Citations

ABSTRACT Background Alcohol‐associated hepatitis (AH) has high short‐term mortality, whereas current prognostic models mainly reflect liver and renal dysfunction. The Metabolic Vulnerability Index (MVX) is a nuclear magnetic resonance‐derived score comprising the Inflammation Vulnerability Index (IVX; small high‐density lipoprotein particles [S‐HDL‐P] and GlycA) and the Metabolic Malnutrition Index (MMX). We evaluated whether MVX, IVX, and IVX components improve 90‐day mortality prediction beyond Model for End‐Stage Liver Disease (MELD) in AH. Methods Serum samples from 196 patients with AH, 169 heavy‐drinking controls, and 351 healthy controls were analyzed by nuclear magnetic resonance spectroscopy. The primary outcome was 90‐day AH‐related mortality. Biomarkers were modeled continuously after standardization within the AH cohort; S‐HDL‐P was modeled per 1 SD decrease. Cox models were adjusted for MELD, age, sex, white blood cell count, and baseline antibiotic or corticosteroid use. Model performance was assessed using Akaike information criterion (AIC), likelihood‐ratio testing, and Harrell's C ‐statistic. Results Among patients with AH, 30 AH‐related deaths occurred within 90 days (15.3%). IVX and MVX were highest in AH cases and increased with AH severity, whereas MMX did not consistently differentiate severity. Lower S‐HDL‐P was independently associated with 90‐day mortality in fully adjusted models (HR, 1.84; 95% CI, 1.01–3.35; p = 0.045), whereas GlycA was not (HR, 0.86; 95% CI, 0.54–1.37; p = 0.527). Adding S‐HDL‐P improved fully adjusted MELD‐based model fit (AIC, 298.97 vs. 301.46; LR p = 0.034; C ‐statistic, 0.741 vs. 0.729). IVX showed supportive improvement in model fit and discrimination (AIC, 299.81; LR p = 0.056; C ‐statistic, 0.749). Continuous MELD interaction analyses supported risk separation for S‐HDL‐P (LR χ 2 = 6.20; p = 0.045) and IVX (LR χ 2 = 6.64; p = 0.036). Conclusions Lower S‐HDL‐P appears to be the principal short‐term prognostic component within the IVX domain in AH. S‐HDL‐P and IVX may refine MELD‐based 90‐day risk stratification, pending external validation.

Objectives: Expanded coverage for telehealth during the COVID-19 pandemic allowed providers to bill for telemedicine services that were previously not reimbursable, including telemedicine critical care (TCC) services for critically ill patients. We aimed to characterize TCC billing practices among Medicare beneficiaries before, during, and after the COVID-19 pandemic. Design, Setting, and Patients: This was a serial cross-sectional study of adult Medicare Fee-For-Service beneficiaries with at least one bill for critical care at acute care hospitals from January 2018 to September 2024. TCC billing was identified using provider billing codes; multivariate regression models were used to determine characteristics associated with receipt of TCC. Key outcomes were patient-, provider-, and hospital-level characteristics associated with TCC billing. Interventions: None. Measurements and Main Results: Billing for TCC increased from 0.002% of critical care bills pre-pandemic to 0.01% of critical care bills during and after the pandemic. Patients billed for TCC were disproportionately likely to have COVID-19 but were otherwise relatively similar to critically ill patients not billed for TCC. Internal medicine/critical care providers accounted for the highest proportion of pandemic TCC bills (46.0%). TCC billing occurred more often at minor teaching hospitals (adjusted odds ratio [aOR], 1.21; 95% CI, 1.03–1.43) and at safety-net hospitals (aOR, 1.33; 95% CI, 1.04–1.70). TCC billing was less likely at small-sized hospitals (aOR, 0.39; 95% CI 0.26–0.58) and medium-sized hospitals (aOR, 0.67; 95% CI, 0.47–0.95), government-owned hospitals (aOR, 0.70; 95% CI, 0.57–0.86), for-profit hospitals (aOR, 0.58; 95% CI, 0.48–0.71), rural hospitals (aOR, 0.70; 95% CI, 0.55–0.89), and critical access hospitals (aOR, 0.59; 95% CI, 0.47–0.73). Conclusions: Billing for TCC among hospitalized critically ill Medicare beneficiaries increased during the pandemic but remained low as a proportion of all critical care bills. There was variability in utilization across subspecialties and lesser utilization at rural and critical access hospitals. Further studies are needed to characterize the clinical and economic consequences of this shift.

Abstract INTRODUCTION Associations of arterial stiffness, measured through pulse wave velocity (PWV), with incident dementia may be driven by age‐related structural changes to the arterial wall or by elevated blood pressure. METHODS Dementia‐free White or Black participants in the community‐based Atherosclerosis Risk in Communities (ARIC) cohort study with measures of PWV were examined. The associations of carotid‐femoral PWV (cfPWV) and total, structural, and load‐dependent PWV with dementia were estimated using Poisson regression models and Cox proportional hazards models. Dementia cases were defined by physician‐adjudicated review, telephone interviews, hospitalization records, and death certificates. RESULTS Of 4818 participants included in the study population (mean age: 75 years; 41% male, 21% Black), 1067 (22%) developed dementia over a median follow‐up of 9.0 years. Higher cfPWV, total PWV, structural PWV, and load‐dependent PWV were associated with greater dementia risk. DISCUSSION Both structural and pressure‐related arterial stiffness mechanisms may underlie the link between PWV and dementia.

Abstract Generative AI (Gen AI), Foundation Models (FMs), and Large Language Models (LLMs) are powerful emerging technologies that demonstrate exceptional capabilities in processing vast amounts of unstructured and structured data, including text, voice, images, video and other formats, and adapting to a wide range of specific tasks. Their immense potential to drive meaningful improvements in treatment outcomes is increasingly evident. The advent of these technologies has marked a transformative era in healthcare, including the fields of radiation oncology and medical physics. Specifically, these powerful technologies offer unprecedented opportunities to analyze domain‐specific data, process and synthesize medical images, automate routine tasks, support clinical decision‐making, optimize and streamline clinical workflows, and enhance the quality of clinical trials. While these emerging technologies present new opportunities to revolutionize radiation therapy practice, their implementation also raises important educational, ethical, and regulatory considerations. This scoping review highlights benefits, promises, risks, and challenges, such as interpretability, data privacy, regulatory compliance, reproducibility, hallucination, and integration into existing clinical workflow. Finally, emerging opportunities are outlined to guide future research directions. This review paper provides a timely overview of Gen AI, FMs and LLMs, aiming to inform medical physicists, clinicians, and researchers of the evolving role of these disruptive technologies in shaping the future of radiation therapy.

Background. Negative pressure wound therapy promotes wound healing through fluid removal, edema reduction, and mechanical contraction. A novel thermoplastic elastomer (TPE) dressing has been developed to improve exudate evacuation and reduce tissue ingrowth, but its effect on wound contraction compared with reticulated open cell foam (ROCF) remains unclear. Objective. To compare the degree of wound contraction with the TPE dressing, ROCF, or no filler at different wound depths and negative pressure settings in a porcine explant model. Materials and Methods. The effect of the materials or lack thereof on wound contraction was investigated at 2 wound depths (shallow, deep) and 3 negative pressure settings (−50 mm Hg, −80 mm Hg, and −125 mm Hg). Wound width was measured at 3 standardized locations before and during therapy. Univariable and multivariable linear regression analyses were performed to identify factors associated with contraction. Results. A total of 810 measurements were obtained. Both the TPE dressing and ROCF demonstrated statistically significantly greater contraction than no filler. In deep wounds, greater contraction was noted with the TPE dressing compared with ROCF. Higher negative pressure and increased wound depth were independently associated with greater contraction. Absolute differences in contraction between dressings were small (<3 mm across all conditions). Conclusion. The TPE dressing provides equivalent or greater wound contraction compared with ROCF, particularly in deep wounds, without impairing macrodeformation. Given the small magnitude of differences, the clinical relevance of this finding likely depends on additional factors, which should be evaluated in future in vivo studies.

This guideline has been updated. This ASCO Living Guideline is reviewed on an eight-week cycle. Please see the online dynamic version for the latest updates. Living guidelines are developed for selected topic areas with rapidly evolving evidence that drives frequent change in recommended clinical practice. Living guidelines are updated on a regular schedule by a standing expert panel that systematically reviews the health literature on a continuous basis, as described in the ASCO Guidelines Methodology Manual . ASCO Living Guidelines follow the ASCO Conflict of Interest Policy Implementation for Clinical Practice Guidelines . Living Guidelines and updates are not intended to substitute for independent professional judgment of the treating clinician and do not account for individual variation among patients. See appendix for disclaimers and other important information (Appendix I and Appendix II). Updates are published regularly and can be found on the ASCO Publications website .

Gross anatomy is now delivered in curricula that are increasingly compressed and integrated with other areas of medical training. At the same time, digital resources and physical models have become more common as supplementary tools in anatomy education. These shifts have renewed interest in the distinctive educational value of donor-based learning and in how preservation methods should be aligned with clinically meaningful learning objectives. This narrative review examines the use of fresh human donor tissue in anatomy teaching and clinically oriented procedural training. It focuses on unembalmed, non-fixed, and fresh-frozen tissue, while soft-preserved tissue is considered mainly as contextual and comparative evidence. Literature searches were conducted in MEDLINE, Scopus, Web of Science, and ERIC databases for English-language human studies published from 2015 through early 2026, with backward citation to identify older landmark comparator papers. Because the preservation-explicit educational literature was limited and heterogenous, findings were synthesized narratively. Across the included literature, fresh tissue appears most educationally valuable when learning objectives depend on functional tissue behavior, including tissue palpation, percussion, tissue-plane recognition, ultrasound-guided anatomy, or realistic procedural handling. Available studies suggest benefits in selected knowledge and performance outcomes, especially in clinically oriented examination and postgraduate refresher courses. Comparator evidence indicates that soft-preserved tissue may provide a pragmatic alternative when programs need repeated access or broader curricular integration while still preserving more realistic handling than formal fixed donors. Formalin fixed tissue remains useful for durable structural teaching despite reduced functional realism. Overall, preservation methods should be treated as a curricular design decision rather than a neutral technical detail. Fresh tissue therefore has a defensible place in competency-based anatomy education when used selectively for tasks requiring high functional fidelity, although stronger evidence for long-term clinical transfer remains limited.

Purpose: Depression is prevalent yet frequently underdiagnosed. Although speech-based detection methods show promise, most prior studies have emphasized binary classification in nontonal languages. This study examined whether acoustic features of spontaneous Mandarin speech reflect depression as a categorical condition or a continuous, dimensional construct. Method: A validated emotional Mandarin speech corpus paired with self-reported depression severity scores was analyzed. Acoustic features were extracted using the extended Geneva Minimalistic Acoustic Parameter Set. A multistage analytic framework was applied, including random forest classification to distinguish depressed from nondepressed clips, linear mixed-effects modeling to examine group and severity effects, and unsupervised clustering to examine latent structure in the acoustic feature space. Results: The random forest classifier achieved an accuracy of 72.3% and an area under the receiver operating characteristic curve of 0.826 on the held-out test set. Model performance favored sensitivity over precision in identifying depressed clips. SHapley Additive exPlanations analysis identified features across multiple acoustic domains, including spectral, pitch-related, voice quality, cepstral, and intensity measures, as important contributors to model predictions. Among the Top 10 features, no acoustic features showed statistically significant group differences. In contrast, median and mean fundamental frequencies were significantly positively associated with depression severity. Clustering analysis revealed overlapping group structures and a continuous distribution of severity scores across clusters. Conclusions: These findings provide preliminary support for a dimensional conceptualization of depression in spontaneous Mandarin speech. While classification models can distinguish depressed from nondepressed speech with moderate accuracy, acoustic features appear to vary more consistently with symptom severity than with diagnostic group. Speech-based measures may therefore have potential for continuous monitoring of depression, although this possibility requires further longitudinal verification.