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ImportanceHospital ratings including the US News & World Report’s Best Hospitals rankings and the Centers for Medicare & Medicaid Services’ (CMS’) Overall Hospital Quality Star Rating (Overall Star Rating) measure different outcomes and are weakly correlated. Therefore, methods for defining and measuring reliable excellence, defined as consistently great performance across all quality measures, are needed.ObjectiveTo assess a measure of reliable excellence using the 45 quality measures reported in the Overall Star Ratings.Design, Setting, and ParticipantsThis cross-sectional study used hospital-level data from the 2023 and 2024 CMS Overall Star Ratings at all US hospitals with a 2023 and 2024 CMS Overall Star Rating.ExposuresThe exposure was the CMS Overall Star Rating summary score, a continuous variable calculated from the weighted z scores of 45 quality measures used in the Overall Star Rating. A total of 100 000 simulations were run in which all US hospitals’ CMS Overall Star Rating summary scores were calculated through summation of z scores from randomly generated measure weights, as opposed to the existing weights used in the Overall Star Rating method.Main Outcomes and MeasuresReliable excellence, defined as achieving a 90th percentile (or better) CMS Overall Star Rating summary score on at least 50 000 of 100 000 simulations. The percentage of hospitals achieving reliable excellence was calculated both overall and stratified by CMS Ovearll Star Ratings.ResultsThere were 2700 hospitals in the analysis, with 335 5-star hospitals (12.4%), 727 4-star hospitals (26.9%), 799 3-star hospitals (29.6%), 572 2-star hospitals (21.2%), and 267 1-star hospitals (9.9%) in the 2024 CMS Overall Star Rating. A total of 244 of 2700 hospitals (9.0%) met the study definition of reliable excellence, whereas 1287 of 2700 hospitals (47.7%) achieved excellence in at least 1 simulation.Conclusions and RelevanceThis cross-sectional study of 2700 US hospitals found that only 244 hospitals (9.0%), including less than two-thirds of the CMS 5-star rated hospitals, were reliably excellent across 100 000 CMS Overall Star Rating scoring simulations using random measure weightings. These findings lend credence to the ubiquity of inconsistent greatness in health care quality and illuminate the need for methods to distinguish hospitals that provide reliably excellent care.

Abstract Background Cisplatin, gemcitabine, and durvalumab combination is a standard first-line treatment for advanced biliary tract cancer. This study aimed to assess the impact of genetic alterations on outcomes in patients with advanced biliary tract cancer treated with cisplatin, gemcitabine, and durvalumab in real-world clinical practice. Methods Patients with unresectable, locally advanced, or metastatic biliary tract cancer treated with cisplatin and gemcitabine plus durvalumab across 39 centers in 11 countries in Europe, the United States, and Asia were included in this analysis. Results The cohort included 513 patients with advanced biliary tract cancer. The 5 most frequently altered genes were TP53 (22.1%), KRAS (13.7%), CDKN2A/B (13.6%), ARID1A (12.2%), and IDH1 (9.2%). In multivariate analysis, SMAD4 mutations were associated with improved progression-free survival (PFS) (hazard ratio [HR] = 0.49, P = .018) and overall survival (HR = 0.11, P = .023), while TP53 mutations were linked to worse PFS (HR = 1.62, P = .0047) and TERT mutations to worse overall survival (HR = 8.92, P = .0012). No other genomic alterations were statistically associated with outcomes. Subgroup analysis showed that TP53 mutations negatively affected PFS and overall survival in intrahepatic cholangiocarcinoma, while KRAS mutations were associated with poorer PFS in extrahepatic cholangiocarcinoma. No gene alterations were linked to outcomes in gallbladder cancer. Conclusions This large-scale analysis, with comprehensive molecular profiling, supports the positive prognostic impact of SMAD4 mutations for PFS and overall survival and highlights the negative prognostic roles of TP53 (PFS) and TERT (overall survival) mutations, providing valuable insights for personalized treatment strategies in biliary tract cancer.

Subjective and objective limitations to exercise and activity are hallmarks of heart failure (HF), regardless of underlying ejection fraction (EF). These limitations relate to cardiovascular abnormalities involving the systolic and diastolic properties of the heart, venous, and arterial vasculature, as well as noncardiovascular abnormalities, including impairments in pulmonary function, autonomic regulation, anemia, metabolism, and changes in mitochondria and skeletal muscle. The contribution of these abnormalities varies between patients with HF with preserved EF and those with HF with reduced EF, but, even within each HF subtype, there is substantial individual patient pathophysiologic variability, which suggests a potentially important role for phenotyping based on exercise reserve responses to individualize treatment. In this article, we review the current understanding of exercise reserve limitation with a focus on specific organ systems involved, both in patients with HF with preserved EF and HF with reduced EF, and how these interact to lead to symptoms of exercise intolerance and objective limitations in submaximal and peak aerobic capacity across the spectrum of HF.

Three-dimensional radiomic analysis of digital breast tomosynthesis outperformed two-dimensional measures in breast cancer risk assessment.

Abstract Background Low-density lipoprotein cholesterol (LDL-C) is directly associated with coronary artery disease (CAD) risk. Subfractionation of LDL enables differentiation between large-buoyant LDL (>20.5 nm) and small-dense LDL (≤20.5 nm). Small-dense LDL reportedly increases CAD risk, as do LDL-C and LDL particle (LDL-P) concentrations. Nuclear magnetic resonance spectroscopy (NMR) reports LDL-C, LDL-P, and LDL size (LDL-s). We investigated associations between these outputs and their agreement on CAD risk information. Methods Associations between LDL-P, LDL-C, and LDL-s measured by NMR were evaluated in serum from clinically ordered samples (n = 26 710), and a subset of patients with CAD evaluation from coronary angiography (n = 356). Correlations were determined using Spearman ρ, and clinical classifications were compared using the following thresholds for increased risk: LDL-C > 160 mg/dL, LDL-P > 1600 nmol/L, and LDL-S < 20.5 nm. Results The large laboratory NMR data set showed LDL-C was highly correlated with LDL-P (ρ = 0.87), and moderately with LDL-s (ρ = 0.51). Correlation between LDL-P and LDL-s was weakest (ρ = 0.21). When comparing pairwise high- and low-risk laboratory values, concordant values were observed in 99.8%, 43%, and 25% of cases for LDL-P/LDL-C, LDL-s/LDL-P, and LDL-C/LDL-s, respectively. In patients with angiography and NMR results, CAD was diagnosed in 40% (6/15) of patients with concordant high-risk LDL-C and small-dense LDL-s in the smaller patient cohort, but only 19% (6/31) of CAD-positive patients with high-risk LDL-C had small-dense LDL-s. Conclusions LDL-s and LDL-C are frequently discordant at established LDL-C risk cutoffs. CAD diagnosis was found in similar numbers regardless of LDL-s phenotype.

Purpose To develop an expert consensus statement on the diagnosis, management, and rehabilitation of medial meniscal root tears (MMRTs) using a modified Delphi technique. Methods A working group developed statements on MMRT diagnosis, nonoperative management, surgical indications, surgical management, alignment, and rehabilitation using modified Delphi techniques. Fifty‐six experts were surveyed over 3 rounds to reach consensus, with agreement measured on a 5‐point Likert scale. Statements were included, revised, or excluded on the basis of predefined thresholds (≥75% agreement, <20% disagreement). Experts suggested revisions or new statements in the first 2 rounds, and final consensus statements were included. Results All 56 experts completed 3 survey rounds. Experts agreed that root tears may occur with no known history of trauma, typically in older patients, and that it should be diagnosed with an magnetic resonance imaging. In symptomatic patients with MMRTs without advanced osteoarthritis should be repaired using an anatomic transtibial pull‐out technique (performing a pie‐crusting technique can be helpful for visualization). Nonoperative management is advised for patients with advanced osteoarthritis. High tibial osteotomy may be considered for significant varus malalignment during MMRT repair. The only statement without consensus was the management of asymptomatic MMRTs with mild medial compartment cartilage wear, indicating ongoing debate. Conclusions Overall, 98% of statements reached consensus. There is agreement that magnetic resonance imaging is the gold standard for diagnosis. Symptomatic MMRTs without advanced osteoarthritis should be repaired early using an anatomic transtibial pull‐out technique. End‐stage knee osteoarthritis warrants nonoperative management of MMRTs, and a structured postoperative protocol with limited weightbearing and range of motion is essential after repair. No agreement was reached on managing asymptomatic MMRTs in patients without significant medial compartment degeneration. Meniscal centralization sutures may help in cases of substantial extrusion, but their routine use is debated. Level of Evidence Level V, consensus of expert opinion.

Oncogene expression can cause replication stress (RS), leading to DNA double-strand breaks (DSBs) that require repair through pathways such as homologous recombination, nonhomologous end-joining, and microhomology-mediated end-joining (MMEJ). Cyclin D1 (encoded by CCND1 ) is a well-known oncoprotein overexpressed in cancer; however, its role in RS is unknown. Using mantle cell lymphoma (MCL) as a naturally occurring model of cyclin D1 overexpression, we examined the impact of cyclin D1 on RS and DSB repair mechanisms. Cyclin D1 overexpression elevated RS, increased DNA damage, especially during mitosis, and caused specific upregulation of MMEJ. Furthermore, cyclin D1 activated polymerase theta ( POLQ ) transcription by binding its promoter loci, driving POLΘ-mediated MMEJ that is essential to withstand cyclin D1–induced RS. Moreover, concurrent ATM deficiency further intensified RS, enhanced POLQ expression, and heightened reliance on MMEJ-mediated DNA damage repair. Consequently, inhibition of POLΘ in cyclin D1–overexpressed settings further exacerbated RS, causing single-strand DNA gap accumulations and chromosomal instability, ultimately leading to apoptosis, an effect amplified in ATM-deficient cells. Targeting MMEJ via POLΘ inhibition is therefore an effective strategy in the context of cyclin D1 overexpression and ATM deficiency and may provide a unique therapeutic approach for treating MCL and other malignancies characterized by similar alterations.

Importance Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin–stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important. Objective To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods. Design, Setting, and Participants This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditional pathologist-read methods and an artificial intelligence (AI)-driven approach. The study was conducted using retrospective cohorts of patients with melanoma between January 2022 and June 2023 across 45 institutions, with tissue evaluated by participants from academic, clinical, and research institutions. Participants were selected to ensure diverse expertise and professional backgrounds. Main Outcomes and Measures Intraclass correlation coefficient (ICC) values were calculated for the manual and AI-assisted arms using log-transformed data. Kendall W values were calculated for Clark scores (brisk = 3, nonbrisk = 2, and sparse = 1). Reliabilities of ICC and W values were classified as moderate (0.40-0.60), good (0.61-0.80), or excellent (&amp;gt;0.80). AI TIL measurements were dichotomized using the 16.6 and median cutoffs. Univariable and multivariable Cox regression analyses assessed the prognostic value of TIL scores adjusted for clinicopathologic variables. Results There were 111 patients with melanoma in the independent testing cohort (median [range] age at diagnosis, 61.0 [25.0-87.0] years; 56 [50.5%] male) who contributed melanoma whole tissue sections. A total of 98 participants evaluated TILs on 60 hematoxylin and eosin–stained melanoma tissue sections. All 40 participants in the manual arm were pathologists, while the AI-assisted arm included 11 pathologists and 47 nonpathologists (scientists). The AI algorithm demonstrated superior reproducibility, with ICCs higher than 0.90 for all machine learning TIL variables, significantly outperforming manual assessments (ICC, 0.61 for AI-derived stromal TILs vs Kendall W , 0.44 for manual Clark TIL scoring). AI-based TIL scores showed prognostic associations with patient outcomes (n = 111) using the median cutoff approach with a hazard ratio (HR) of 0.45 (95% CI, 0.26-0.80; P = .005), and using the cutoff of 16.6, with an HR of 0.56 (95% CI, 0.32-0.98; P = .04). Conclusions and Relevance In this prognostic study of TIL quantification in melanoma, the AI algorithm demonstrated superior reproducibility and prognostic associations compared with traditional methods. Although the retrospective nature of the cohorts limits demonstration of clinical utility, the publicly available dataset and open-source AI tool offer a foundation for future validation and integration into melanoma management.

Objectives: Breast cancer (BC) remains a critical public health issue where early detection significantly improves outcomes. Despite advancements, disparities in screening awareness and access persist, particularly in underserved populations. This study evaluates a comprehensive, technology-driven educational campaign designed to empower individuals to advocate for their breast health, bridging gaps in knowledge and accessibility. Methods: Between 10/1/22 and 12/2/22, a multiplatform campaign was conducted with IRB approval. The initiative utilized traditional media, including televised ads and educational videos, and digital tools such as a mobile app and website in English and Spanish. Central to this campaign was an interactive risk calculator, offering personalized BC screening recommendations. Data collection included user demographics, platform engagement metrics, and the identification of high-risk individuals. A cost-effectiveness analysis was conducted using campaign budget data. Results: The campaign reached 673,920 individuals through televised ads and 152,672 impressions by digital ads. The website garnered 930 unique impressions, while the app recorded 2752 downloads across 131 countries. The risk calculator was completed 637 times, identifying 72 high-risk individuals. Follow-up data revealed ongoing engagement, with the calculator used an additional 1468 times. The cost per conversion was $1.62, and the cost to identify a high-risk individual was $209.27, demonstrating remarkable cost-efficiency. Conclusions: This campaign successfully increased BC awareness and early detection efforts, leveraging a cost-effective, multiplatform approach. The integration of personalized tools like the risk calculator underscores the potential of digital interventions in health education. Future efforts should build on this model to further enhance reach and health outcomes.

ABSTRACT Aging is a prominent risk factor for heart disease, driving pathological cardiac changes such as hypertrophy, fibrosis, and cellular senescence. While BubR1 has been linked to systemic aging in mammalian models, its specific role in regulating cardiac aging remains unclear. Here, we investigated how BubR1 regulates heart aging and its potential contribution to the pathogenesis of cardiac disease, including heart failure. BubR1 insufficiency in mice resulted in marked cardiac hypertrophy, increased fibrosis, and elevated markers of cellular senescence. Transcriptomic profiling revealed widespread disruption in key pathways involved in cardiac function, including ion channel regulation, cytoskeletal organization, and contractile fiber dynamics. Comparative analysis with aged hearts demonstrated shared dysregulated gene networks, linking BubR1 deficiency to age‐related cardiac dysfunction. Additionally, BubR1 hypomorphic hearts mirrored transcriptomic changes observed in end‐stage heart failure patients, and BubR1 protein levels were found to decline with age in the heart and were also significantly reduced in rodent models of heart failure and in heart failure patients. BubR1 reduction in cardiomyocytes in vitro led to an increased expression of markers of heart failure, hypertrophy, and cytoskeletal remodeling, underscoring an essential and direct role of BubR1 in maintaining cardiomyocyte health. Overall, our data suggest that BubR1 deficiency is a feature of cardiac aging and disease in humans, and that sustaining BubR1 expression may offer a potential therapeutic strategy to mitigate age‐associated cardiac decline and improve heart health in the elderly.