The Need for Head Protection Protocols for Craniectomy Patients during Rest, Transfers and Turning

After craniectomy, patients are generally advised to wear a helmet when mobilising to protect the unshielded brain from damage. However, there exists limited guidance regarding head protection for patients at rest and when being transferred or turned. Here, we emphasise the need for such protocols and utilise evidence from several sources to affirm our viewpoint. A literature search was first performed using MEDLINE and EMBASE, looking for published material relating to head protection for patients post-craniectomy during rest, transfer or turning. No articles were identified using a wide-ranging search strategy. Next, we surveyed and interviewed staff and patients from our neurosurgical centre to ascertain how often their craniectomy site was exposed to external pressure and the precautions taken to prevent this. 59% of patients admitted resting in contact with the craniectomy site, in agreement with the observations of 67% of staff. In 63% of these patients, this occurred on a daily basis and for some, was associated with symptoms suggestive of raised intracranial pressure. 44% of staff did not use a method to prevent craniectomy site contact while 65% utilised no additional precautions during transfer or turning. 63% of patients received no information about avoiding craniectomy site contact upon discharge, and almost all surveyed wished for resting head protection if it were available. We argue that pragmatic guidelines are needed and that our results support this perspective. As such, we offer a simple, practical protocol which can be adopted and iteratively improved as further evidence becomes available in this area

National Estimates of Emergency Department Visits for Pediatric Severe Sepsis in the United States

Objective. We sought to determine the characteristics of children presenting to United States (US) Emergency Departments (ED) with severe sepsis. Study design. Cross-sectional analysis using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS). Using triage vital signs and ED diagnoses (defined by the International Classification of Diseases, Ninth Revision codes), we identified children(triage fever or ICD-9 infection) and organ dysfunction (triage hypotension or ICD-9 organ dysfunction). Results. Of 28.2 million pediatric patients presenting to US EDs each year, severe sepsis was present in 95,055 (0.34%; 95% CI: 0.29-0.39%). Fever and respiratory infection were the most common indicators of an infection. Hypotension and respiratory failure were the most common indicators of organ dysfunction. Most severe sepsis occurred in children ages 31 days-1 year old (32.1%). Most visits for pediatric severe sepsis occurred during winter months (37.4%), and only 11.1% of patients arrived at the ED by ambulance. Over half of severe sepsis cases were self-pay or insured by Medicaid. A large portion (44.1%) of pediatric severe sepsis ED visits occurred in the South census region. ED length of stay was over 3 h, and 16.5% were admitted to the hospital. Conclusion. Nearly 100,000 children annually present to US EDs with severe sepsis. The findings of this study highlight the unique characteristics of children treated in the ED for severe sepsis

A National Point‐of‐Care Ultrasound Competition for Medical Students

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146850/1/jum14670_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146850/2/jum14670.pd

Zirconium carbide oxidation: kinetics and oxygen diffusion through the intermediate layer

Oxidation of hot‐pressed ZrC was investigated in air in the 1073‐1373 K range. The kinetics were linear at 1073 K, whereas at higher temperature samples initially followed linear kinetics before undergoing rapid oxidation leading to a Maltese cross shape of the oxide. The linear kinetics at 1073 K was governed by inward oxygen diffusion through an intermediate layer of constant thickness between ZrC and ZrO2 which was comprised of amorphous carbon and ZrO2 nanocrystals. Diffusion of oxygen through the intermediate layer was measured to be 9 × 10−10 cm2 s−1 using 18O as a tracer in a double oxidation experiment in 16O/18O. Oxidation at 1073 and 1173 K produced samples made of m‐ZrO2 and either t‐ or c‐ZrO2 with an adherent intermediate layer made of amorphous carbon and ZrO2, whereas oxidation at 1273 and 1373 K produced samples with a voluminous oxide made of m‐ZrO2 showing a gap between ZrC and the oxide. A substoichiometric zirconia layer was found at the gap at 1273 K and no carbon uptake was detected in this layer when compared with the top oxide layer. The loss of the intermediate layer and the slowdown of the linear rate constant (g m−2 s−1) at 1273 K compared to 1173 K was correlated with the preferential oxidation of carbon at the intermediate layer which would leave as CO and/or CO2 leaving a gap between ZrC and substoichiometric zirconia

Towards Conversational Diagnostic AI

At the heart of medicine lies the physician-patient dialogue, where skillful history-taking paves the way for accurate diagnosis, effective management, and enduring trust. Artificial Intelligence (AI) systems capable of diagnostic dialogue could increase accessibility, consistency, and quality of care. However, approximating clinicians' expertise is an outstanding grand challenge. Here, we introduce AMIE (Articulate Medical Intelligence Explorer), a Large Language Model (LLM) based AI system optimized for diagnostic dialogue. AMIE uses a novel self-play based simulated environment with automated feedback mechanisms for scaling learning across diverse disease conditions, specialties, and contexts. We designed a framework for evaluating clinically-meaningful axes of performance including history-taking, diagnostic accuracy, management reasoning, communication skills, and empathy. We compared AMIE's performance to that of primary care physicians (PCPs) in a randomized, double-blind crossover study of text-based consultations with validated patient actors in the style of an Objective Structured Clinical Examination (OSCE). The study included 149 case scenarios from clinical providers in Canada, the UK, and India, 20 PCPs for comparison with AMIE, and evaluations by specialist physicians and patient actors. AMIE demonstrated greater diagnostic accuracy and superior performance on 28 of 32 axes according to specialist physicians and 24 of 26 axes according to patient actors. Our research has several limitations and should be interpreted with appropriate caution. Clinicians were limited to unfamiliar synchronous text-chat which permits large-scale LLM-patient interactions but is not representative of usual clinical practice. While further research is required before AMIE could be translated to real-world settings, the results represent a milestone towards conversational diagnostic AI.Comment: 46 pages, 5 figures in main text, 19 figures in appendi

Endotracheal intubation skill acquisition by medical students

During the course of their training, medical students may receive introductory experience with advanced resuscitation skills. Endotracheal intubation (ETI – the insertion of a breathing tube into the trachea) is an example of an important advanced resuscitation intervention. Only limited data characterize clinical ETI skill acquisition by medical students. We sought to characterize medical student acquisition of ETI procedural skill.11Presented as a poster discussion on 17 October 2007 at the annual meeting of the American Society of Anesthesiologists in San Francisco, CA.The study included third-year medical students participating in a required anesthesiology clerkship. Students performed ETI on operating room patients under the supervision of attending anesthesiologists. Students reported clinical details of each ETI effort, including patient age, sex, Mallampati score, number of direct laryngoscopies and ETI success. Using mixed-effects regression, we characterized the adjusted association between ETI success and cumulative ETI experience.ETI was attempted by 178 students on 1,646 patients (range 1–23 patients per student; median 9 patients per student, IQR 6–12). Overall ETI success was 75.0% (95% CI 72.9–77.1%). Adjusted for patient age, sex, Mallampati score and number of laryngoscopies, the odds of ETI success improved with cumulative ETI encounters (odds ratio 1.09 per additional ETI encounter; 95% CI 1.04–1.14). Students required at least 17 ETI encounters to achieve 90% predicted ETI success.In this series medical student ETI proficiency was associated with cumulative clinical procedural experience. Clinical experience may provide a viable strategy for fostering medical student procedural skills

Kaiso (ZBTB33) subcellular partitioning functionally links LC3A/B, the tumor microenvironment, and breast cancer survival

The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression.Fil: Singhal, Sandeep K.. North Dakota State University; Estados UnidosFil: Byun, Jung S.. National Institutes of Health; Estados UnidosFil: Park, Samson. National Institutes of Health; Estados UnidosFil: Yan, Tingfen. National Institutes of Health; Estados UnidosFil: Yancey, Ryan. Columbia University; Estados UnidosFil: Caban, Ambar. Columbia University; Estados UnidosFil: Hernandez, Sara Gil. National Institutes of Health; Estados UnidosFil: Hewitt, Stephen M.. U.S. Department of Health & Human Services. National Institute of Health. National Cancer Institute; Estados UnidosFil: Boisvert, Heike. Ultivue, Inc; Reino UnidoFil: Hennek, Stephanie. Ultivue Inc.; Reino UnidoFil: Bobrow, Mark. Ultivue Inc.; Reino UnidoFil: Ahmed, Md Shakir Uddin. Tuskegee University; Estados UnidosFil: White, Jason. Tuskegee University; Estados UnidosFil: Yates, Clayton. Tuskegee University; Estados UnidosFil: Aukerman, Andrew. Columbia University; Estados UnidosFil: Vanguri, Rami. Columbia University; Estados UnidosFil: Bareja, Rohan. Columbia University; Estados UnidosFil: Lenci, Romina. Columbia University; Estados UnidosFil: Farré, Paula Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: de Siervi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Nápoles, Anna María. National Institutes of Health; Estados UnidosFil: Vohra, Nasreen. East Carolina University; Estados UnidosFil: Gardner, Kevin. Columbia University; Estados Unido

Evaluation of an educational program for essential newborn care in resource-limited settings: Essential Care for Every Baby

Abstract Background Essential Care for Every Baby (ECEB) is an evidence-based educational program designed to increase cognitive knowledge and develop skills of health care professionals in essential newborn care in low-resource areas. The course focuses on the immediate care of the newborn after birth and during the first day or until discharge from the health facility. This study assessed the overall design of the course; the ability of facilitators to teach the course; and the knowledge and skills acquired by the learners. Methods Testing occurred at 2 global sites. Data from a facilitator evaluation survey, a learner satisfaction survey, a multiple choice question (MCQ) examination, performance on two objective structured clinical evaluations (OSCE), and pre- and post-course confidence assessments were analyzed using descriptive statistics. Pre-post course differences were examined. Comments on the evaluation form and post-course group discussions were analyzed to identify potential program improvements. Results Using ECEB course material, master trainers taught 12 facilitators in India and 11 in Kenya who subsequently taught 62 providers of newborn care in India and 64 in Kenya. Facilitators and learners were satisfied with their ability to teach and learn from the program. Confidence (3.5 to 5) and MCQ scores (India: pre 19.4, post 24.8; Kenya: pre 20.8, post 25.0) improved (p < 0.001). Most participants demonstrated satisfactory skills on the OSCEs. Qualitative data suggested the course was effective, but also identified areas for course improvement. These included additional time for hands-on practice, including practice in a clinical setting, the addition of video learning aids and the adaptation of content to conform to locally recommended practices. Conclusion ECEB program was highly acceptable, demonstrated improved confidence, improved knowledge and developed skills. ECEB may improve newborn care in low resource settings if it is part of an overall implementation plan that addresses local needs and serves to further strengthen health systems

Towards Accurate Differential Diagnosis with Large Language Models

An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces powered by Large Language Models (LLMs) present new opportunities to both assist and automate aspects of this process. In this study, we introduce an LLM optimized for diagnostic reasoning, and evaluate its ability to generate a DDx alone or as an aid to clinicians. 20 clinicians evaluated 302 challenging, real-world medical cases sourced from the New England Journal of Medicine (NEJM) case reports. Each case report was read by two clinicians, who were randomized to one of two assistive conditions: either assistance from search engines and standard medical resources, or LLM assistance in addition to these tools. All clinicians provided a baseline, unassisted DDx prior to using the respective assistive tools. Our LLM for DDx exhibited standalone performance that exceeded that of unassisted clinicians (top-10 accuracy 59.1% vs 33.6%, [p = 0.04]). Comparing the two assisted study arms, the DDx quality score was higher for clinicians assisted by our LLM (top-10 accuracy 51.7%) compared to clinicians without its assistance (36.1%) (McNemar's Test: 45.7, p < 0.01) and clinicians with search (44.4%) (4.75, p = 0.03). Further, clinicians assisted by our LLM arrived at more comprehensive differential lists than those without its assistance. Our study suggests that our LLM for DDx has potential to improve clinicians' diagnostic reasoning and accuracy in challenging cases, meriting further real-world evaluation for its ability to empower physicians and widen patients' access to specialist-level expertise