Objective: The MEchanick Transculturalization Research and Innovation ConSortium/Bernard Lown Scholars in Cardiovascular Health Program Consensus Conference on Dysglycemia-Based Chronic Disease (DBCD) Transculturalization in Chile convened on November 20, 2023, in Santiago, Chile. The conference generated affirmed and emergent concepts, key strategies, and specific implementation tactics to improve type 2 diabetes (T2D) care in Chile. Findings: Important affirmed concepts included: (1) implementing a comprehensive approach to T2D management beyond glycemic control; (2) addressing unique challenges for early detection and treatment of T2D; and (3) applying expanded roles of telemedicine. Important emergent concepts included: (1) adopting transculturalized chronic care models such as DBCD; (2) recognizing prediabetes as a critical DBCD target to prevent T2D and T2D complications, especially cardiovascular disease; and (3) implementation of the DBCD model for individual and population health. Key strategies included: (1) validation of culturally adapted T2D risk assessment tools; (2) integration of social determinants of health (SDOH) and ethnocultural factors into DBCD care strategies/tactics; and (3) promotion of equity in healthcare access for all people comprising diverse populations. Finally, specific implementation tactics included: (1) focusing on patient-centered public policies; (2) ensuring access to effective treatments; and (3) using culturally relevant resources for education and prevention. When coordinated, these strategies and tactics mitigate DBCD progression, thereby enhancing healthcare outcomes. Conclusions and recommendations: Expert consensus emphasizes the need for a comprehensive approach to T2D management in Chile, leveraging transculturalized lifestyle medicine, validated risk assessment tools, SDOH, and patient-centered public policies. This process should begin with incorporating eHealth technologies, validation studies, and then translation into clinical practice guidelines. As this templated methodology is applied to other regions of the world, the resulting compendium of concepts, strategies, and tactics can foment a more effective preventive health culture and optimize DBCD care across the ethnocultural spectrum.
The clinical trial ecosystem of Saudi Arabia has advanced significantly, with innovative industry-sponsored clinical trials (iCTs) growing by 27% from 2018 to 2023, reaching 51.4% in the first half of 2025. However, the Kingdom remains underrepresented in global research. This study aimed to quantify this gap and develop strategies to enhance Saudi Arabia's competitiveness. A mixed-methods research design was employed. Phase 1 involved a quantitative landscape analysis of historical and current iCT data (2016-2023) using the LongTaal Clinical Trial Informatics platform. Phase 2 involved a qualitative assessment of expert input derived from two national clinical trial conferences (2022 and 2024), in which expert panel discussions and documented outputs were used to contextualize findings and inform strategic recommendations. In 2023, Saudi Arabia's iCT market share was < 0.06%, significantly lower than its ~ 0.9% share of global pharmaceutical consumption. This 16-fold disparity highlights a critical lack of patient representation. Economic modelling indicates that achieving parity could increase annual research and development (R&D) investment from ~ USD 46 million to over USD 740 million. Insights derived from conference-based expert discussions highlighted regulatory timelines, infrastructure fragmentation, and insufficient incentives as primary barriers. To bridge this gap, the authors propose operationalizing a centralised national body to serve as a "one-stop shop" for global sponsors. Strategic priorities include harmonizing regulatory timelines to 6 months, establishing distributed Centres of Excellence, and implementing direct R&D financial incentives. These measures are essential to ensuring Saudi patients are adequately represented in the development of novel pharmaceuticals.
Objective: This study describes a multidisciplinary, multi-generational case conference focusing on healthcare professionals' emotional conflicts and moral distress-what we call "moyamoya" in Japanese-in clinical practice. Materials and Methods: Five hybrid conferences were co-organized by Kyoto-Min-Iren and an independent study group. In each session, one anonymized case was presented. Discussions emphasized sharing emotional conflicts without criticism or seeking conclusions and encouraged dialogue from multiple professional perspectives. Participants included physicians, nurses, medical social workers, administrative staff, and medical students. Results: The conferences appeared to generate diverse discussions and serendipitous insights. The dialogue may have promoted reflection similar to Significant Event Analysis and may foster mutual understanding by making interprofessional perspectives visible. It also appeared to offer opportunities to reconsider the problem-solving orientation common in daily practice and to share an approach attentive to patients' life backgrounds. For young healthcare professionals and students, it may provide practical learning about the social determinants of health through socially vulnerable cases. However, the absence of thematic limits may pose challenges in facilitating discussions and aligning participants' interests. Conclusion: A case conference centered on emotional conflicts may foster reflective practice, interprofessional understanding, and learning beyond technical knowledge, while requiring structural refinement to enhance practical value.
General pediatricians often evaluate hematologic and oncologic presentations before subspecialty consultation, yet the 2025 Accreditation Council for Graduate Medical Education (ACGME) pediatric requirements reduce inpatient pediatric hematology/oncology (PHO) time, raising questions about resident readiness. We evaluated whether inpatient PHO exposure was associated with resident confidence and knowledge in faculty-prioritized topics. We conducted a single-center cross-sectional study. PHO faculty completed a needs assessment to identify generalist-relevant competencies. Residents completed a 27-item confidence survey and an 8-item multiple-choice question (MCQ) assessment and were compared across cohorts with 0, 288 (one 4-week block), or 840 inpatient PHO hours using Kruskal-Wallis testing. Spearman correlation related confidence to knowledge overall and within cohorts. Fourteen PHO faculty and 44 of 89 residents (49.4%) completed the surveys. Overall confidence differed across cohorts (p < 0.0001), similar in the 0- and 288-h cohorts but higher in the 840-h cohort. Total MCQ scores did not differ significantly (p = 0.1283). Five of eight faculty-prioritized topics were answered correctly by fewer than half of residents. Higher confidence was associated with higher knowledge overall (ρ = 0.31, p = 0.04), but this reflected differences between cohorts and was not significant within any cohort. Greater inpatient PHO exposure was associated with higher confidence but not higher MCQ performance, and confidence was not a reliable indicator of measured knowledge. Residents approximating the new ACGME exposure threshold were indistinguishable from those with no exposure in either outcome. PHO educators should assess knowledge directly against defined generalist outcomes rather than assuming time on service or confidence reflects the knowledge residents need.  : This work was presented in part as Poster #202, "Impact of Reduced Pediatric Heme/Onc Exposure on Resident Confidence and Knowledge," at the 2026 American Society of Pediatric Hematology/Oncology Conference, April 29 to May 2, 2026, Minneapolis, Minnesota, and published in the Pediatric Blood & Cancer 2026 ASPHO Conference Paper and Poster Index. The poster was selected as a top poster at ASPHO that year.
Understanding congenital heart disease requires a 3D mental framework, yet clinicians typically rely on 2D imaging. Multi-disciplinary case management conference (CMC) discussions often involve review of complex anatomy utilizing cross-sectional imaging. Mixed reality (MR) offers immersive 3D visualization that may enhance these discussions. Our objectives were to demonstrate the feasibility of integrating MR-guided discussions into CMC and assess Heart Center perceptions of its use. This prospective, single-center study was conducted during multi-disciplinary CMCs. Baseline and post-presentation Likert-scale questionnaires were administered. EchoPixel True3D (Santa Clara, CA) was used to present 3D MR models from cardiac CT datasets. Participants used electronic glasses wirelessly linked to a 3D projector to view the MR models in conference, which were manipulated in real-time. On the baseline survey (n = 46), 67% agreed that complex cardiac anatomy is difficult to interpret with 2D imaging. Twelve MR cases were presented. On the post-survey (n = 100), 93% rated the MR model quality as good/excellent, 75% felt that MR improved their understanding of the cardiac anatomy, and 89% supported regular use of MR in CMC. Among surgeons and interventionalists, 82% reported improved procedural planning and 57% altered their procedural approach. Mixed reality imaging can be successfully incorporated into CMC presentations and discussions, with positive participant responses. MR provides a virtual 3D framework that closely replicates patient anatomy and supports pre-procedural planning and execution.
The Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were developed to improve the completeness and transparency of reporting of reliability and agreement of health measurement instruments. However, since their publication in 2011 methodological standards, both for reporting guideline development and reliability, agreement and measurement error studies have advanced, highlighting the need for aligning and updating. In addition, related initiatives like COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) have emerged, offering opportunities to harmonise terminology and promote consistency across diverse types of measurement instruments. This method review aims to (1) systematically identify and synthesise commentaries on and evaluations of the original GRRAS and (2) map recent methodological developments in the planning, conduct and interpretation of reliability, agreement and measurement error studies in health science, psychology and education that should be reflected in the reporting, to inform the development of the GRRAS-COSMIN reporting guidelines. Two complementary search strategies will be employed. First, forward direct citation tracking of the original GRRAS publications will be conducted in Web of Science. We will include sources providing critique, commentaries or suggestions related to the GRRAS. We will exclude publications that used GRRAS just for structuring their report, withdrawn or retracted articles, textbooks, peer reviews, supplements and conference materials without full-text publications. Included articles will be analysed using descriptive content analysis. Second, we will perform a systematic search in MEDLINE, PsycInfo, Embase, ERIC and CINAHL supplemented by key references identified by or known to the author team. We will include studies, reviews, commentaries, editorials, methodological papers, tutorials and guidance documents that discuss or critically reflect on methodological aspects of the measurement properties reliability and/or agreement/measurement error published between 1 January 2015 and 30 June 2026 in health sciences, psychology or education. Eligibility will be assessed by two independent reviewers and included sources will be analysed using 'codebook' thematic analysis. Findings will be presented narratively supplemented by visuals and tables if appropriate. This study involves publicly available data. No ethical approval is needed. Results will be disseminated through an open-access journal publication following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension and conference presentations.
Natural language processing (NLP) techniques offer promising solutions for semi-automating the time-consuming process of abstract screening in systematic reviews. The exponential growth of published literature has created significant bottlenecks, with review teams manually assessing thousands of abstracts over weeks to months. Single reviewers can miss 5-13% of relevant studies, necessitating dual screening that further increases workload. Advances in artificial intelligence, including deep learning models such as BERT and its successors, show potential for automating this critical step, but comprehensive evidence on optimal approaches, performance, and practical feasibility remains limited. This systematic review aimed to assess techniques, performance, and feasibility of NLP approaches for title and abstract screening by characterizing the range of NLP methods used, summarizing performance on key metrics like workload reduction and recall, evaluating real-world implementation feasibility, and identifying research gaps and future directions. We searched PubMed, Web of Science, Embase, CINAHL, The Cochrane Library, Scopus, and gray literature sources from inception to December 2024. The search strategy, developed with an information specialist and peer-reviewed using PRESS guidelines, targeted keywords related to natural language processing, machine learning, abstract screening, and systematic reviews. Additional sources included conference proceedings, preprint servers, reference lists, forward citation tracking, and expert consultation. We included primary studies of any design describing development or evaluation of NLP techniques for automating title and abstract screening in evidence syntheses. Eligible studies reported on NLP methods, screening performance (workload reduction, recall, precision), or implementation feasibility. Studies using only rule-based approaches without machine learning, systematic reviews of NLP methods, commentaries, and conference abstracts were excluded. No language or date restrictions were applied. Two reviewers independently screened titles, abstracts, and full texts using Covidence software, with disagreements resolved through discussion. Data extraction covered study characteristics, NLP techniques, training approaches, performance metrics, and feasibility considerations. Risk of bias was assessed using a modified ROBIS tool. Given diverse techniques and outcomes, we conducted narrative synthesis following SWiM guidelines, grouping studies by NLP approach. From 4,105 records, 19 studies met inclusion criteria, with 68.4% published since 2023, reflecting rapid field advancement. Studies employed diverse approaches from traditional machine learning (Support Vector Machines, Random Forests) to advanced deep learning models, particularly BERT variants. Most achieved >90% recall with workload reductions of 13-96%, representing substantial time savings. Deep learning models with transfer learning consistently outperformed traditional approaches. However, implementation faced significant barriers including requirements for high-quality training data, specialized computational resources, technical expertise, and user-friendly interfaces. Performance was generally better for targeted reviews with lower inclusion prevalence. NLP techniques, especially deep learning with transfer learning, show substantial promise for semi-automating abstract screening with potential for large workload savings while maintaining high recall. However, challenges remain regarding training data quality, computational requirements, technical expertise needs, and user-centered design. Realizing full potential requires interdisciplinary collaboration to develop reliable, generalizable tools integrating seamlessly with human expertise and existing workflows. Future priorities include creating standardized datasets, conducting prospective evaluations, developing user-friendly interfaces, and establishing implementation best practices to revolutionize evidence synthesis efficiency. Declarative title: Natural language processing substantially reduces abstract screening workload but requires significant expertise and specialized computing resources. The review in brief Natural language processing techniques can reduce manual abstract screening workload by 30-90% while maintaining over 90% recall of relevant studies, with deep learning models showing the greatest promise for systematic review automation. What is this review about? Problem statement: Systematic reviews are the highest level of evidence for policy and practice, but exponential literature growth has made abstract screening a major bottleneck, taking weeks to months. Single reviewers miss 5-13% of relevant studies, making dual independent screening the gold standard, at significant cost in time and resources. What is the aim of this review? This systematic review examines the techniques, performance, and feasibility of natural language processing methods for automating title and abstract screening in systematic reviews. What are the main findings of this review? What studies are included? This review includes 19 studies that evaluated NLP techniques for automating abstract screening in systematic reviews, rapid reviews, scoping reviews, and other evidence syntheses. Studies came from diverse global regions, with 68.4% published in 2023 or later. Studies varied in design and corpus size (hundreds to tens of thousands of articles), mostly from medical literature, and demonstrated generally good methodological quality. Do NLP techniques reduce workload while maintaining accuracy? NLP techniques consistently demonstrate substantial workload reductions while maintaining high recall of relevant studies. Workload reductions range from 13-96%, with most studies achieving reductions of 30-60%. Most studies achieve recall rates exceeding 90%, meaning they successfully identify over 90% of relevant articles. Precision varied widely (10-99%), primarily affecting the volume of articles requiring manual review rather than the risk of missing relevant studies. Which NLP approaches perform best? Deep learning models, particularly those leveraging transfer learning with large pretrained language models like BERT and its variants (BioBERT, PubMedBERT), consistently outperform traditional machine learning approaches. Traditional approaches such as Support Vector Machines perform well but are generally outperformed by these modern architectures. What factors affect implementation feasibility? Several key factors influence the practical implementation of NLP systems. High-quality training data and specialist technical expertise are prerequisites. Computational resources vary from standard computing for simpler models to specialized GPU infrastructure for advanced deep learning approaches. User-friendly interfaces and domain generalizability remain key challenges for broader adoption. What do the findings of this review mean? NLP offers substantial promise for reducing the abstract screening burden. Workload reductions of 30-90% could accelerate evidence synthesis and policy translation. However, successful implementation requires careful planning, technical expertise, and adequate computational resources. Standardized datasets, user-friendly tools, and clearer best-practice guidance are needed to realise this potential. How up-to-date is this review? The review authors searched for studies up to December 2024.
Point-of-care ultrasound (POCUS) improves patient care by expedited diagnosis and safer procedures. Despite POCUS benefits, some clinicians, including emergency physicians, do not readily use POCUS. The study objective identified barriers and facilitators to clinical POCUS use and performed an intervention to address these barriers. A prospective cohort study at a single academic hospital included emergency department attendings, residents and advanced practice providers (APPs). Participants were surveyed on perceived POCUS use barriers and facilitators (primary outcome). A multifaceted intervention from December 2023 to January 2024 addressed identified barriers and involved: in-person POCUS education during shift by ultrasound faculty, clinical POCUS workflow demonstration during resident conference/faculty meetings and QR code reference files on machines. 42/99 participants (42.4%) responded to surveys preintervention and 28 postintervention (28.3%). 56 physicians and APPs participated in the in-person POCUS intervention (17 attendings, 34 residents, 5 APPs). Perceived POCUS barriers were time constraints on shift; internet/connectivity problems and losing saved images; forgetting to finish exam worksheets online; images not uploading into Butterfly cloud by the end of shift and residents performing 'phantom scans'. Perceived POCUS facilitators included clear documentation protocols, hands-on teaching sessions and incentives for completing scans. Comfort in teaching diagnostic and procedural POCUS improved pre to postintervention but did not change for performing POCUS. Identified barriers and facilitators were incorporated into a multifaceted intervention to improve clinical POCUS workflow processes. Future individualised interventions for low POCUS users and institutional initiatives with POCUS champions can be studied for improved patient care.
Immune exclusion in cold tumors is a major mechanism of immunotherapy resistance, and TGF-β signaling acts as a key orchestrator of this process. The clinical development of TGF-β/PD-(L)1 dual-targeting agents has seen both setbacks and breakthroughs, and a critical examination of this strategy is therefore timely and translationally relevant. This work summarizes the mechanisms by which TGF-β drives immune exclusion through stromal remodeling, metabolic suppression, and immune cell regulation. It systematically analyzes preclinical and clinical evidence on bifunctional fusion proteins, represented by M7824 and SHR-1701, as well as bispecific antibodies. Key translational challenges, including therapeutic window constraints, biomarker development, and indication selection, are discussed. The literature search covered PubMed and major oncology conference proceedings on TGF-β/PD-(L)1 dual blockade. The success of TGF-β-targeted therapy depends on moving beyond broad pathway inhibition toward biomarker-guided patient selection and context-dependent intervention. Spatially or biologically restricted targeting, multi-parametric biomarker frameworks, and mechanism-driven combination regimens are likely to define the next phase of clinical development in this field.
Acupuncture is increasingly recognised as an effective treatment for chronic pain conditions, yet inter-individual variability in treatment response remains a major clinical challenge. Recent neuroimaging studies suggest that baseline brain characteristics may serve as objective biomarkers for predicting therapeutic outcomes, with some achieving classification accuracies exceeding 80%. These findings, however, have not been systematically synthesised. This review will be the first to systematically evaluate whether pre-treatment neuroimaging biomarkers can predict acupuncture treatment response in adults with chronic pain. This protocol is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. We will search MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PubMed, Web of Science and four Chinese databases (China National Knowledge Infrastructure, Wanfang, VIP and CBM) from inception to the search date without date restrictions. Eligible studies must include adults with chronic pain (≥3 months duration), baseline neuroimaging assessment (functional MRI, structural MRI, positron emission tomography (PET) or single-photon emission computed tomography (SPECT)) and needle-based acupuncture intervention with post-treatment clinical outcomes. Two reviewers will independently screen studies, extract data and assess risk of bias using the Prediction model Risk Of Bias ASsessment Tool, Cochrane Risk of Bias 2.0 and Newcastle-Ottawa Scale. Primary outcomes include predictive performance metrics (accuracy, sensitivity, specificity, area under the curve) and identification of specific brain regions with predictive value. Meta-analysis will be performed using random-effects models when sufficient homogeneous studies are available. Where studies classify responders versus non-responders, diagnostic test accuracy meta-analysis (bivariate/hierarchical summary receiver operating characteristic (ROC models)) will pool sensitivity and specificity. Coordinate-based meta-analysis using activation likelihood estimation will be conducted if 10 or more studies report stereotactic coordinates. The completed review will be reported following the PRISMA 2020 statement. Ethical approval is not required as this study involves secondary analysis of published data. Findings will be disseminated through peer-reviewed publication and conference presentations. Results are expected to support the development of neuroimaging-based clinical decision tools and to guide future biomarker validation studies. CRD420261290372.
Falls affect approximately one-third of community-dwelling adults aged 65 years and older annually, with healthcare costs exceeding US$80 billion in the USA alone. Home-based fall detection technologies have proliferated, yet cost-effectiveness evidence remains fragmented. To systematically identify, appraise and synthesise evidence on the cost-effectiveness of home-based fall detection and monitoring technologies for community-dwelling older adults. This protocol is reported following Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. Searches will be conducted across MEDLINE, Embase, Cochrane Library, CINAHL, Web of Science and economic databases from database inception to the date the searches are executed. Two reviewers will independently screen studies using Covidence, extract data and assess quality using Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 and Drummond checklists. Narrative synthesis with meta-analysis where appropriate will be employed. Ethical approval is not required as this systematic review will analyse only previously published, aggregate data and will not involve primary data collection from human participants. Findings will be disseminated through peer-reviewed open-access publication, conference presentations and accessible formats developed with patient and caregiver advocacy organisations. The protocol is registered with PROSPERO (CRD420261433029).
As humans, we bring biases based on our own vertebrate, mammalian biology into the way we conceptualize the world. This includes how we discuss the range of concepts we reference with the term sex and the implicit assumptions that are often embedded in how we discuss life cycles and reproduction. These assumptions situate diplontic life cycles, unitary body plans, and amphigonic reproduction as normative and frame sex (meiosis and syngamy) and reproduction (the creation of new individuals) as inherently intertwined. We draw from the social science theoretical framework of master narrative theory to discuss these implicit assumptions. Master narrative theory typically is used to articulate normative expectations for humans in specific socio-cultural contexts. Here we use it to reveal normative expectations about organisms that are common in western modern science. Following this explication, we discuss frameworks and language that biologists working with modular metazoans and plants have developed to discuss complex sexual variation, addressing multi-level modularity and continuous, quantitative variation in investment into or reproductive success via male and female gametes. We consider ways these "specialized" approaches can be useful for broadly comparative work, across organisms with a range of sexual simplicity and complexity, and identify challenges to greater conceptual integration. As a step toward tools for improving conceptual integration across sexual systems and body plans, we introduce a graphical system for mapping anisogamete-production strategy across levels of modularity. We call for further conversations that build on the "Sex Across Origins" symposium at the 2026 Society for Integrative Biology conference, considering key concepts in the biology of sex and reproduction through the prism of different kinds of organisms. This practice can help break apart common oversimplifications and overgeneralizations, reveal the breadth or limits of concepts, and generate insights from the ways that concepts fail for subsets of organisms, suggesting paths forward to better understand and articulate the complexity and variation of sex and reproduction.
Hearing aids (HAs) can alleviate hearing loss; however, HA rehabilitation is frequently hampered by delayed diagnosis, suboptimal fitting and lack of systematic follow-up. Although the association between hearing loss and cognitive decline has been identified, evidence from randomised controlled trials remains limited. Addressing these gaps is essential for reducing hearing loss-related experiences and evaluating whether effective HA use could reduce the risk of cognitive decline. The healthy hearing for healthy ageing study is a proof-of-concept, single-site, two-arm parallel-group 12-month randomised controlled trial with a 12-month extended follow-up. Up to two hundred participants with hearing loss and without cognitive decline referred for an initial HA rehabilitation are recruited and randomised 1:1 to either data-driven hearing rehabilitation or standard care. The primary outcome is the change in two speech perception in noise tests validated for the Finnish language: the Finnish matrix sentence test and the digits-in-noise test. The secondary outcomes are patient-reported outcomes (eg, Hearing in Real-Life Environment and Speech, Spatial and Quality questionnaires), quality of life (eg, 15D-questionnaire), cognitive (eg, Consortium to Establish a Registry for Alzheimer's Disease test) and psychosocial measures. Exploratory outcomes include event-related responses, cortical auditory evoked potentials, structural brain imaging and vision-related measures. Ethical approval has been obtained from the Regional Medical Research Ethics Committee of the well-being Services County of North Savo (approval no. 697/2023). Findings from this study will be disseminated through peer-reviewed publications, conference presentations and relevant clinical and patient communities. NCT06495268.
Stroke is a leading cause of mortality and morbidity in the United States and worldwide. Unfortunately, stroke deaths and disabilities continue to disproportionately affect minority populations and those living in rural areas. The social determinants of health also have a tremendous impact on the outcomes of stroke prevention and disease. There are gaps in provider awareness and confidence in recognizing how health disparities affect stroke outcomes, highlighting the ongoing need to strengthen understanding and capacity to address these disparities. By increasing awareness of the impact of health disparities, stroke outcomes can improve. Stroke coordinators from the Minnesota Statewide Stroke System were invited to participate in an Evidence-Based Practice project to increase their confidence in understanding the impact health care disparities have on stroke outcomes. The education for this project was in the form of informal discussions (dubbed "coffee talks") on the topic of health care disparities. Video segments from the American Heart Association International Stroke Conference 2023 were used as the catalyst for conversation. After 4 discussion sessions, the stroke coordinators were questioned with a retrospective survey on the pre- and post-discussion confidence of their knowledge of the impact of health disparities on stroke outcomes. A survey was deployed after the last discussion date to 89 stroke coordinators within the Minnesota Stroke System. Of the 89 stroke coordinators, 15 responded to the survey; 9 attended the coffee talks. The 9 stroke coordinators reported an increase in confidence in understanding the impact of health disparities on stroke outcomes. The respondents were also able to articulate how they would use the knowledge from the discussions in their place of work. Informal discussions may be an effective way to improve knowledge of health care disparities.
Objective: To review the emerging evidence supporting the use of nerandomilast (Jascayd), a selective phosphodiesterase-4B (PDE4B) inhibitor, for the treatment of idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF). The review aims to summarize its mechanism of action, efficacy, safety, and potential role as monotherapy or in combination with existing antifibrotic therapies. Data Sources: A literature search was conducted using PubMed, Embase, ClinicalTrials.gov, and relevant conference proceedings from January 2018 through December 2025. Search terms included nerandomilast, BI 1015550, Jascayd, phosphodiesterase-4B inhibitor, idiopathic pulmonary fibrosis, progressive pulmonary fibrosis, interstitial lung disease, FIBRONEER-IPF, and FIBRONEER-ILD. Human studies published in English were included. Study Selection and Data Extraction: Original clinical studies, phase II and phase III trials, subgroup analyses, and regulatory publications evaluating nerandomilast in patients with IPF or PPF were reviewed. Studies were selected based on relevance to efficacy, safety, mechanism of action, and clinical outcomes. Data regarding study design, patient population, forced vital capacity (FVC) outcomes, adverse events, and concomitant antifibrotic use were extracted and qualitatively synthesized. Data Synthesis: Nerandomilast was approved in October 2025 for the treatment of IPF and PPF, representing the first PDE4B inhibitor approved for fibrotic lung disease. By inhibiting PDE4B, nerandomilast increases intracellular cyclic adenosine monophosphate (cAMP) levels, resulting in reduced inflammatory cytokine production and decreased fibroblast activation. Clinical trials, including the phase III FIBRONEER-IPF study, demonstrated a significant reduction in the rate of FVC decline compared with placebo, indicating attenuation of disease progression. Benefits were observed both in patients receiving nerandomilast alone and in those receiving background antifibrotic therapy with pirfenidone or nintedanib. Overall, nerandomilast demonstrated a favorable benefit-risk profile and offers a mechanistically distinct approach compared with currently available antifibrotic agents. Conclusions: Nerandomilast provides a novel anti-inflammatory and antifibrotic treatment option for patients with IPF and PPF. Available evidence suggests meaningful reductions in lung function decline with acceptable tolerability, including use alongside established antifibrotic therapies. As longer-term and real-world data emerge, nerandomilast may become an important component of the therapeutic strategy for progressive fibrotic lung diseases.
Objectives The COVID-19 pandemic disrupted in-person medical school teaching, and certain parts of the curriculum were disproportionately affected, including traditional hands-on training in point-of-care ultrasound (POCUS). It is challenging to find interactive methods for teaching POCUS while conveying image acquisition techniques via online video-conference platforms for distance learning. Our objective was to evaluate the effectiveness and learners perceptions of POCUS gamification distance learning. Methods This was a cross-sectional study at an academic center. Study participants were third-year medical students (MS3) with minimal ultrasound experience. A pre-test was administered. Point-of-care ultrasound (POCUS) fellowship-trained emergency medicine (EM) faculty gave an online 1-h review lecture on basic POCUS applications and ran an online POCUS Pictionary session, where a student was randomly chosen to illustrate a POCUS topic. After each turn, the instructor reviewed teaching points. Students completed a post-test and survey. Descriptive statistics were used to summarize the data. Survey responses were reported as percentages of total respondents with 95% confidence intervals, and a two-sample t-test was performed to determine the statistical significance of pre- and post-test performances. Results A total of 73 students completed the pre-test, post-test, and survey. The average pre-test score was 53.3% (±15.9%), and the post-test score was 84.0% (±13.2%). Performance improvement was statistically significant (p<0.001). Before the sessions, students had the lowest familiarity with Extended Focused Assessment with Sonography in Trauma (eFAST), peripheral nerves, and soft-tissue ultrasound. After the sessions, the majority of students reported being more confident in performing almost all the reviewed applications. The vast majority (90.4%) stated that if possible, they would prefer in-person hands-on sessions for POCUS training. Conclusion Medical students' POCUS knowledge improved significantly after a didactics session and a gamified point-of-care ultrasound distance-learning session. Although the sessions increased their confidence in image acquisition and interpretation, students preferred in-person, hands-on training and practice when given the opportunity.
We conducted a systematic review and meta-analysis to compare the effectiveness of shunts with and without anti-siphon devices (ASDs) or other flow-regulating systems in preventing cerebrospinal fluid (CSF) overdrainage and its associated complications. Following established guidelines, we searched PubMed, Embase, Scopus, Cochrane, and Web of Science for clinical studies evaluating adult patients diagnosed with NPH who underwent CSF shunting with ASDs or flow-regulating valves, and included a control group of patients with standard CSF shunts lacking such mechanisms. Non-English studies, conference abstracts, and case reports were ineligible. We included seven studies with 928 patients. Although most outcomes showed no statistically significant difference between the intervention and control groups, ASDs had reduced incidences of subdural hygroma (OR = 0.33; p = 0.0368) and subdural hematoma (RR = 0.35; p = 0.0014), indicating a clear benefit in preventing these adverse events. ASDs significantly reduced the development of subdural hygroma and subdural hematoma, playing a vital role in preventing neurological sequelae.
To identify and examine evaluation methods and metrics used for specialist cancer nursing. A scoping review of published and grey literature on evaluation approaches for specialist cancer nursing roles and models of care. Comprehensive searches were conducted across CINAHL, Cochrane Library, Medline, PsycINFO and Google Scholar for English-language published and grey literature published between January 2014 and November 2025. Two reviewers independently screened and extracted data. Findings were synthesised narratively and mapped to the Strong Model of Advanced Practice Nursing and Quintuple Aim. Of 3360 records screened, 23 sources met the inclusion criteria: 14 published articles, and 9 grey literature sources (conference abstracts, theses, textbooks). Most sources originated from the USA (n = 12, 52%) or high-income countries (n = 22, 96%), and focused on nurse navigator roles (n = 9, 39%). Five themes emerged in the sources: (1) purpose of evaluation; (2) development of methods and metrics; (3) selection and implementation; (4) data collection approaches; and (5) challenges and considerations. Evaluation was primarily used to demonstrate value and drive quality improvement through pragmatic methods. Metrics varied widely and were concentrated in the Strong Model domains of Direct Comprehensive Care and Support of Systems, with fewer addressing Education, Research and Professional Leadership. Key challenges to evaluation included role variability and lack of standardised tools. Despite the lack of standardised evaluation practices for specialist cancer nursing, the five themes synthesised in this review can guide evaluation of specialist cancer nursing roles and models of care in real-world settings. Opportunity exists for international collaboration to develop a comprehensive, context-sensitive set of metrics, relevant in diverse healthcare settings, that capture both excellence in service delivery and nursing scholarship. What problem did the review address? ○ Specialist cancer nurses perform a diverse range of interventions and roles that are complex in nature, leading to challenges in their accurate evaluation. ○ Effective and efficient approaches to evaluation of specialist cancer nursing roles are crucial to demonstrate their value. ○ A significant body of literature has demonstrated the efficacy of specialist cancer nursing roles and models of care in a research framework; however, evaluation is needed to better understand the impact of translating this evidence into real-world settings. What were the main findings? ○ A scoping review exploring evaluation methods and metrics of specialist cancer nursing revealed five key themes: (1) purpose of evaluation; (2) development of evaluation methods and metrics; (3) selection and implementation of evaluation methods and metrics; (4) methods of data collection; and (5) challenges and considerations. ○ Evaluation of specialist cancer nursing is important, however variation in nurses' roles and responsibilities and lack of standardised measurement tools were key challenges. ○ Evaluation metrics varied widely and were specific to specialist cancer nursing roles; predominantly reported under the domains of Direct Comprehensive Care and Support of Systems, with fewer reported under Education, Research and Professional Leadership. Where and on whom will the research have an impact? ○ Nursing and health service leaders can use the identified themes and subthemes as a framework to guide evaluation of specialist cancer nursing. The predominance of English-language and high-income country evidence limits the global applicability of these findings. ○ Gaps in knowledge can drive the future work of cancer nursing organisations to collaboratively develop a comprehensive list of evaluation metrics that can be contextualised for specific roles across diverse health care settings. ○ Specialist cancer nurses in all roles and models of care should have metrics for Research, Leadership and Professional Leadership to support the scholarship of nursing. ○ Consistent national role definitions, shared competency frameworks and standardised outcome measures should be embedded in policy and commissioning to enable systematic evaluation, appropriate resourcing, and integration into workforce and service planning of specialist cancer nurses. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews PRISMA-ScR checklist. Employees of a cancer patient advocacy group were involved in the design of the study, interpretation of the data and the preparation of the manuscript. No patients were involved in the conduct of this scoping review.