ECRI Institute

Evidence synthesis and guideline groups have the potential to address health disparities. In June 2024, the Agency for Healthcare Research and Quality (AHRQ) and the Robert Wood Johnson Foundation (RWJF) cosponsored a summit to address racial and ethnic health equity in systematic reviews and other syntheses and guidelines, with support from Cochrane US. This article summarizes cross-cutting themes around future directions for systematic reviews and guidelines. Discussions addressed include the rationale for addressing racial health equity in systematic reviews and guidelines; representation of people with lived experience in systematic reviews and guidelines; approaches to developing and addressing equity-focused scope, including frameworks, methods, and thoughtful interpretation in systematic reviews; challenges and opportunities for guideline recommendations; need for standardized language and reporting for race and ethnicity in primary research studies, systematic reviews, and guidelines; and measures to track the progress of incorporating and addressing racial and ethnic health equity in systematic reviews and guidelines. Participants acknowledged that a one-size-fits-all approach was not possible or desired. Consensus priorities for next steps were to develop methods guidance to address equity in systematic reviews and guidelines; develop measures to track the progress of addressing racial and health equity in systematic reviews and guidelines; operationalize engaging representative interest holders in systematic reviews and guidelines; and share resources and learning for advancing health equity.

Most existing methods of 3D clothed human reconstruction from a single image treat the clothed human as a single object without distinguishing between cloth and human body. In this regard, we present DeClotH, which separately reconstructs 3D cloth and human body from a single image. This task remains largely unexplored due to the extreme occlusion between cloth and the human body, making it challenging to infer accurate geometries and textures. Moreover, while recent 3D human reconstruction methods have achieved impressive results using text-to-image diffusion models, directly applying such an approach to this problem often leads to incorrect guidance, particularly in reconstructing 3D cloth. To address these challenges, we propose two core designs in our framework. First, to alleviate the occlusion issue, we leverage 3D template models of cloth and human body as regularizations, which provide strong geometric priors to prevent erroneous reconstruction by the occlusion. Second, we introduce a cloth diffusion model specifically designed to provide contextual information about cloth appearance, thereby enhancing the reconstruction of 3D cloth. Qualitative and quantitative experiments demonstrate that our proposed approach is highly effective in reconstructing both 3D cloth and the human body.

Research on brain disorders, particularly in the field of oncology, requires in vivo models to evaluate various therapeutic approaches, including intracerebral drug delivery. To meet this requirement, the implantation of intracerebral cannulas offers a reliable method for administering candidate therapeutics directly into the brain. This protocol describes a surgical technique for cannula implantation in mice, enabling repeated administration of therapeutic compounds in the context of glioblastoma treatment. The method was designed with an emphasis on using accessible, easy-to-handle, and sterilized tools to optimize surgical outcomes. Particular attention was also given to animal welfare, notably through refined procedures for asepsis, anesthesia, and postoperative care.Key features• This protocol requires specific equipment and surgical mice expertise.• This protocol is dedicated to brain disorders and cancer models, with a particular emphasis on locoregional delivery of drugs and derivatives.

BackgroundThe reporting of adverse events in medical devices (MD) is a starting point of post-market surveillance and the most common source of initial safety signals. Because MD adverse events (AE) occur globally and involve high-profile international public health crises, international regulators implanted standard codes for MDAE reporting. This study aimed to assess the application of MDAE terminology and codes by providing examples of virtual events.MethodsAn online survey was conducted among participants of the MD Training Program for Regulatory Authorities which provide International Medical Device Regulators Forum (IMDRF) adverse event terminology and codes, and six virtual MDAE cases.ResultsAll 29 of the 72 participants were regulators. In all cases, most participants selected the broad (level 1) codes rather than the detailed (level 2 or level 3) codes. While responders selected a variety of codes for all annexes in case 1, over 50% of responders selected the intended codes in case 6. The codes for cause investigation were chosen more frequently than other annexes for device problem, components, and health effect. No differences were observed in code selection amongst different stakeholders.ConclusionsWe identified the diversification in terminology and code selection for reporting MDAEs.

There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities. To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities. Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023. Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms. Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension. Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques. Results are mostly based on modeling studies and may be highly context-specific. Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes. Agency for Healthcare Quality and Research.

It is challenging to anticipate stock market values, and in the past, this has necessitated significant human-computer interaction. Traditional batch processing methods cannot be effectively utilized for stock market research since stock prices are interconnected. It is practically impossible to estimate stock prices to the penny due to the unpredictability of the factors that affect price movement. However, an informed estimate of pricing is attainable. The data is provided in the form of corporate stock data, that will be evaluated in real time. The proposed system produces an output in the graphical form that depicts the predicted future stock price. Hence, this research study has proposed a solution to predict the stock market prices using the machine learning algorithm.

To provide evidence-based recommendations on the use of vaccinations in children and adults with rheumatic and musculoskeletal diseases (RMDs). This guideline follows American College of Rheumatology (ACR) policy guiding management of conflicts of interest and disclosures and the ACR guideline development process, which includes the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. It also adheres to the Appraisal of Guidelines for Research and Evaluation (AGREE) criteria. A core leadership team consisting of adult and pediatric rheumatologists and a guideline methodologist drafted clinical population, intervention, comparator, outcomes (PICO) questions. A review team performed a systematic literature review for the PICO questions, graded the quality of evidence, and produced an evidence report. An expert Voting Panel reviewed the evidence and formulated recommendations. The panel included adult and pediatric rheumatology providers, infectious diseases specialists, and patient representatives. Consensus required ≥70% agreement on both the direction and strength of each recommendation. This guideline includes expanded indications for some vaccines in patients with RMDs, as well as guidance on whether to hold immunosuppressive medications or delay vaccination to maximize vaccine immunogenicity and efficacy. Safe approaches to the use of live attenuated vaccines in patients taking immunosuppressive medications are also addressed. Most recommendations are conditional and had low quality of supporting evidence. Application of these recommendations should consider patients' individual risk for vaccine-preventable illness and for disease flares, particularly if immunosuppressive medications are held for vaccination. Shared decision-making with patients is encouraged in clinical settings.

Dans cet essai, les autrices expliquent l’intention qui les a guidées dans le processus d’adaptation du livre audio Halfbreed de Maria Campbell, autrice, conteuse, activiste et aînée métis de renommée nationale et internationale. Le livre de Campbell a été publié en français par la maison d’édition Prise de parole, dont le mandat est d’accroître l’accessibilité de la littérature française au Canada. Dans le cadre du projet d’adaptation soutenu par la maison d’édition, Maria a réuni une équipe locale dans le but de produire une version audio de son livre. Nous, les autrices, faisions partie de cette équipe dans les rôles respectifs de directrice et de narratrice. Notre démarche était axée sur l’éthique du storytelling, le soin relationnel, l’oralité, l’originalité et le contexte local et culturel. Tout au long du processus d’adaptation, nous avons tenu compte de ces considérations et de notre responsabilité envers l’autrice du livre et les lecteurs. Nous avons également intégré à notre démarche nos liens respectifs, notre expérience et notre connaissance du lieu.