OBJECTIVE: The rapid development of Artificial Intelligence (AI) has raised questions about its potential uses in different sectors of everyday life. Specifically in medicine, the question arose whether chatbots could be used as tools for clinical decision-making or patients\' and physicians\' education. To answer this question in the context of fertility, we conducted a test to determine whether current AI platforms can provide evidence-based responses regarding methods that can improve the outcomes of embryo transfers.
METHODS: We asked nine popular chatbots to write a 300-word scientific essay, outlining scientific methods that improve embryo transfer outcomes. We then gathered the responses and extracted the methods suggested by each chatbot.
RESULTS: Out of a total of 43 recommendations, which could be grouped into 19 similar categories, only 3/19 (15.8%) were evidence-based practices, those being \"ultrasound-guided embryo transfer\" in 7/9 (77.8%) chatbots, \"single embryo transfer\" in 4/9 (44.4%) and \"use of a soft catheter\" in 2/9 (22.2%), whereas some controversial responses like \"preimplantation genetic testing\" appeared frequently (6/9 chatbots; 66.7%), along with other debatable recommendations like \"endometrial receptivity assay\", \"assisted hatching\" and \"time-lapse incubator\".
CONCLUSIONS: Our results suggest that AI is not yet in a position to give evidence-based recommendations in the field of fertility, particularly concerning embryo transfer, since the vast majority of responses consisted of scientifically unsupported recommendations. As such, both patients and physicians should be wary of guiding care based on chatbot recommendations in infertility. Chatbot results might improve with time especially if trained from validated medical databases; however, this will have to be scientifically checked.

UNASSIGNED: Addressing systemic bias in medical school assessment is an urgent task for medical education. This paper outlines recommendations on topic areas for further research on systemic bias, developed from a workshop discussion at the 2023 annual meeting of the Society of Directors of Research in Medical Education.
UNASSIGNED: During the workshop, directors engaged in small-group discussions on guidelines to address bias in assessment practices following a proposed categorization of \'Do\'s,\' \'Don\'ts,\' and \'Don\'t knows\' and listed their insights using anonymous sticky notes, which were shared and discussed with the larger group of participants. The authors performed a content analysis of the notes through deductive and inductive coding. We reviewed and discussed our analysis to reach consensus.
UNASSIGNED: The workshop included 31 participants from 28 institutions across the US and Canada, generating 51 unique notes. Participants identified 23 research areas in need of further study. The inductive analysis of proposed research areas revealed four main topics: 1) The role of interventions, including pre-medical academic interventions, medical-education interventions, assessment approaches, and wellness interventions; 2) Professional development, including the definition and assessment of professionalism and professional identity formation; 3) Context, including patient care and systemic influences; and 4) Research approaches.
UNASSIGNED: While limited to data from a single workshop, the results offered perspectives about areas for further research shared by a group of directors of medical education research units from diverse backgrounds. The workshop produced valuable insights into the need for more evidence-based interventions that promote more equitable assessment practices grounded in real-world situations and that attenuate the effects of bias.

UNASSIGNED: Although Objective Structured Clinical Examinations (OSCEs) offer innovative, objective, and fair methods of clinical assessment, their quality is compromised by poor planning and design.
UNASSIGNED: This study aimed to describe the development and present evidence-based recommendations on strengthening the planning and design of OSCEs for a South African public College of Nursing.
UNASSIGNED: A South African public College of Nursing.
UNASSIGNED: Recommendations were developed based on synthesising two sets of qualitative data. Set 1 included two main themes with each of the four sub-themes related to barriers and facilitators towards quality in OSCE designs from 14 nurse educator interviews and 15 external moderator reports. Set 2 included 12 quality measures to be adopted in the quality design of OSCEs derived from an integrative literature review. The draft recommendations were reviewed by eight experts to be finalised.
UNASSIGNED: Seven recommendations were developed for strengthening OSCEs\' planning and design, related to: (1) policy framework, standard operating procedures and stakeholder code of conduct; (2) blueprinting and mapping of the OSCE content; (3) developing a bank of OSCE stations; (4) scoring rubric and standard-setting method selection; (5) examiners and standardised patients\' recruitment and training; (6) venue selection; and (7) station piloting.
UNASSIGNED: The seven developed recommendations can strengthen the quality of OSCEs in the South African public College of Nursing context.
UNASSIGNED: The developed recommendations can assist nurse educators in planning and designing to conduct quality OSCEs following piloting and implementation.

Cognitive impairment associated with schizophrenia (CIAS) represents one of the core features of the disorder and has a significant impact on functional and rehabilitation outcomes of people living with schizophrenia spectrum disorders (SSD). The aim of this critical review is to highlight the most recent evidence on effective treatments available for CIAS, to discuss the current challenges in this field, and to present future perspectives that may help to overcome them. Concerning psychopharmacological approaches, among the most indicated strategies for the management and prevention of CIAS is to favor second-generation antipsychotic medications and avoid long-term and high-dose treatments with anticholinergic medications and benzodiazepines. Moreover, non-pharmacological approaches such as cognitive remediation and physical exercise-based programs represent evidence-based interventions in the treatment of CIAS that have shown reliable evidence of effectiveness on both cognitive and functional outcomes. These treatments, however, are still delivered to people accessing mental health services with a diagnosis of CIAS in an uneven manner, even in high-income countries. Academic and clinical partnership and collaboration, as well as advocacy from service users, families, carers, and stakeholders\' organizations could help to reduce the bench to bedside gap in the treatment of CIAS. Future perspectives include the development of novel pharmacological agents that could be effective in the treatment of CIAS, the implementation of novel technologies such as telemedicine and virtual reality in the delivery of evidence-based interventions to improve accessibility and engagement, and further research in the field of non-invasive brain stimulation.

Despite the ubiquitous nature of sarcoids, robust data regarding the selection of treatment modalities are scarce, with many treatments having little or no published data to support their use. Treatment options are numerous and vary with the location and type of sarcoid, treatment accessibility, and the financial status of the owner. Many treatments are expensive and time-consuming, and some have health and safety implications. It is this author\'s belief that, based on the limited evidence base, appropriate treatment options vary with the location and type of the sarcoid, and no one treatment is universally appropriate.

Sodium channelopathies are genetic disorders caused by mutations in genes, including sodium voltage-gated channel alpha subunit 1 (SCN1A), that lead to several epilepsy syndromes. Traditional treatments with sodium channel blockers often have limited effectiveness and side effects. Dravet syndrome (DS), a severe epilepsy starting in infancy, presents significant treatment challenges. Perampanel (PER), a noncompetitive α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor antagonist, has shown promise for DS, reducing seizure frequency and improving quality of life (QoL). The limited availability of randomized controlled trials on PER among DS is challenging, but broader studies on refractory epilepsies offer insights. Real-world studies support PER\'s efficacy, underscoring its potential for managing refractory seizures in DS. Studies showed long-term effectiveness in reducing seizure frequency and enhancing QoL. While PER has minimal impact on cognitive development, it significantly improves seizure control. Numerous studies confirm the use of PER as an effective adjunctive treatment for DS; however, it is crucial to observe the safety profile, especially for pediatric sodium channelopathy patients. Common side effects include dizziness, drowsiness, and irritability, necessitating careful management. Long-term safety is generally favorable, but monitoring for behavioral and mood changes is essential. Additionally, the response to PER in DS varies widely, complicating its use. The limited clinical data and the need for careful dosage monitoring, especially in children, present significant challenges. Side effects, potential drug interactions, and high costs further complicate treatment. Despite increasing attention to its cost-effectiveness, accessibility remains limited in some regions, posing significant barriers for many families. In this paper, we review the role of PER in treating pediatric patients with DS, emphasizing clinical evidence and practical considerations.

BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods exist for investigating and measuring AEs. However, some methods have a limited scope, data extraction, and the need for data standardization. In Brazil, there are few studies on the application of trigger tools, and this study is the first to create automated triggers in ambulatory care.
OBJECTIVE: This study aims to develop a machine learning (ML)-based automated trigger for outpatient health care settings in Brazil.
METHODS: A mixed methods research will be conducted within a design thinking framework and the principles will be applied in creating the automated triggers, following the stages of (1) empathize and define the problem, involving observations and inquiries to comprehend both the user and the challenge at hand; (2) ideation, where various solutions to the problem are generated; (3) prototyping, involving the construction of a minimal representation of the best solutions; (4) testing, where user feedback is obtained to refine the solution; and (5) implementation, where the refined solution is tested, changes are assessed, and scaling is considered. Furthermore, ML methods will be adopted to develop automated triggers, tailored to the local context in collaboration with an expert in the field.
RESULTS: This protocol describes a research study in its preliminary stages, prior to any data gathering and analysis. The study was approved by the members of the organizations within the institution in January 2024 and by the ethics board of the University of São Paulo and the institution where the study will take place. in May 2024. As of June 2024, stage 1 commenced with data gathering for qualitative research. A separate paper focused on explaining the method of ML will be considered after the outcomes of stages 1 and 2 in this study.
CONCLUSIONS: After the development of automated triggers in the outpatient setting, it will be possible to prevent and identify potential risks of AEs more promptly, providing valuable information. This technological innovation not only promotes advances in clinical practice but also contributes to the dissemination of techniques and knowledge related to patient safety. Additionally, health care professionals can adopt evidence-based preventive measures, reducing costs associated with AEs and hospital readmissions, enhancing productivity in outpatient care, and contributing to the safety, quality, and effectiveness of care provided. Additionally, in the future, if the outcome is successful, there is the potential to apply it in all units, as planned by the institutional organization.
UNASSIGNED: PRR1-10.2196/55466.

UNASSIGNED: This paper defines and illustrates the ways in which Between-Session Homework (BSH) may be integrated into clinical work with clients across various treatment approaches. In line with the focus of this special issue, we explore how clinical training and supervision can enhance therapist skills and competence in the use of BSH.
UNASSIGNED: After providing a brief historical overview and an integrative perspective on BSH, along with a review of empirical research supporting its efficacy, we delve into the discussion of BSH as a transtheoretical clinical method with heuristic value across different treatment approaches, such as cognitive-behavioral, psychodynamic, and humanistic-experiential therapies.
UNASSIGNED: There exists diversity in how BSH is incorporated into distinct treatment approaches. Furthermore, we emphasize the significance of therapist skills and competence in utilizing BSH to facilitate client engagement and achieve positive treatment outcomes. Finally, we address how clinical training and supervision contribute to the development of these essential skills and competence.
UNASSIGNED: Our findings highlight three main points: (1) substantial empirical support for the integration of BSH within cognitive-behavioral therapies, (2) the potential of BSH as a promising transtheoretical clinical method, even though research beyond cognitive-behavioral therapies remains limited, and (3) the imperative need for further research into how clinical training and supervision can effectively enhance therapist skills and competence in implementing BSH.

OBJECTIVE: The early identification and diagnosis of transplant-associated thrombotic microangiopathy (TA-TMA) are essential yet difficult in patients underwent hematopoietic stem cell transplantation (HSCT). To develop an evidence-based, nurse-leading early warning model for TA-TMA, and implement the healthcare quality review and improvement project.
METHODS: This study was a mixed-methods, before-and-after study. The early warning model was developed based on quality evidence from literature search. The healthcare quality review and improvement project mainly included baseline investigation of nurse, improvement action and effectiveness evaluation. The awareness and knowledge of early parameter of TA-TMA among nurses and the prognosis of patients underwent HSCT were compared before and after the improvement.
RESULTS: A total of 1 guideline, 1 evidence synthesis, 4 expert consensuses, 10 literature reviews, 2 diagnostic studies, and 9 case series were included in the best evidence. The early warning model including warning period, high-risk characteristics and early manifestation of TA-TMA was developed. The improvement action, including staff training and assessment, suspected TA-TMA identification and patient education, was implemented. The awareness and knowledge rate of early parameter of TA-TMA among nurses significantly improved after improvement action (100% vs. 26.7%, P < 0.001). The incidence of TA-TMA was similar among patients underwent HSCT before and after improvement action (2.8% vs. 1.2%, P = 0.643), while no fall event occurred after improvement action (0 vs. 1.2%, P < 0.001).
CONCLUSIONS: The evidence-based early warning model and healthcare quality improvement project could enhance the awareness and knowledge of TA-TMA among healthcare providers and might improve the prognosis of patients diagnosed with TA-TMA.

Evidence-based medicine (EBM) emerged from McMaster University in the 1980-1990s, which emphasizes the integration of the best research evidence with clinical expertise and patient values. The Health Information Research Unit (HiRU) was created at McMaster University in 1985 to support EBM. Early on, digital health informatics took the form of teaching clinicians how to search MEDLINE with modems and phone lines. Searching and retrieval of published articles were transformed as electronic platforms provided greater access to clinically relevant studies, systematic reviews, and clinical practice guidelines, with PubMed playing a pivotal role. In the early 2000s, the HiRU introduced Clinical Queries-validated search filters derived from the curated, gold-standard, human-appraised Hedges dataset-to enhance the precision of searches, allowing clinicians to hone their queries based on study design, population, and outcomes. Currently, almost 1 million articles are added to PubMed annually. To filter through this volume of heterogenous publications for clinically important articles, the HiRU team and other researchers have been applying classical machine learning, deep learning, and, increasingly, large language models (LLMs). These approaches are built upon the foundation of gold-standard annotated datasets and humans in the loop for active machine learning. In this viewpoint, we explore the evolution of health informatics in supporting evidence search and retrieval processes over the past 25+ years within the HiRU, including the evolving roles of LLMs and responsible artificial intelligence, as we continue to facilitate the dissemination of knowledge, enabling clinicians to integrate the best available evidence into their clinical practice.