Nawaz, Faisal A.

Background Documentation burden contributes significantly to psychiatric clinician burnout, with psychiatrists spending an average of three hours per workday on administrative tasks rather than direct patient care. While quantitative studies demonstrate that ambient artificial intelligence (AI) scribes reduce workload and improve documentation quality, the experiential perspectives of clinicians and standardized patients (SPs) remain unexplored, particularly in psychiatry where the therapeutic relationship is central to practice. Our aims were to explore clinician and standardized simulated patient perspectives on ambient AI scribes in psychiatric consultations, examining experiences, concerns, and conditions for successful implementation. Methods This study was part of a cross-sectional quantitative simulation study, where qualitative part was planned a-priori. We conducted focus groups with psychiatrists and SPs following a simulation-based crossover study comparing traditional versus AI-assisted documentation. Data were analyzed using Braun and Clarke’s reflexive thematic analysis framework. Results In this focus group session with eight psychiatrists and four SPs, total six themes were identified: (1) Clinical Presence, whereby reduced documentation barriers were perceived to allow more authentic human connection; (2) Liberation from documentation burden, with clinicians describing cognitive and emotional relief beneficial for their mental health; (3) Clinical Competence Amplified, in which clinicians perceived the AI scribe as enhancing practice through intelligent translation to psychiatric terminology and prompting for missed assessments; (4) Calibrating Trust, where participants navigated initial uncertainty while recognizing the importance of human oversight; (5) Privacy, stigma, and psychiatric exceptionalism, highlighting unique consent and confidentiality considerations for psychiatric populations; and (6) Perceptions of an enhanced standard of care, with both groups expressing strong preference for AI-assisted consultations with conditions for adoption. Conclusion In this exploratory simulation-based qualitative study, AI scribes were perceived as having potential to support more present, patient-centered psychiatric consultations by reducing documentation burden. Implementation should be cautious and requires transparent consent processes, clinician training in behavioral adaptations, robust human oversight, specialty-specific templates, and real-world evaluation with patients receiving psychiatric care.

Background Artificial intelligence (AI) and large language models (LLMs), are potential tools for enhancing healthcare delivery and clinical research. Presently, there is a scarcity of research regarding the viewpoints of medical students toward LLMs. This study aims to explore the perceptions of LLMs and their applications among this demographic. Methods A cross-sectional study was done using an online survey. It was designed using Google Forms and circulated from July 2023 to August 2023. The target population included medical students from Ecuador, Ethiopia, India, Mauritius, Pakistan, United Arab Emirates (UAE), and the United States (USA). Results A total of 1180 responses were collected from 10 medical colleges across 7 countries. The UAE had the largest number of responses (31.7%), followed by Ecuador (17.6%), and Mauritius (13.7%). And 77.4% respondents were already aware about LLMs before attempting the survey, most popularly, ChatGPT. Participants were most familiar with the specific use of LLMs in research (46%), and the lowest familiarity was seen in the use of LLMs in healthcare (37%). More than half of the participants (52%) support the use of LLMs healthcare, yet a significant number of them remained neutral (37%) or disagreed (31%) on LLMs being safe in this context. Conclusion While most of the medical students are aware of LLMs and their applications, the multinational survey demonstrated hesitancy among medical students in fully adopting LLMs into healthcare practice and clinical research. This study prompts further exploration of medical students’ attitudes and acceptance concerning the integration of LLMs for research methodologies, ethical considerations, and healthcare practice.

Aim: AI research, development, and implementation are expanding at an exponential pace across healthcare. This paradigm shift in healthcare research has led to increased demands for clinical outcomes, all at the expense of a significant gap in AI literacy within the healthcare field. This has further translated to a lack of tools in creating a framework for literature in the AI in medicine domain. We propose HUMANE (Harmonious Understanding of Machine Learning Analytics Network), a checklist for establishing an international consensus for authors and reviewers involved in research focused on artificial intelligence (AI) or machine learning (ML) in medicine. Methods: This study was conducted using the Delphi method by devising a survey using the Google Forms platform. The survey was developed as a checklist containing 8 sections and 56 questions with a 5-point Likert scale. Results: A total of 33 survey respondents were part of the initial Delphi process with the majority (45%) in the 36–45 years age group. The respondents were located across the USA (61%), UK (24%), and Australia (9%) as the top 3 countries, with a pre-dominant healthcare background (42%) as early-career professionals (3–10 years’ experience) (42%). Feedback showed an overall agreeable consensus (mean ranges 4.1–4.8, out of 5) as cumulative scores throughout all sections. The majority of the consensus was agreeable with the Discussion (Other) section of the checklist (median 4.8 (interquartile range (IQR) 4.8-4.8)), whereas the least agreed section was the Ground Truth (Expert(s) review) section (median 4.1 (IQR 3.9–4.2)) and the Methods (Outcomes) section (median 4.1 (IQR 4.1–4.1)) of the checklist. The final checklist after consensus and revision included a total of 8 sections and 50 questions. Conclusions: The HUMANE international consensus has reflected on further research on the potential of this checklist as an established consensus in improving the reliability and quality of research in this field.

Abstract Background Bacterial blood stream infection (BSI) is a leading cause for mortality and morbidity in the pediatric solid organ transplant recipient population. This systematic review aims at pooling global data from the leading transplant institutions to identify the overall prevalence and risk factors associated with bacterial BSI and the most common causative organisms. Methods A systematic review of PubMed and OVID databases was conducted for the past 20 years. Initial search from both databases had a yield of 252 unique articles which were reviewed independently by two authors. Data related to demographics, prevalence, organisms and risk factors were extracted from the articles and subsequently analysed. The systematic review was registered on PROSPERO (ID: CRD42023403206). The PRISMA flow diagram visually summarises the screening process Results A total of 14 articles were included from the United States of America, France, Italy, Thailand, Japan, Spain and Korea. A total of 4215 liver transplants were included in the final analysis. The overall prevalence of BSI in pediatric liver transplant patients was 23.5% with the highest prevalence reported in Japan (39.5%) and lowest in the USA (18.7%). Mean age of the patients was 25 months and 54% were females. The most common organisms reported were Staphylococcus epidermidis at 22.8% followed by Enterococcus species (16.6%), Klebsiella species (11.9%) and Escherichia coli (11.4%). Among the risk factors studied, postoperative biliary complications, past medical history of biliary atresia and younger age were the risk factors most associated with BSI. Prevalence of bloodstream infections (BSI) post pediatric liver transplant in included countries. Bacterial organisms isolated in blood cultures in pediatric post liver transplant patient with a bloodstream infection. Conclusion Bacterial BSI post pediatric liver transplantation occurs with high prevalence. Further studies need to be conducted to better define risk factors for BSI and determine the best empirical antibiotic management for BSI in this population as the distribution of organisms varies greatly from otherwise healthy pediatric patients. Disclosures All Authors: No reported disclosures

Abstract Background Twitter has become an invaluable resource for gaining insights into crucial developments in global healthcare communication. The hashtags (#) can be used to categorize tweets and gather conversations on a specific topic or to target a particular audience. Although the prevailing knowledge fund underlines the potential of digital networks to essentially influence the management of infectious diseases (ID), there has been no comprehensive analysis on the user information in the ID Twitter community, nor of the influence this hashtag has generated. The objective of our study was to evaluate the demographic data of #IDTwitter users, discern the most influential members and popular narratives in this realm, and ascertain the impact of the hashtag. Methods Using data from 28th June 2019 and 28th March 2023, an extensive analysis was conducted using the Symplur Signals research analytics tool. The analysis focused on the cumulative number of tweets, impressions, and unique users who shared tweets containing the hashtag #IDTwitter, with users categorized into specific healthcare stakeholder groups. The primary outcome measures were outreach and awareness measured by the number of tweets and impressions. Results The study observed the trends of #IDTwitter over a period of 45 months and found 441,650 tweets were shared by 92,734 users that generated a total of 1,833,037,732 impressions (views). Top five co-occurring hashtags were #IDtwitter, #MedTwitter, #MedEd, #COVID19, #TwitteRx. The top five countries reporting the greatest number of users of this hashtag were The United States of America (48326), Canada (4803), Mexico (3413), India (2759), Australia (2658). Various healthcare stakeholders’ categories were identified and three largest groups of contributors were Doctors (14.55%), Healthcare Providers (7.54%) and Researcher/Academic (3.70%). The top three influencers of this hashtag include two clinical pharmacists and one organization account. Country-wise distribution of Users of #IDTwitter The image shows the geographical distribution of the users who posted tweets containing #IDTwitter were shared (based on the locations at which the posting accounts were registered). Twitter is used worldwide for conversations regarding communicable diseases and their prevention, not only among the general public but also among students and professionals via online chat discussions and virtual rounds. Stakeholders of #IDTwitter Accounting for the percentage distribution of #IDTwitter-posting users in various healthcare stakeholders categories (data derived from Symplur Signals, with the classification being based on information provided in the Twitter biographies of the users- https://help.symplur.com/en/articles/103684-healthcare-stakeholder-segmentation). Twitter has become a quintessential tool for connecting people worldwide, and we can leverage this platform to our advantage by paying close attention to the topic and content of hashtag exchanges to combat misinformation related to matters like antibiotic usage or any epidemic infection on social media platforms. Top Co-occurring Hashtags The hashtags that generally appear alongside of #IDTwitter could provide an insight regarding the popular discussions involving #IDTwitter. Conclusion Our findings indicate that there is considerable interest in using #IDTwitter to promote relevant content and engage a geographically diverse audience. It underscores the vitality of professional voices in combating misinformation and we could definitely leverage this 'viral' hashtag for our advantage. Disclosures All Authors: No reported disclosures

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education. Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ 2 test was performed to determine the association between gender and different violence forms. Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with >1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance. Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction.

Background and Objectives: Bartter syndrome (BS) is a rare group of autosomal-recessive disorders that usually presents with hypokalemic metabolic alkalosis, occasionally with hyponatremia and hypochloremia. The clinical presentation of BS is heterogeneous, with a wide variety of genetic variants. The aim of this systematic review was to examine the available literature and provide an overview of the case reports and case series on BS. Materials and Methods: Case reports/series published from April 2012 to April 2022 were searched through Pubmed, JSTOR, Cochrane, ScienceDirect, and DOAJ. Subsequently, the information was extracted in order to characterize the clinical presentation, laboratory results, treatment options, and follow-up of the patients with BS. Results: Overall, 118 patients, 48 case reports, and 9 case series (n = 70) were identified. Out of these, the majority of patients were male (n = 68). A total of 21 patients were born from consanguineous marriages. Most cases were reported from Asia (73.72%) and Europe (15.25%). In total, 100 BS patients displayed the genetic variants, with most of these being reported as Type III (n = 59), followed by Type II (n = 19), Type I (n = 14), Type IV (n = 7), and only 1 as Type V. The most common symptoms included polyuria, polydipsia, vomiting, and dehydration. Some of the commonly used treatments were indomethacin, potassium chloride supplements, and spironolactone. The length of the follow-up time varied from 1 month to 14 years. Conclusions: Our systematic review was able to summarize the clinical characteristics, presentation, and treatment plans of BS patients. The findings from this review can be effectively applied in the diagnosis and patient management of individuals with BS, rendering it a valuable resource for nephrologists in their routine clinical practice.