BACKGROUND: The study reported the time (from the initial submission to the final decision) to evaluate a clinical research project by one of the 39 French national ethics committees. The times from this final decision to the first participant inclusion and study achievement (first patient inclusion to the end of the last patient\'s follow-up) were also reported.
METHODS: Clinical research projects submitted between January 1st 2019 and June 30th 2023 were analyzed according to their type (research on drugs, clinical investigations, performance studies, research implying human person), and the promotor (industry, university hospital, general hospital, private medical institution, others). The times of assessment of the project by the ethic committee (from the initial submission to the final decision), of the first participant inclusion (from the approval of the project) and of study achievement (first patient inclusion to the end of the last patient\'s follow-up) were calculated.
RESULTS: Among 467 submitted clinical research projects, 424 were approved (90.8 %). The median time [Q1-Q3] to evaluate a project was 73 days [51-98] whatever the types of projects and promotors. In 307 accepted projects, the first patient inclusion occurred after 134 days [61-237] and was being waited for 347 days [306-510] in 39 other ones. In 122 projects, the time for study achievement was 446 days [230-731]. In 185 other projects, the inclusions were still in progress for 699 days [397-1098].
CONCLUSIONS: In this concerned ethic committee, a final decision was edited after a median assessment time of 73 days (with >90 % approvals), shorter than the times to include the first patient and for achieving the study.

UNASSIGNED: Impaired quality of life (QOL) is common in patients with inflammatory bowel disease (IBD). A tool to more quickly identify IBD patients at high risk of impaired QOL improves opportunities for earlier intervention and improves long-term prognosis. The purpose of this study was to use a machine learning (ML) approach to develop risk stratification models for evaluating IBD-related QOL impairments.
UNASSIGNED: An online questionnaire was used to collect clinical data on 2478 IBD patients from 42 hospitals distributed across 22 provinces in China from September 2021 to May 2022. Eight ML models used to predict the risk of IBD-related QOL impairments were developed and validated. Model performance was evaluated using a set of indexes and the best ML model was explained using a Local Interpretable Model-Agnostic Explanations (LIME) algorithm.
UNASSIGNED: The support vector machine (SVM) classifier algorithm-based model outperformed other ML models with an area under the receiver operating characteristic curve (AUC) and an accuracy of 0.80 and 0.71, respectively. The feature importance calculated by the SVM classifier algorithm revealed that glucocorticoid use, anxiety, abdominal pain, sleep disorders, and more severe disease contributed to a higher risk of impaired QOL, while longer disease course and the use of biological agents and immunosuppressants were associated with a lower risk.
UNASSIGNED: An ML approach for assessing IBD-related QOL impairments is feasible and effective. This mechanism is a promising tool for gastroenterologists to identify IBD patients at high risk of impaired QOL.

BACKGROUND: Perinatal depression affects a significant number of women during pregnancy and after birth, and early identification is imperative for timely interventions and improved prognosis. Mobile apps offer the potential to overcome barriers to health care provision and facilitate clinical research. However, little is known about users\' perceptions and acceptability of these apps, particularly digital phenotyping and ecological momentary assessment apps, a relatively novel category of apps and approach to data collection. Understanding user\'s concerns and the challenges they experience using the app will facilitate adoption and continued engagement.
OBJECTIVE: This qualitative study explores the experiences and attitudes of users of the Mom2B mobile health (mHealth) research app (Uppsala University) during the perinatal period. In particular, we aimed to determine the acceptability of the app and any concerns about providing data through a mobile app.
METHODS: Semistructured focus group interviews were conducted digitally in Swedish with 13 groups and a total of 41 participants. Participants had been active users of the Mom2B app for at least 6 weeks and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis.
RESULTS: Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience.
CONCLUSIONS: The study findings suggest that app-based digital phenotyping is a feasible and acceptable method of conducting research and health care delivery among perinatal women. The Mom2B app was perceived as an efficient and practical tool that facilitates engagement in research as well as allows users to monitor their well-being and receive general and personalized information related to the perinatal period. However, this study also highlights the importance of trustworthiness, accessibility, and prompt technical issue resolution in the development of future research apps in cooperation with end users. The study contributes to the growing body of literature on the usability and acceptability of mobile apps for research and ecological momentary assessment and underscores the need for continued research in this area.

UNASSIGNED: Hidradenitis supprativa is a chronic inflammatory skin disease that can respond to treatment with laser hair removal.
UNASSIGNED: To assess alexandrite laser hair removal laser as a treatment for hidradenitis suppurativa as measured by the Hidradenitis Supprativa Clinical Response.
UNASSIGNED: We conducted a prospective, randomized, controlled study in adult patients with hidradenitis supprativa. Participants underwent a series of 4 monthly laser treatments to 1 side of the body, with the contralateral side serving as a control. The primary outcome was Hidradenitis Supprativa Clinical Response at week 24, 8 weeks after the final laser treatment.
UNASSIGNED: The percent improvement across treated sites after 4 treatments was 72.73% axillary, 70% inguinal, and 100% inframammary. Across all body regions, Hidradenitis Supprativa Clinical Response was significantly higher for the sites treated with the alexandrite laser compared to the contralateral controls: 75% vs 33.33% (P = .0046, 95% CI: [0.16, 1]).
UNASSIGNED: The limitations of this study include a small sample size from which the data was collected.
UNASSIGNED: The 775-nm alexandrite laser is a safe and effective treatment for hidradenitis supprativa at various anatomic sites in both resolving preexisting lesions and preventing new eruptions.

BACKGROUND: The integrity and reliability of clinical research outcomes rely heavily on access to vast amounts of data. However, the fragmented distribution of these data across multiple institutions, along with ethical and regulatory barriers, presents significant challenges to accessing relevant data. While federated learning offers a promising solution to leverage insights from fragmented data sets, its adoption faces hurdles due to implementation complexities, scalability issues, and inclusivity challenges.
OBJECTIVE: This paper introduces Federated Learning for Everyone (FL4E), an accessible framework facilitating multistakeholder collaboration in clinical research. It focuses on simplifying federated learning through an innovative ecosystem-based approach.
METHODS: The \"degree of federation\" is a fundamental concept of FL4E, allowing for flexible integration of federated and centralized learning models. This feature provides a customizable solution by enabling users to choose the level of data decentralization based on specific health care settings or project needs, making federated learning more adaptable and efficient. By using an ecosystem-based collaborative learning strategy, FL4E encourages a comprehensive platform for managing real-world data, enhancing collaboration and knowledge sharing among its stakeholders.
RESULTS: Evaluating FL4E\'s effectiveness using real-world health care data sets has highlighted its ecosystem-oriented and inclusive design. By applying hybrid models to 2 distinct analytical tasks-classification and survival analysis-within real-world settings, we have effectively measured the \"degree of federation\" across various contexts. These evaluations show that FL4E\'s hybrid models not only match the performance of fully federated models but also avoid the substantial overhead usually linked with these models. Achieving this balance greatly enhances collaborative initiatives and broadens the scope of analytical possibilities within the ecosystem.
CONCLUSIONS: FL4E represents a significant step forward in collaborative clinical research by merging the benefits of centralized and federated learning. Its modular ecosystem-based design and the \"degree of federation\" feature make it an inclusive, customizable framework suitable for a wide array of clinical research scenarios, promising to revolutionize the field through improved collaboration and data use. Detailed implementation and analyses are available on the associated GitHub repository.

BACKGROUND: Calciphylaxis patients historically have experienced diagnostic challenges and high morbidity; however limited data is available examining these characteristics over time.
OBJECTIVE: The primary goals were to a) investigate factors associated with diagnostic delay of calciphylaxis and b) assess morbidity outcomes. The secondary goal was to provide updated mortality rates.
METHODS: A retrospective review of 302 adult patients diagnosed with calciphylaxis between January 1, 2006 and December 31, 2022 was conducted. Univariate and multivariate statistical analyses were performed.
RESULTS: Nonnephrogenic calciphylaxis (P = .0004) and involvement of the fingers (P = .0001) were significantly associated with an increased diagnostic delay, whereas involvement of the arms (P = .01) and genitalia (P = .022) resulted in fewer days to diagnosis. Almost all patients with genitalia, finger, or toe involvement had nephrogenic disease. The number of complications per patient decreased with time, especially for wound infections (P = .028), increase in lesion number (P = .012), and recurrent hospitalizations (P = .020). Updated 1-year mortality rates were 36.70% and 30.77% for nephrogenic and nonnephrogenic calciphylaxis, respectively.
CONCLUSIONS: Limitations include the retrospective nature and data from a single institution.
CONCLUSIONS: Diagnostic delay, particularly in nonnephrogenic calciphylaxis, and complications per patient decreased with time, highlighting the importance of continued awareness to expedite diagnosis. Mortality rates have continued to improve in recent years.

BACKGROUND: Engaging in clinical research includes confronting challenges about the uncertainty around outcomes and ramifications the results may have on practice. This is pertinent for osteopathy where little is known about the experiences of osteopaths involved in clinical trials. The aim of this study was to explore the lived experience of osteopaths who participated in a randomised controlled trial for infantile colic. The study was informed by a principles-based approach to clinical ethics and their application to practice.
METHODS: Qualitative study using semi-structured interviews and reflexive thematic analysis.
METHODS: An international two-arm pragmatic randomised controlled trial (the CUTIES trial) to evaluate the effectiveness of osteopathic care for infantile colic.
METHODS: A principles-based approach to clinical ethics and their application to practice for osteopaths asked to make decisions about participating in a clinical trial was used. Osteopaths from the UK and Australia who completed the CUTIES trial training were invited to be interviewed about their experiences, regardless of whether they went on to recruit infants in the trial. Interviewees were asked about their reasons for wanting to participate in the CUTIES trial, why they decided to continue or not to continue in the trial and, for those who completed the trial, their personal experiences as participants in the trial. Data were analysed using reflexive thematic analysis.
RESULTS: Nine osteopaths were interviewed. Three themes were identified from the data: Paradigm dilemma - observed clinical outcomes vs scientific evidence for mechanism of effects; trial-related ethical dilemmas; and trial outcome dilemmas.
CONCLUSIONS: Participating in the CUTIES trial required osteopaths to overcome clinical ethical dilemmas for the benefit of patients, the research, and the profession.

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BACKGROUND: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied.
OBJECTIVE: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool.
METHODS: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap\'s data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience.
RESULTS: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes).
CONCLUSIONS: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap\'s data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients.

BACKGROUND: Recruitment of sufficient and diverse participants into clinical research for Alzheimer\'s disease and related dementias remains a formidable challenge. The primary goal of this manuscript is to provide an overview of an approach to diversifying research recruitment and to provide case examples of several methods for achieving greater diversity in clinical research enrollment.
METHODS: The University of Kansas Alzheimer\'s Disease Research Center (KU ADRC) developed MyAlliance for Brain Health (MyAlliance), a service-oriented recruitment model. MyAlliance comprises a Primary Care Provider Network, a Patient and Family Network, and a Community Organization Network, each delivering tailored value to relevant parties while facilitating research referrals.
RESULTS: We review three methods for encouraging increased diversity in clinical research participation. Initial outcomes reveal an increase in underrepresented participants from 17% to 27% in a research registry. Enrollments into studies supported by the research registry experienced a 51% increase in proportion of participants from underrepresented communities.
CONCLUSIONS: MyAlliance shifts power, resources, and knowledge to community advocates, promoting brain health awareness and research participation, and demands substantial financial investment and administrative commitment. MyAlliance offers valuable lessons for building sustainable, community-centered research recruitment infrastructure, emphasizing the importance of localized engagement and cultural understanding.
UNASSIGNED: MyAlliance led to a significant increase in the representation of underrepresented racial and ethnic groups and individuals from rural areas.The service-oriented approach facilitated long-term community engagement and trust-building, extending partnerships between an academic medical center and community organizations.While effective, MyAlliance required substantial financial investment, with costs including infrastructure development, staff support, partner organization compensation, and promotional activities, underscoring the resource-intensive nature of inclusive research recruitment efforts.