Baseline health parameters of rhinoceros auklets (Cerorhinca monocerata) using serum protein electrophoresis, acute phase proteins, and biochemistry.

Clinical metrics of baseline health in sentinel seabird species can offer insight into marine ecosystem dynamics, individual and population health, and assist in wildlife rehabilitation and conservation efforts. Protein electrophoresis is useful for detecting changes in acute phase proteins and immunoglobulin levels that may indicate subtle inflammatory responses and/or infectious disease. Serum biochemistry can highlight nutritional status, metabolic derangements, and organ injury and function. However, baseline values for such health parameters are largely unknown for many seabird species. Therefore, the objective of this study is to establish baseline clinical health reference intervals for serum protein electrophoresis, acute phase proteins including serum amyloid A and haptoglobin, and biochemistry parameters in the rhinoceros auklet (Cerorhinca monocerata), a key sentinel species in the North Pacific. From 2013 to 2019, 178 wild, apparently healthy breeding adult rhinoceros auklets were captured across four breeding colonies in British Columbia, Canada (Lucy Island, Pine Island, Triangle Islands, and SGang Gwaay) and from one colony in Washington, United States (Protection Island). Reference intervals were calculated for protein electrophoresis fractions and acute phase proteins (n = 163), and serum biochemistry (n = 35) following established guidelines by the American Society of Veterinary Clinical Pathology. Animals were also assessed for the presence of antibodies to the influenza A virus. Approximately 48% (70/147) of sampled birds were seropositive for influenza A virus, with a prevalence of 50% (6/12) in 2013, 75% (47/63) in 2014, and 24% (17/72) in 2019. This work provides clinical baseline health metrics of a key North Pacific sentinel species to help inform marine ecosystem monitoring, recovery, and rehabilitation efforts in the Pacific Northwest.

At the break point: What needs to change for antimicrobial stewardship program pharmacists?

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Improved Electrosynthesis of Biomass Derived Furanic Compounds via Nitroxyl Radical Redox Mediation.

Biomass is an abundantly available, underutilized feedstock for the production of bulk and fine chemicals, polymers, and sustainable and biodegradable plastics that are traditionally sourced from petrochemicals. Among potential feedstocks, 2,5-furan dicarboxylic acid (FDCA) stands out for its potential to be converted to higher-value polymeric materials such as polyethylene furandicarboxylate (PEF), a bio-based plastic alternative. In this study, the sustainable, electrocatalytic oxidation of stable furan molecule 2,5-bis(hydroxymethyl)furan (BHMF) to FDCA is investigated using a variety of TEMPO derivative electrocatalysts in a mediated electrosynthetic reaction. Three TEMPO catalysts (acetamido-TEMPO, methoxy-TEMPO, and TEMPO) facilitate full conversion to FDCA in basic conditions with >90% yield and >100% Faradaic efficiency. The remaining three TEMPO catalysts (hydroxy-TEMPO, oxo-TEMPO, and amino-TEMPO) all perform intermediate oxidation of BHMF in basic conditions but do not facilitate full conversion to FDCA. On the basis of pH studies completed on all TEMPO derivatives to assess their electrochemical reversibility and response to substrate, pH and reversibility play significant roles in the catalytic ability of each catalyst, which directly influences catalyst turnover and product formation. More broadly, this study also highlights the importance of an effective and rapid electroanalytical workflow in mediated electrosynthetic reactions, demonstrating how voltammetric catalyst screening can serve as a useful tool for predicting the reactivity and efficacy of a catalyst-substrate electrochemical system.

Time to positivity of blood cultures in a level IV NICU varies based on organism category and population subgroups: is a 36-hour rule out safe?

BACKGROUND: Time to positivity (TTP) of blood cultures and organism characteristics may be different in a Level IV NICU population. METHODS: Retrospective study of 309 Level IV NICU positive blood cultures between January 2012 to December 2018 describing TTP and organism characteristics. RESULTS: Median TTP [IQR] was 21.1 [14.3, 25.2] hours, with 91.2% positive at 36 h, and 96.1% positive at 48 h. Gram negative definite pathogens had the shortest TTP (13.0 [11.4, 15.4] hours) compared to gram positive definite pathogens (16.3 [13.0, 22.4] hours). TTP for treated gram positive commensal organisms (22.3 [20.1, 30.4] hours) and those considered contaminants (23.6 [21.4, 26.0] hours), was significantly longer than both gram positive and negative definite pathogens. CONCLUSION: When antimicrobials are initiated due to concern for bacteremia and blood cultures have not identified a causative pathogen at 36 h, antimicrobials may be safely discontinued in the majority of Level IV NICU patients.

ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.

Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures.

BACKGROUND: Descending thoracic aortic aneurysms and dissections can go undetected until severe and catastrophic, and few clinical indices exist to screen for aneurysms or predict risk of dissection. METHODS: This study generated a plasma proteomic dataset from 75 patients with descending type B dissection (Type B) and 62 patients with descending thoracic aortic aneurysm (DTAA). Standard statistical approaches were compared to supervised machine learning (ML) algorithms to distinguish Type B from DTAA cases. Quantitatively similar proteins were clustered based on linkage distance from hierarchical clustering and ML models were trained with uncorrelated protein lists across various linkage distances with hyperparameter optimization using fivefold cross validation. Permutation importance (PI) was used for ranking the most important predictor proteins of ML classification between disease states and the proteins among the top 10 PI protein groups were submitted for pathway analysis. RESULTS: Of the 1,549 peptides and 198 proteins used in this study, no peptides and only one protein, hemopexin (HPX), were significantly different at an adjusted p < 0.01 between Type B and DTAA cases. The highest performing model on the training set (Support Vector Classifier) and its corresponding linkage distance (0.5) were used for evaluation of the test set, yielding a precision-recall area under the curve of 0.7 to classify between Type B from DTAA cases. The five proteins with the highest PI scores were immunoglobulin heavy variable 6-1 (IGHV6-1), lecithin-cholesterol acyltransferase (LCAT), coagulation factor 12 (F12), HPX, and immunoglobulin heavy variable 4-4 (IGHV4-4). All proteins from the top 10 most important groups generated the following significantly enriched pathways in the plasma of Type B versus DTAA patients: complement activation, humoral immune response, and blood coagulation. CONCLUSIONS: We conclude that ML may be useful in differentiating the plasma proteome of highly similar disease states that would otherwise not be distinguishable using statistics, and, in such cases, ML may enable prioritizing important proteins for model prediction.

The role of governance in shaping health system reform: a case study of the design and implementation of new health regions in Ireland, 2018-2023.

BACKGROUND: Effective governance arrangements are central to the successful functioning of health systems. While the significance of governance as a concept is acknowledged within health systems research, its interplay with health system reform initiatives remains underexplored in the literature. This study focuses on the development of new regional health structures in Ireland in the period 2018-2023, one part of a broader health system reform programme aimed at greater universalism, in order to scrutinise how aspects of governance impact on the reform process, from policy design through to implementation. METHODS: This qualitative, multi-method study draws on document analysis of official documents relevant to the reform process, as well as twelve semi-structured interviews with key informants from across the health sector. Interviews were analysed according to thematic analysis methodology. Conceiving governance as comprising five domains (Transparency, Accountability, Participation, Integrity, Capacity) the research uses the TAPIC framework for health governance as a conceptual starting point and as initial, deductive analytic categories for data analysis. RESULTS: The analysis reveals important lessons for policymakers across the five TAPIC domains of governance. These include deficiencies in accountability arrangements, poor transparency within the system and vis-à-vis external stakeholders and the public, and periods during which a lack of clarity in terms of roles and responsibilities for various process and key decisions related to the reform were identified. Inadequate resourcing of implementation capacity, competing policy visions and changing decision-making arrangements, among others, were found to have originated in and continuously reproduced a lack of trust between key institutional actors. The findings highlight how these challenges can be addressed through strengthening governance arrangements and processes. Importantly, the research reveals the interwoven nature of the five TAPIC dimensions of governance and the need to engage with the complexity and relationality of health system reform processes. CONCLUSIONS: Large scale health system reform is a complex process and its governance presents distinct challenges and opportunities for stakeholders. To understand and be able to address these, and to move beyond formulaic prescriptions, critical analysis of the historical context surrounding the policy reform and the institutional relationships at its core are needed.

Mariner: explore the Hi-Cs.

MOTIVATION: 3D chromatin structure plays an important role in regulating gene expression and alterations to this structure can result in developmental abnormalities and disease. While genomic approaches like Hi-C and Micro-C can provide valuable insights in 3D chromatin architecture, the resulting datasets are extremely large and difficult to manipulate. RESULTS: Here, we present mariner, a rapid and memory efficient tool to extract, aggregate, and plot data from Hi-C matrices within the R/Bioconductor environment. Mariner simplifies the process of querying and extracting contacts from multiple Hi-C files using a parallel and block-processing approach. Modular functions allow complete workflow customization for advanced users, yet all-in-one functions are available for running the most common types of analyses. Finally, tight integration with existing Bioconductor infrastructure enables complete analysis and visualization of Hi-C data in R. AVAILABILITY AND IMPLEMENTATION: Available on GitHub at https://github.com/EricSDavis/mariner and on Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/mariner.html.

Frontline Providers' and Patients' Perspectives on Improving Diagnostic Safety in the Emergency Department: A Qualitative Study.

BACKGROUND: Few studies have described the insights of frontline health care providers and patients on how the diagnostic process can be improved in the emergency department (ED), a setting at high risk for diagnostic errors. The authors aimed to identify the perspectives of providers and patients on the diagnostic process and identify potential interventions to improve diagnostic safety. METHODS: Semistructured interviews were conducted with 10 ED physicians, 15 ED nurses, and 9 patients/caregivers at two separate health systems. Interview questions were guided by the ED-Adapted National Academies of Sciences, Engineering, and Medicine Diagnostic Process Framework and explored participant perspectives on the ED diagnostic process, identified vulnerabilities, and solicited interventions to improve diagnostic safety. The authors performed qualitative thematic analysis on transcribed interviews. RESULTS: The research team categorized vulnerabilities in the diagnostic process and intervention opportunities based on the ED-Adapted Framework into five domains: (1) team dynamics and communication (for example, suboptimal communication between referring physicians and the ED team); (2) information gathering related to patient presentation (for example, obtaining the history from the patients or their caregivers; (3) ED organization, system, and processes (for example, staff schedules and handoffs); (4) patient education and self-management (for example, patient education at discharge from the ED); and (5) electronic health record and patient portal use (for example, automatic release of test results into the patient portal). The authors identified 33 potential interventions, of which 17 were provider focused and 16 were patient focused. CONCLUSION: Frontline providers and patients identified several vulnerabilities and potential interventions to improve ED diagnostic safety. Refining, implementing, and evaluating the efficacy of these interventions are required.

Cefadroxil and cephalexin pharmacokinetics and pharmacodynamics in children with musculoskeletal infections.

Cephalexin, a first-generation cephalosporin, is the first-line oral therapy for children with musculoskeletal infections due to methicillin-susceptible Staphylococcus aureus (MSSA). Cefadroxil, a similar first-generation cephalosporin, is an attractive alternative to cephalexin given its longer half-life. In this study, we describe the comparative pharmacokinetics (PK) and pharmacodynamics (PD) of cephalexin and cefadroxil in children with musculoskeletal infections. Children aged 6 months to 18 years with a musculoskeletal infection were enrolled in a prospective, open-label, crossover PK study and given single oral doses of cefadroxil (50-75 mg/kg up to 2,000 mg) and cephalexin (50 mg/kg up to 1,375 mg). Population PK models were developed and used for dosing simulations. Our primary PD target was the achievement of free antibiotic concentrations above the minimum inhibitory concentration (fT >MIC) for 40% of the day for MICs ≤ 4 mg/L. PK of cephalexin (n = 15) and cefadroxil (n = 14) were best described using a one-compartment, first-order absorption model, with a lag time component for cefadroxil. PK parameters were notable for cefadroxil's longer half-life (1.61 h) than cephalexin's (1.10 h). For pediatric weight bands, our primary PD target was achieved by cephalexin 25 mg/kg/dose, maximum 750 mg/dose, administered three times daily and cefadroxil 40 mg/kg/dose, maximum 1,500 mg/dose, administered twice daily. More aggressive dosing was required to achieve higher PD targets. Among children with musculoskeletal infections, oral cephalexin and cefadroxil achieved PD targets for efficacy against MSSA. Given less frequent dosing, twice-daily cefadroxil should be further considered as an alternative to cephalexin for oral step-down therapy for serious infections due to MSSA.

Developing medical simulations for opioid overdose response training: A qualitative analysis of narratives from responders to overdoses.

Medical simulation offers a controlled environment for studying challenging clinical care situations that are difficult to observe directly. Overdose education and naloxone distribution (OEND) programs aim to train potential rescuers in responding to opioid overdoses, but assessing rescuer performance in real-life situations before emergency medical services arrive is exceedingly complex. There is an opportunity to incorporate individuals with firsthand experience in treating out-of-hospital overdoses into the development of simulation scenarios. Realistic overdose simulations could provide OEND programs with valuable tools to effectively teach hands-on skills and support context-sensitive training regimens. In this research, semi-structured interviews were conducted with 17 individuals experienced in responding to opioid overdoses including emergency department physicians, first responders, OEND program instructors, and peer recovery specialists. Two coders conducted qualitative content analysis using open and axial thematic coding to identify nuances associated with illicit and prescription opioid overdoses. The results are presented as narrative findings complemented by summaries of the frequency of themes across the interviews. Over 20 hours of audio recording were transcribed verbatim and then coded. During the open and axial thematic coding process several primary themes, along with subthemes, were identified, highlighting the distinctions between illicit and prescription opioid overdoses. Distinct contextual details, such as locations, clinical presentations, the environment surrounding the patient, and bystanders' behavior, were used to create four example simulations of out-of-hospital overdoses. The narrative findings in this qualitative study offer context-sensitive information for developing out-of-hospital overdose scenarios applicable to simulation training. These insights can serve as a valuable resource, aiding instructors and researchers in systematically creating evidence-based scenarios for both training and research purposes.

Human Factors Contributing to Infection Prevention in Outpatient Hemodialysis Centers: A Mixed Methods Study.

RATIONALE & OBJECTIVE: Infection prevention efforts in dialysis centers can avert patient morbidity and mortality but are challenging to implement. The objective of this study was to better understand how the design of the work system might contribute to infection prevention in outpatient dialysis centers. STUDY DESIGN: Mixed methods, observational study. SETTING & PARTICIPANTS: Six dialysis facilities across the United States visited by a multidisciplinary team over 8 months. ANALYTICAL APPROACH: At each facility, structured macroergonomic observations were undertaken by a multidisciplinary team using the SEIPS 1.0 model. Ethnographic observations were collected about staff encounters with dialysis patients including the content of staff conversations. Selective and axial coding were used for qualitative analysis and quantitative data were reported using descriptive statistics. RESULTS: Organizational and sociotechnical barriers and facilitators to infection prevention in the outpatient dialysis setting were identified. Features related to human performance, (eg, alarms, interruptions, and task stacking), work system design (eg, physical space, scheduling, leadership, and culture), and extrinsic factors (eg, patient-related characteristics) were identified. LIMITATIONS: This was an exploratory evaluation with a small sample size. CONCLUSIONS: This study used a systematic macroergonomic approach in multiple outpatient dialysis facilities to identify infection prevention barriers and facilitators related to human performance. Several features common across facilities were identified that may influence infection prevention in outpatient care and warrant further exploration.

NPEPPS Is a Druggable Driver of Platinum Resistance.

There is an unmet need to improve the efficacy of platinum-based cancer chemotherapy, which is used in primary and metastatic settings in many cancer types. In bladder cancer, platinum-based chemotherapy leads to better outcomes in a subset of patients when used in the neoadjuvant setting or in combination with immunotherapy for advanced disease. Despite such promising results, extending the benefits of platinum drugs to a greater number of patients is highly desirable. Using the multiomic assessment of cisplatin-responsive and -resistant human bladder cancer cell lines and whole-genome CRISPR screens, we identified puromycin-sensitive aminopeptidase (NPEPPS) as a driver of cisplatin resistance. NPEPPS depletion sensitized resistant bladder cancer cells to cisplatin in vitro and in vivo. Conversely, overexpression of NPEPPS in sensitive cells increased cisplatin resistance. NPEPPS affected treatment response by regulating intracellular cisplatin concentrations. Patient-derived organoids (PDO) generated from bladder cancer samples before and after cisplatin-based treatment, and from patients who did not receive cisplatin, were evaluated for sensitivity to cisplatin, which was concordant with clinical response. In the PDOs, depletion or pharmacologic inhibition of NPEPPS increased cisplatin sensitivity, while NPEPPS overexpression conferred resistance. Our data present NPEPPS as a druggable driver of cisplatin resistance by regulating intracellular cisplatin concentrations. SIGNIFICANCE: Targeting NPEPPS, which induces cisplatin resistance by controlling intracellular drug concentrations, is a potential strategy to improve patient responses to platinum-based therapies and lower treatment-associated toxicities.

The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies.

BACKGROUND: Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging. OBJECTIVE: Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies. METHODS: We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types. RESULTS: Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (ß = < 0.0001, 95% CI: 0.0000, 0.0000; ß = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small ß values represent no 'measurable real-world' associations. When stratified by type, we observed no strong associations between greenspace and EVI. IMPACT: It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a 'gold standard' vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.

Clinical Outcomes Associated with Amoxicillin Treatment for Acute Otitis Media in Children.

BACKGROUND: Acute otitis media (AOM) is the most common reason children are prescribed antibiotics. Bacteria that produce beta-lactamase are an increasingly frequent cause of AOM and may be resistant to amoxicillin, the currently recommended treatment for AOM. We aimed to evaluate the clinical outcomes of children treated with amoxicillin for AOM and assessed whether outcomes vary by infecting pathogen or beta-lactamase production. METHODS: 205 children 6-35 months old diagnosed with AOM and prescribed amoxicillin were included. Bacterial culture and qualitative multiplex real-time polymerase chain reaction were performed on nasopharyngeal swabs collected at enrollment. Parents completed surveys assessing symptoms, antibiotic adherence, and potential adverse events. The primary outcome was treatment failure with amoxicillin. Secondary outcomes included recurrence, symptom improvement, resolution, and adverse drug events (ADE). RESULTS: 8 children (5.4%) experienced treatment failure and 14 (6.8%) had recurrence. By day 5, 152 (74.1%) children had symptom improvement and 97 (47.3%) had resolution. Parents reported ADE for 56 (27.3%) children. Among 149 children who did not take any amoxicillin before enrollment, 98 (65.8%) had one or more beta-lactamase-producing bacteria. Common bacterial otopathogens were Moraxella catarrhalis (79, 53.0%), Streptococcus pneumoniae (51, 34.2%), Haemophilus influenzae (30, 20.1%), and Staphylococcus aureus (21, 14.1%). Treatment failure did not differ between children that did (5, 5.1%) and did not (3, 5.9%) have beta-lactamase-producing otopathogens (p = .05). CONCLUSIONS: Among children diagnosed with AOM treated with amoxicillin, treatment failure was uncommon and did not differ by pathogen or beta-lactamase production. These data support guidance recommending amoxicillin despite an increasing prevalence of beta-lactamase-producing bacteria.

CAM3.0: determining cell type composition and expression from bulk tissues with fully unsupervised deconvolution.

MOTIVATION: Complex tissues are dynamic ecosystems consisting of molecularly distinct yet interacting cell types. Computational deconvolution aims to dissect bulk tissue data into cell type compositions and cell-specific expressions. With few exceptions, most existing deconvolution tools exploit supervised approaches requiring various types of references that may be unreliable or even unavailable for specific tissue microenvironments. RESULTS: We previously developed a fully unsupervised deconvolution method-Convex Analysis of Mixtures (CAM), that enables estimation of cell type composition and expression from bulk tissues. We now introduce CAM3.0 tool that improves this framework with three new and highly efficient algorithms, namely, radius-fixed clustering to identify reliable markers, linear programming to detect an initial scatter simplex, and a smart floating search for the optimum latent variable model. The comparative experimental results obtained from both realistic simulations and case studies show that the CAM3.0 tool can help biologists more accurately identify known or novel cell markers, determine cell proportions, and estimate cell-specific expressions, complementing the existing tools particularly when study- or datatype-specific references are unreliable or unavailable. AVAILABILITY AND IMPLEMENTATION: The open-source R Scripts of CAM3.0 is freely available at https://github.com/ChiungTingWu/CAM3/(https://github.com/Bioconductor/Contributions/issues/3205). A user's guide and a vignette are provided.

How and why do financial incentives contribute to helping people stop smoking? A realist review.

BACKGROUND: Tobacco smoking remains a key cause of preventable illness and death globally. In response, many countries provide extensive services to help people to stop smoking by offering a variety of effective behavioural and pharmacological therapies. However, many people who wish to stop smoking do not have access to or use stop smoking supports, and new modes of support, including the use of financial incentives, are needed to address this issue. A realist review of published international literature was undertaken to understand how, why, for whom, and in which circumstances financial incentives contribute to success in stopping smoking for general population groups and among pregnant women. METHODS: Systematic searches were undertaken from inception to February 2022 of five academic databases: MEDLINE (ovid), Embase.com, CIHAHL, Scopus and PsycINFO. Study selection was inclusive of all study designs. Twenty-two studies were included. Using Pawson and Tilley's iterative realist review approach, data collected were screened, selected, coded, analysed, and synthesised into a set of explanatory theoretical findings. RESULTS: Data were synthesised into six Context-Mechanism-Outcome Configurations and one overarching programme theory after iterative rounds of analysis, team discussion, and expert panel feedback. Our programme theory shows that financial incentives are particularly useful to help people stop smoking if they have a financial need, are pregnant or recently post-partum, have a high threshold for behaviour change, and/or respond well to external rewards. The incentives work through a number of mechanisms including the role their direct monetary value can play in a person's life and through a process of reinforcement where they can help build confidence and self-esteem. CONCLUSION: This is the first realist review to synthesise how, why, and for whom financial incentives work among those attempting to stop smoking, adding to the existing evidence demonstrating their efficacy. The findings will support the implementation of current knowledge into effective programmes which can enhance the impact of stop smoking care. PROSPERO REGISTRATION NUMBER: CRD42022298941.

Refining a Framework to Enhance Communication in the Emergency Department During the Diagnostic Process: An eDelphi Approach.

BACKGROUND: Emergency departments (EDs) are susceptible to diagnostic error. Suboptimal communication between the patient and the interdisciplinary care team increases risk to diagnostic safety. The role of communication remains underrepresented in existing diagnostic decision-making conceptual models. METHODS: The authors used eDelphi methodology, whereby data are collected electronically, to achieve consensus among an expert panel of 18 clinicians, patients, family members, and other participants on a refined ED-based diagnostic decision-making framework that integrates several potential opportunities for communication to enhance diagnostic quality. This study examined the entire diagnostic process in the ED, from prehospital to discharge or transfer to inpatient care, and identified where communication breakdowns could occur. After four iterative rounds of the eDelphi process, including a final validation round by all participants, the project's a priori consensus threshold of 80% agreement was reached. RESULTS: The authors developed a final framework that positions communication more prominently in the diagnostic process in the ED and enhances the original National Academies of Sciences, Engineering, and Medicine (NASEM) and ED-adapted NASEM frameworks. Specific points in the ED journey were identified where more attention to communication might be helpful. Two specific types of communication-information exchange and shared understanding-were identified as high priority for optimal outcomes. Ideas for communication-focused interventions to prevent diagnostic error in the ED fell into three categories: patient-facing, clinician-facing, and system-facing interventions. CONCLUSION: This project's refinement of the NASEM framework adapted to the ED can be used to develop communications-focused interventions to reduce diagnostic error in this highly complex and error-prone setting.

The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients.

Contemporary analyses focused on a limited number of clinical and molecular biomarkers have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma. Here we describe a precision medicine platform known as the Molecular Twin consisting of advanced machine-learning models and use it to analyze a dataset of 6,363 clinical and multi-omic molecular features from patients with resected pancreatic ductal adenocarcinoma to accurately predict disease survival (DS). We show that a full multi-omic model predicts DS with the highest accuracy and that plasma protein is the top single-omic predictor of DS. A parsimonious model learning only 589 multi-omic features demonstrated similar predictive performance as the full multi-omic model. Our platform enables discovery of parsimonious biomarker panels and performance assessment of outcome prediction models learning from resource-intensive panels. This approach has considerable potential to impact clinical care and democratize precision cancer medicine worldwide.