Citations

Lay Summary This multicenter study evaluated clinical outcomes in pregnancy for women with ulcerative colitis and an ileal pouch-anal anastomosis. Close monitoring is needed with a multidisciplinary team for management of inflammatory complications of the pouch such as pouchitis in pregnancy and postpartum.

Abstract Aims Heart failure (HF) with preserved (HFpEF) and mildly reduced (HFmrEF) ejection fraction are prevalent, yet frequently underdiagnosed syndromes associated with high morbidity and mortality, impaired quality of life, and escalating healthcare expenditures. Although guideline-directed medications like SGLT2 inhibitors have been shown to reduce the risk of hospitalization and cardiovascular death, their use remains limited and substantial residual risk persists. This trial aims to evaluate the safety and performance of a novel left-atrium-to-coronary-sinus shunt (Edwards APTURE transcatheter shunt system) in HFpEF and HFmrEF patients. Methods ALT-FLOW II is a prospective multi-centre, randomized, sham-controlled, double-blinded (patient and assessor) trial. Approximately 100 symptomatic HF patients aged ≥18 years with left ventricular ejection fraction >40% and exercise pulmonary capillary wedge pressure (PCWP) ≥25 mm Hg with a PCWP to right atrial pressure gradient ≥8 mm Hg will be randomized 1:1 to the APTURE shunt vs sham control. Key exclusion criteria include severe HF, significant valvular disease, and more than mild right ventricular dysfunction. The primary endpoints are the safety of the APTURE device at 30 days and change in workload-corrected PCWP normalized to bodyweight at 6 months. Secondary endpoints include changes in patient-reported outcomes, and hemodynamic and echocardiographic parameters through 5 years. The trial will also explore the impact of the device on short-term cardiac remodelling and intra-cardiac flow patterns using multi-modality imaging. Conclusions The ALT-FLOW II trial will evaluate the safety and performance of the APTURE system in symptomatic HFpEF and HFmrEF patients with elevated left atrial pressure.

Abstract Introduction Cardiovascular disease (CVD) is the leading cause of death among patients with kidney failure on dialysis. Social determinants of health may worsen this risk but are seldom incorporated into prognostic models. ICD-10 Z-codes provide standardized documentation of social determinants of health, yet their prognostic value in dialysis populations remains uncertain. This study examined whether Z-coded social determinants of health are associated with adverse cardiovascular outcomes and mortality among patients receiving dialysis for kidney failure. Methods A retrospective cohort study was conducted using the TriNetX Research Network (2010–2024), encompassing de-identified data from 103 institutions. Adults with kidney failure on chronic dialysis were stratified by the presence of ICD-10 Z-codes (Z55–Z65). Propensity score matching (1:1) balanced demographics, comorbidities, medications, and laboratory values. Primary outcomes were all-cause mortality and hospitalization; secondary outcomes included acute heart failure, myocardial infarction, stroke, cardiac arrest, bradyarrhythmias, and ventricular tachycardia. Results After matching, mean age was 62 years, and 42.4% were female in the Z-code cohort versus 41.2% in controls. Over one year, mortality occurred in 12.5% versus 10.9% (hazard ratio [HR], 1.22; 95% confidence interval [CI], 1.15–1.29) and all-cause hospitalizations in 57.3% versus 53.1% (HR, 1.22; 95% CI, 1.19–1.26). Cardiovascular complications were consistently higher in Z-coded patients, including heart failure (24.3% vs 20.5%; HR, 1.29), myocardial infarction (8.0% vs 7.1%; HR, 1.19), stroke (6.6% vs 6.2%; HR, 1.13), cardiac arrest (3.8% vs 3.1%; HR, 1.29), and bradyarrhythmias (6.9% vs 5.5%; HR, 1.33). Discussion Among patients with kidney failure, documented Z-coded social risk factors were associated with greater mortality and cardiovascular morbidity. Incorporating social determinants of health documentation into nephrology care may improve risk stratification and inform targeted interventions.

Abstract Introduction Cannabidiol has been shown to exert significant anti-inflammatory effects and has demonstrated efficacy in murine models of autoimmune myocarditis, pericarditis, and heart failure. The ARCHER Study assessed whether a pharmaceutically produced cannabidiol formulation showed beneficial effects on cardiac magnetic resonance (CMR) endpoints known to predict prognosis in this patient population. Methods In a multicentre international double-blind placebo-controlled phase 2 study, we randomly assigned 109 patients within 10 days of CMR confirmed diagnosis of acute myocarditis to 12 weeks of pharmaceutically produced oral cannabidiol (active) or placebo. Dose was titrated up to 10 mg/kg of body weight twice daily. Primary endpoints were the difference in extracellular volume (ECV) and global longitudinal strain (GLS) measured by CMR at week 12. Other CMR endpoints included left-ventricular ejection fraction (LVEF), LV mass, intracellular volume (ICV), LV end-diastolic and end-systolic volumes (LVEDV, LVESV), and left-atrial end-systolic volume (LAESV). Results All randomized patients (56 active/53 placebo) completed the study with no loss to follow-up. Study drug appeared safe and well tolerated. Baseline mean ECV 38.9 ± 10.9 ml, GLS −15.3 ± 3.6%, and LVEF 60.6 ± 9.9% were consistent with mild to moderate myocarditis and predominantly intact LV function. Week 12 mean ECV was 33.6 ml in the active group and 37.3 ml in the placebo group, a difference of −3.7 ml, confidence interval (CI): −7.4 to 0.1; P = .0538; GLS was −16.0% in the active group and −15.9% in the placebo group, difference of −0.1, CI: −1.2 to 1.1; P = .90. Left ventricular mass was significantly reduced in the active group at 121.1 g compared to placebo 130.3 g, a difference of −9.2, CI: −16.4 to −2.1; P = .0117. In terms of remodelling, LAESV was significantly reduced in the active group (−8.1 ml; P = .0376) while the reduction in LVEDV failed to reach significance (−7.4 ml; P = .098). Conclusion In mild-to-moderate acute myocarditis, treatment with pharmaceutically manufactured cannabidiol was not associated with a statistically significant change in myocardial ECV or GLS, although a trend towards reduction in ECV was observed. In addition, improvement in other potential markers of myocardial recovery, including a significant reduction in LV mass, was seen in the active treatment group. Further investigation of the therapeutic potential of this therapy in inflammatory cardiac conditions is warranted.

Abstract Background Bedaquiline, pretomanid, and linezolid with or without moxifloxacin (BPaL/M) are recommended oral 6-month treatment regimens for multidrug- or rifampin-resistant (MDR/RR) tuberculosis (TB). Since the US rollout of these regimens in 2019, the US Centers for Disease Control and Prevention (CDC) and partners have identified patients who failed or relapsed on these regimens. Methods Here, we report a case series of US patients with TB treated with BPaL/M-containing regimens, who experienced adverse outcomes during the period 2022‒2024, including drug resistance, relapse, and treatment failure. Results Clinical and public health outcomes were significant for US patients reported. There were 8 patients identified (n = 8). 5 (62.5%) were male, with a median age 57 years, 2 (25%) were previously treated for TB, and 8 (100%) presented with cavitary disease. This included a patient who died from infectious TB with acquired resistance after exposing over 100 healthcare workers, a waitress who was found to have highly infectious TB at the time of her relapse, and a son who contracted Mycobacterium tuberculosis (Mtb) with reduced activity to bedaquiline from his mother in a household transmission event. Conclusions These patients highlight consequences, both for the individual and public health, of relapse and treatment failure in real-life operational settings that may not be readily evident in well-controlled and well-resourced clinical trials. Despite the advent of shorter and better tolerated bedaquiline-based regimens, US clinicians continue to face challenges in managing drug-resistant TB. These data support the need for expert management of these patients beyond routine TB care, as well as the need for close monitoring and follow-up months after treatment completion.

Abstract Background People living with HIV (PLHIV) are at increased risk of atherosclerotic cardiovascular disease (ASCVD), but the immunological mechanisms driving plaque formation remain unclear. This study investigated the association between peripheral immune cell subsets and carotid atherosclerotic plaques in PLHIV without prior clinical ASCVD. Methods In this multi-center cross-sectional study, virally suppressed PLHIV receiving antiretroviral therapy were enrolled from two Dutch cohorts: a discovery cohort (n = 994) and a validation cohort (n = 200). Participants underwent carotid ultrasound imaging to assess plaques using standardized criteria. Immune profiling was performed using high-dimensional flow cytometry of 355 immune cell populations. Associations with plaque were analyzed using linear regression adjusted for relevant confounders, and key findings were validated in the second cohort. Transcriptomic profiles of main cell populations were evaluated using deconvoluted bulk RNA sequencing to identify differential expression and pathway enrichment. Results Carotid plaques were present in 584 participants (49%)—502 of 994 (51%) in the discovery and 82 of 200 (41%) in the validation cohort. Plaques were associated with higher counts of several CD8+ T cell subsets, particularly PD-1-expressing cytotoxic T cells with an interferon secretion profile (CD8TC1PD1+). Transcriptomic analysis of CD8+ T cells revealed downregulated mitochondrial function and upregulated type 1 interferon and epidermal growth factor receptor signaling, indicating a senescent phenotype. Conclusions CD8+ T cell senescence may contribute to early atherosclerotic plaque formation in PLHIV. Targeting immune senescence could offer a novel strategy for cardiovascular risk reduction in this population. Clinical Trials Registration ClinicalTrials.gov Identifier: NCT03994835

Abstract Background There is growing interest in artificial intelligence (AI) models for predicting future breast cancer. We performed a systematic review of studies of mammography-based AI models for future breast cancer risk prediction to summarize current evidence, identify knowledge gaps, and inform future research directions. Methods We searched 6 databases for studies from January 1, 2012, to February 28, 2025, that evaluated mammography-based AI models for future breast cancer risk prediction. We extracted study design, participants’ race and ethnicity, geographic origin, mammogram type, vendor, prediction time frame, breast cancer type predicted, external validation, and exclusion of cancers diagnosed on the index screening mammogram. Areas under the receiver operating curve (AUCs) were summarized overall and by study characteristics. Results A total of 41 studies met our inclusion criteria. All studies were retrospective, and most used 2D mammograms (n = 37 studies) acquired using Hologic equipment (n = 25) and performed in the United States (n = 17); White, non-Hispanic women were most represented. Nearly all (n = 40) studies assessed discrimination performance with a median AUC of 0.71 for no longer than 2-year risk prediction, 0.72 for 3-4 years, and 0.71 for 5 years or more prediction. Median AUC was 0.75 for studies including index cancers vs 0.68 when excluded. Six studies reported model calibration performance ranging from good to overestimation of risk. Conclusion Future studies should evaluate models using digital breast tomosynthesis, examine performance for aggressive or advanced breast cancer, include diverse populations, and evaluate both discrimination and model calibration. Prospective evaluations are needed to determine the clinical utility of mammography-based AI models for personalized risk-based breast cancer screening before implementation.

BACKGROUND: The Ventral Rectopexy International Expert Panel recently published a consensus update on ventral rectopexy. The ability of large language models to synthesize the literature on ventral rectopexy without an explicit knowledge base was studied before the publication of the consensus. OBJECTIVE: To compare the responses and citations of different large language models on ventral rectopexy using the expert panel consensus as the reference standard. DESIGN: ChatGPT-4o, Gemini 1.5 Pro, and OpenEvidence were compared on content appropriateness (1 = inappropriate to 5 = appropriate), readability (Flesch reading ease), response length, citation fabrication, and citation quality per Oxford Levels of Evidence. The most content-appropriate chatbot response selected by the expert panel was de-identified and presented alongside the consensus text to 15 colorectal surgeons who attempted to identify the chatbot-generated text. SETTINGS: Questions were submitted from September 18 to 19, 2024. Analysis was performed before the online publication of the consensus on January 30, 2025. MAIN OUTCOME MEASURES: The main outcome measures included content appropriateness, fabricated citation rate, citation quality, and the accuracy of identifying human versus chatbot text by colorectal surgeons. RESULTS: OpenEvidence ranked highest for content appropriateness (mean 3.5/5), above Gemini (3.0/5) and ChatGPT (2.8/5; p < 0.001). ChatGPT was most verbose with the highest readability scores ( p = 0.021). ChatGPT fabricated 53% of citations; Gemini fabricated 12%; OpenEvidence fabricated 0% ( p < 0.001). All OpenEvidence citations were peer reviewed, with 40 of 117 (34%) citing level I to III studies compared with 46 of 94 (49%) of the references cited in the consensus ( p = 0.043). Chatbot-generated responses were identified with 28 of 51 (55%) accuracy. LIMITATIONS: Reproducibility may be affected due to the nature of large language models and the availability of the consensus after publication. CONCLUSIONS: OpenEvidence outperformed Gemini 1.5 Pro and ChatGPT-4o in content appropriateness and peer-reviewed citation quantity and quality. Chatbot-generated text was indistinguishable from expert-authored consensus to subject matter experts. Large language models, as an early-stage research tool, may be viable for future consensus working groups, provided transparent disclosure and rigorous oversight. See Video Abstract . ¿PUEDEN LOS MODELOS LINGÜÍSTICOS DE GRAN TAMAÑO SER UNA HERRAMIENTA VIABLE PARA LOS GRUPOS DE TRABAJO DE CONSENSO? LA EXPERIENCIA DEL GRUPO DE CONSENSO DE EXPERTOS EN RECTOPEXIA VENTRAL ANTECEDENTES: El Panel Internacional de Expertos en Rectopexia Ventral publicó recientemente una actualización consensuada sobre la rectopexia ventral. Antes de la publicación del consenso, se estudió la capacidad de los grandes modelos lingüísticos para sintetizar la bibliografía sobre la rectopexia ventral sin una base de conocimientos explícita. Objetivo: Comparar las respuestas y citas de diferentes grandes modelos lingüísticos sobre la rectopexia ventral utilizando el consenso del panel de expertos como estándar de referencia. DISEÑO: Se compararon ChatGPT-4o, Gemini 1.5 Pro y OpenEvidence en cuanto a la idoneidad del contenido (1 = inadecuado a 5 = adecuado), la legibilidad (índice de legibilidad de Flesch), la longitud de la respuesta, la fabricación de citas y la calidad de las citas según los niveles de evidencia de Oxford. La respuesta del chatbot más adecuada en cuanto al contenido seleccionada por el panel de expertos se anonimizó y se presentó junto con el texto del consenso a 15 cirujanos colorrectales que intentaron identificar el texto generado por el chatbot. ENTORNO: Las preguntas se enviaron los días 18 y 19 de septiembre de 2024. El análisis se realizó antes de la publicación del consenso en línea el 30 de enero de 2025. PRINCIPALES MEDIDAS DE RESULTADOS: Adecuación del contenido, tasa de citas inventadas, calidad de las citas, precisión en la identificación del texto humano frente al del chatbot por parte de los cirujanos colorrectales. RESULTADOS: OpenEvidence obtuvo la puntuación más alta en cuanto a la adecuación del contenido (media de 3,5/5), por encima de Gemini (3,0/5) y ChatGPT (2,8/5) (p<0,001). ChatGPT fue el más prolijo, con las puntuaciones más altas en legibilidad (p = 0,021). ChatGPT inventó el 53% de las citas; Gemini inventó el 12 %; OpenEvidence inventó el 0 % (p < 0,001). Todas las citas de OpenEvidence fueron revisadas por pares, con 40/117 (34 %) que citaban estudios de nivel I-III frente a 46/94 (49 %) de las referencias citadas en el consenso (p = 0,043). Las respuestas generadas por el chatbot se identificaron con una precisión del 28/51 (55 %). LIMITACIONES: Reproducibilidad debido a la naturaleza de los modelos de lenguaje grandes y a la disponibilidad del consenso tras la publicación. CONCLUSIONES: OpenEvidence superó a Gemini 1.5 Pro y ChatGPT-4o en cuanto a la idoneidad del contenido y la cantidad y calidad de las citas revisadas por pares. El texto generado por el chatbot era indistinguible del consenso redactado por expertos para los expertos en la materia. Los modelos de lenguaje grandes como herramienta de investigación en fase inicial pueden ser viables para futuros grupos de trabajo de consenso, siempre que se garantice una divulgación transparente y una supervisión rigurosa. ( AI-generated translation )