insufficient activity for further development in osteosarcoma.