Faculty Bibliography

OBJECTIVE:Physical activity can reduce cardiovascular disease and depression risk and improve quality of life in patients with systemic lupus erythematosus (SLE). To facilitate physical activity and achieve health benefits in patients with SLE, it is critical to understand potential barriers to physical activity, including socioeconomic, social, demographic, quality-of-life, or clinical factors. METHODS:We conducted cross-sectional analyses of data from a large, diverse cohort of patients with SLE. All completed the International Physical Activity Questionnaire, recalling the past seven days of vigorous physical activity, moderate activity, or walking. Data included financial insecurity, Everyday Discrimination Scale, education, demographics, lupus-specific disease activity, immunosuppressive medication, Census Block Area Deprivation Index, and patient-reported pain, fatigue, and cognitive function. Multivariable models included logistic regression for dichotomous outcome of "any" moderate/vigorous physical activity and quasi-Poisson model for total combined days of moderate and vigorous activity. RESULTS:Of the 271 participants, 170 (63%) reported any moderate or vigorous activity in the past 7 days (mean = 2.6 days of moderate/vigorous activity). Only 4% reported zero days of physical activity. Logistic regression analysis indicated that active disease was associated with 47% lower odds of engaging in any moderate/vigorous physical activity (P = 0.04) and with a 35% reduction in the mean number of days of moderate to vigorous physical activity (P = 0.04). In contrast, individual- and area-level socioeconomic factors and patient-reported outcomes were not associated with physical activity. CONCLUSION/CONCLUSIONS:Moderate/vigorous physical activity was negatively associated only with disease activity. The current study reinforces the need primarily to control SLE disease activity to promote patients' ability to be physically active, which may improve symptoms.

OBJECTIVES/OBJECTIVE:Large language models (LLMs) are increasingly used in medicine and research, but neuroradiologists' awareness, perceived utility, and concerns about integrity and disclosure remain incompletely characterized. This survey aimed to assess radiologists' awareness and perceptions of LLMs in clinical and research domains. MATERIALS AND METHODS/METHODS:An anonymous, voluntary SurveyMonkey survey was distributed internationally (October 1, 2024 to March 31, 2025) via neuroradiology society newsletters/membership channels and social media. Categorical variables were summarized as counts and percentages; Likert items were summarized using weighted means and response distributions. Item-level complete-case denominators were reported. Prespecified subgroup analyses used chi-square/Fisher exact tests (categorical) and nonparametric tests (ordinal), with Holm multiplicity control within prespecified multi-item question blocks and within each subgroup factor. RESULTS:A total of 265 respondents started the survey; after exclusions, 209 were included in the analytic sample, of whom 64.6% were male. Awareness of LLMs was high (ChatGPT: 83.3%), but knowledge gaps persisted (14.8% unfamiliar with all listed models; 16.7% misclassified DALL·E as an LLM). Respondents most frequently endorsed bounded, workflow-adjacent clinical applications, including guideline-based recommendations (75.6%) and protocol selection (60.8%), with lower endorsement for image interpretation (22.0%). Concerns were common regarding plagiarism/data fabrication (82.1%), inaccurate or biased outputs (75.8%), and accountability (72.1%), alongside support for AI-detection tools (77.0%) and documentation of LLM use aligned with an example journal policy (73.1%). CONCLUSION/CONCLUSIONS:Survey respondents reported cautious optimism toward LLM integration, favoring workflow-adjacent applications while emphasizing disclosure, oversight, and targeted education.

BACKGROUND:Systemic therapy with phosphodiesterase type 5 inhibitors (PDE5is) is the standard of care for erectile dysfunction (ED), but these treatments are not effective in all men, and others may prefer non-systemic treatment options. AIM/OBJECTIVE:The goal of this Delphi consensus initiative was to address unmet needs in the treatment of men with ED and the best use of a US Food and Drug Administration (FDA) cleared topical therapy, MED3000 (Eroxon®), that is available without a prescription. METHODS:The iterative Delphi process involved the creation of an initial slate of 38 statements and brief summaries of related evidence (if available), followed by the review from 2 co-chairs and 3 rounds of consensus development by an independent panel. OUTCOMES/RESULTS:The Delphi process reduced the initial set of 38 statements to 31 for which there was ≥80% support (in some cases after revision of the initial statement and revoting) from the panel in the final round of voting. RESULTS:Statements for which consensus was achieved were consistent with current guidelines in recognizing the need for topical ED therapy. They also provided practical expert advice on the best use of this topical therapy. Statements regarding MED3000 (Eroxon®) for which consensus was not achieved identified important clinical considerations that would benefit from further analysis of existing clinical trial results for MED3000 and collection of new real-world data. CLINICAL IMPLICATIONS/CONCLUSIONS:This initiative identified multiple unmet needs that may be addressed by a well-tolerated and efficacious topical treatment. It also provided a critical assessment from experienced healthcare professionals of the evidence supporting the use of an over-the-counter topical therapy for ED. STRENGTHS AND LIMITATIONS/UNASSIGNED:The main strength of this Delphi initiative was an expert assessment of unmet needs in ED and the place in therapy for topical medications. The main limitation was that available data for topical treatment leaves some questions unanswered, most notably efficacy in different subpopulations of men with ED. CONCLUSIONS:Overall, the statements supported in this Delphi initiative may provide a framework for more detailed recommendations that could be incorporated into treatment guidelines. In addition, the statements for which unanimous support could not be achieved help to identify evidence gaps that are targets for future research.

PURPOSE/UNASSIGNED:This study describes the patient-centered approach to hearing technology selection and fitting of the participants randomized to a best practice hearing intervention as part of the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study (ClinicalTrials.gov identifier NCT03243422). We evaluated associations between hearing technology with daily hours of hearing aid use and listening and communication goal achievement. METHOD/UNASSIGNED:technology levels, and offered at least one hearing-assistive technology (HAT). The Client-Oriented Scale of Improvement (COSI) was used to identify listening needs that guided intervention delivery and was used to assess attainment of hearing-related goals following ~10-week intervention period. Hearing aid datalogging was used to measure hours of daily wear. We estimated the association between hearing aid technology level, HATs, hours of wear, and COSI goal attainment using an ordered logistic model adjusting for auditory and sociodemographic characteristics. Proportionality odds assumption was checked for all models. RESULTS/UNASSIGNED:= 9.3 hr across all participants) and did not differ between hearing technology (levels or HATs). Participant COSI goals, which included categories such as conversation in noise and in quiet or attending church and/or meetings, improved and were not dependent on technology used. Participants benefited from patient-centered hearing intervention, and there were no statistically significant associations among hearing aid technology level, HATs, hours of use, and change in COSI goals. CONCLUSIONS/UNASSIGNED:The patient-centered selection of hearing technology used in the ACHIEVE study resulted in high levels of hearing aid and HAT usage, along with positive COSI listening goal attainment for the majority of participants. Carefully assessed and selected technology is needed to meet individual auditory rehabilitation needs. SUPPLEMENTAL MATERIAL/UNASSIGNED:https://doi.org/10.23641/asha.32069253.

IntroductionBleeding and thrombosis are major causes of morbidity and mortality in pediatric extracorporeal membrane oxygenation (ECMO), yet their evolving, time-dependent risks remain poorly defined. This study evaluated clinical predictors of bleeding and thrombotic events using time-to-event analysis.MethodsA retrospective cohort study was conducted using the Pediatric ECMO Outcomes Registry (PEDECOR) from October 2011 to September 2024. Patients aged ≤18 years undergoing their first ECMO run were included. Two time-varying Cox proportional hazards models assessed associations between prior complications and time to first bleed or thrombosis, adjusting for clinical and ECMO-related variables.ResultsAmong 1444 patients, median age was 0.4 years (IQR: 0.0-4.4), and 53.6% were male. Bleeding occurred in 65% and thrombosis in 28%. Time to first bleeding events had a median of 2 days (IQR: 0-4) while time to first thrombosis had a median of 3 days (IQR: 2-6). Prior thrombosis was associated with lower early bleeding risk (HR: 0.39, 95% CI: 0.25-0.62, p < 0.001), which reversed over time (interaction HR: 1.44, 95% CI: 1.08-1.92, p = 0.013; crossover at 12.4 days). Similarly, prior bleeding was associated with reduced early thrombosis risk (HR: 0.49, 95% CI: 0.34-0.71, p < 0.001), but reversed over time (interaction HR: 1.63, 95% CI: 1.26-2.11, p < 0.001; crossover at 4.3 days). Central cannulation, cardiac surgery, and non-pulmonary indications were associated with bleeding; sepsis was associated with thrombosis. Anticoagulant type and sex were not significant.ConclusionsBleeding and thrombosis are common and time-dependent in pediatric ECMO. These findings support dynamic anticoagulation strategies tailored to evolving risk.

Critical-sized bone defects remain a significant clinical challenge, and dipyridamole (DIPY)-coated 3D-tricalcium phosphate (β-TCP) scaffolds have shown promising osteogenic efficacy in preclinical models. However, the literature on the systematic physicochemical characterization of this scaffold system, including optimization of DIPY loading parameters, release kinetics, and surface properties, is lacking. This study addresses these gaps by characterizing DIPY-loaded 3D-printed β-TCP scaffolds across solid and porous architectures, three coating concentrations (10, 100, and 1000 µM), and three coating volumes (250, 500, and 1000 µL). Under static PBS conditions, drug release over 21 days was quantifiable only at 1000 µM, and release-kinetics modeling (zero-order, Higuchi, and Korsmeyer-Peppas) was therefore restricted to this highest concentration. At 1000 µM, both scaffold types showed biphasic release profiles, with standard empirical models reasonably approximating the overall kinetics, while not fully capturing the biphasic behavior over the entire duration. Porous scaffolds showed significant volume-dependent release (p = 0.002, η

OBJECTIVES/OBJECTIVE:To evaluate the effect of a proprietary motion artifact correction algorithm on CBCT spatial resolution using an in vitro phantom model. STUDY DESIGN/METHODS:Fifty CBCT scans were acquired with a ProMax 3D unit using a point spread function phantom mounted on a motorized turntable. Ten protocols were tested, including no motion and induced motion up to 9 degrees, with and without activation of the correction algorithm. Spatial resolution was assessed using full width at half maximum (FWHM), surface plots, fast Fourier transforms, pairwise comparisons, and Bland-Altman analysis. RESULTS:Motion increased FWHM values and distorted the point spread function, with greater irregularity as motion magnitude increased. The correction algorithm produced partial improvement in selected motion protocols, particularly at lower motion magnitudes, but the effect was inconsistent across all motion conditions and measurement directions. In the no-motion protocol, activation of the algorithm introduced slight unsharpness and increased heterogeneity in the high-frequency domain. CONCLUSION/CONCLUSIONS:Patient motion degrades CBCT spatial resolution. The proprietary correction algorithm may provide partial improvement under selected conditions, particularly at lower motion magnitudes, but it does not replace the need for careful patient stabilization during image acquisition and should be used cautiously when motion is unlikely.

Saliva has emerged as a compelling liquid biopsy for the non-invasive diagnosis and monitoring of both oral and systemic diseases. Secreted by major and minor salivary glands and enriched by gingival crevicular fluid, epithelial turnover, immune mediators, microbial products, and plasma-derived constituents, saliva reflects a biologically integrated interface between local oral environments and systemic physiology. This dual origin enables detection of disease-associated signals across multiple molecular layers, including extracellular RNA, cell-free DNA, genomic and epigenetic material, proteins, metabolites, microbial signatures, and hormones. Advances in high-throughput sequencing, mass spectrometry, and ultrasensitive immunoassays have revealed that salivary analytes can capture dynamic pathological processes ranging from periodontal inflammation and dental caries to oral and head and neck cancers, as well as systemic conditions such as non-oral cancers and autoimmune, cardiometabolic, infectious, endocrine, and neurodegenerative diseases. In particular, extracellular vesicle-encapsulated RNA, cfDNA fragmentomics, and methylation patterns have expanded the diagnostic reach of saliva beyond conventional protein-based biomarkers, while integrated multi-omics approaches increasingly improve diagnostic performance. Despite this progress, clinical translation remains constrained by biological complexity, including variable glandular contributions, oral microbiome interactions, and pre-analytical variability in collection and processing. Emerging point-of-care technologies, microfluidic platforms, and artificial intelligence-driven multi-omic integration are beginning to address these limitations, enabling higher analytical sensitivity and improved disease stratification. Regulatory pathways, including in vitro diagnostic frameworks and laboratory-developed test structures, are progressively accommodating salivary assays, as demonstrated during the COVID-19 pandemic. However, widespread clinical adoption will require rigorous standardization, large-scale validation, and demonstration of clinical utility. Together, saliva-based liquid biopsy represents a rapidly evolving diagnostic paradigm with the potential to shift disease detection towards earlier, minimally invasive, and data-rich precision medicine approaches across dentistry and systemic healthcare.

OBJECTIVES/OBJECTIVE:Generative artificial intelligence (AI) holds promise for creating patient education materials (PEM). However, AI-produced content is often difficult to read. Prompts for AI to write at a lower reading level either fail to meet recommended targets (≤6th grade) or demonstrate inconsistent results. We aimed to determine whether a new AI prompt for plain language would create PEMs that are easier to read, understand, and act upon. METHODS:We analyzed PEMs from two websites (HealthyChildren.org, UpToDate) and two generative AI programs (ChatGPT, Gemini). For each AI program, we used a basic prompt and an advanced prompt to generate separate documents. From these sources, we collected six sets of PEMs about five acute pediatric conditions, evaluated them using a panel of readability indices, and used ANOVA to compare average readability scores between sources. Two pediatricians assessed understandability and actionability using the Patient Education Materials Assessment Tool (PEMAT). We calculated mean PEMAT scores, with values > 70% considered understandable/actionable. RESULTS:ChatGPT (advanced prompt) created PEM with the lowest mean grade reading level (5.8; SD 0.84) and highest PEMAT scores (91% understandable, 84% actionable). Documents from generative AI using the advanced prompt and UpToDate had mean readability scores ≤ 6th grade, with significantly better readability than AI-generated documents using the basic prompt or HealthyChildren.org. All sources except HealthyChildren.org had mean understandability > 70%; AIs using the advanced prompt and UpToDate exceeded the actionability threshold. CONCLUSIONS:A plain-language prompt for generative AI created PEMs that were readable, understandable, and actionable, with comparable results across two AI programs. PRACTICE IMPLICATIONS/CONCLUSIONS:Healthcare providers can use this new plain-language prompt for generative AI programs to quickly create free, patient-friendly PEM about acute healthcare topics. As these AI programs were not trained to provide medical guidance, medical professionals should continue to review PEM prior to sharing with patients.