AI-algorithm training and validation for identification of endometrial CD138+ cells in infertility-associated conditions; polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF)

Background

Endometrial CD138+ plasma cells serve as a diagnostic biomarker for endometrial inflammation, and their elevated occurrence correlates positively with adverse pregnancy outcomes. Infertility-related conditions like polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) are closely associated with systemic and local chronic inflammatory status, wherein endometrial CD138+ plasma cell accumulation could also contribute to endometrial pathology. Current methods for quantifying CD138+ cells typically involve laborious and time-consuming microscopic assessments of only a few random areas from a slide. These methods have limitations in accurately representing the entire slide and are susceptible to significant biases arising from intra- and interobserver variations. Implementing artificial intelligence (AI) for CD138+ cell identification could enhance the accuracy, reproducibility, and reliability of analysis.

Methods

Here, an AI algorithm was developed to identify CD138+ plasma cells within endometrial tissue. The AI model comprised two layers of convolutional neural networks (CNNs). CNN1 was trained to segment epithelium and stroma across 28,363 mm2 (2.56 mm2 of epithelium and 24.87 mm2 of stroma), while CNN2 was trained to distinguish stromal cells based on CD138 staining, encompassing 7345 cells in the object layers (6942 CD138- cells and 403 CD138+ cells). The training and performance of the AI model were validated by three experienced pathologists. We collected 193 endometrial tissues from healthy controls (n = 73), women with PCOS (n = 91), and RIF patients (n = 29) and compared the CD138+ cell percentages based on cycle phases, ovulation status, and endometrial receptivity utilizing the AI model.

Results

The AI algorithm consistently and reliably distinguished CD138- and CD138+ cells, with total error rates of 6.32% and 3.23%, respectively. During the training validation, there was a complete agreement between the decisions made by the pathologists and the AI algorithm, while the performance validation demonstrated excellent accuracy between the AI and human evaluation methods (intraclass correlation; 0.76, 95% confidence intervals; 0.36-0.93, p = 0.002) and a positive correlation (Spearman's rank correlation coefficient: 0.79, p < 0.01). In the AI analysis, the AI model revealed higher CD138+ cell percentages in the proliferative phase (PE) endometrium compared to the secretory phase or anovulatory PCOS endometrium, irrespective of PCOS diagnosis. Interestingly, CD138+ percentages differed according to PCOS phenotype in the PE (p = 0.03). On the other hand, the receptivity status had no impact on the cell percentages in RIF samples.

Conclusion

Our findings emphasize the potential and accuracy of the AI algorithm in detecting endometrial CD138+ plasma cells, offering distinct advantages over manual inspection, such as rapid analysis of whole slide images, reduction of intra- and interobserver variations, sparing the valuable time of trained specialists, and consistent productivity. This supports the application of AI technology to help clinical decision-making, for example, in understanding endometrial cycle phase-related dynamics, as well as different reproductive disorders.

Crossing the Andes: Challenges and opportunities for digital pathology in Latin America

The most widely accepted and used type of digital pathology (DP) is whole-slide imaging (WSI). The USFDA granted two WSI system approvals for primary diagnosis, the first in 2017. In Latin America, DP has the potential to reshape healthcare by enhancing diagnostic capabilities through artificial intelligence (AI) and standardizing pathology reports. Yet, we must tackle regulatory hurdles, training, resource availability, and unique challenges to the region. Collectively addressing these hurdles can enable the region to harness DP's advantages-enhancing disease diagnosis, medical research, and healthcare accessibility for its population. Americas Health Foundation assembled a panel of Latin American pathologists who are experts in DP to assess the hurdles to implementing it into pathologists' workflows in the region and provide recommendations for overcoming them. Some key steps recommended include creating a Latin American Society of Digital Pathology to provide continuing education, developing AI models trained on the Latin American population, establishing national regulatory frameworks for protecting the data, and standardizing formats for DP images to ensure that pathologists can collaborate and validate specimens across the various DP platforms.

Effects of thymoquinone and the curcumin analog EF-24 on the activity of the enzyme paraoxonase-1 in human glioblastoma cells U87MG

The spices and aromatic herbs were used not only in cooking to add flavour and smell to dishes but also for medicinal use. Nigella sativa, also called black cumin, is one of the species that contains an important bioactive component, thymoquinone (TQ), which has antioxidant, anti-inflammatory, antimicrobial, and antidiabetic effects. Curcuma longa, which also includes curcumin, has numerous anti-cancer properties. However, the bioavailability of curcumin is lower than that of its analogs. An analog of curcumin (EF-24), which has better bioavailability than curcumin, is capable of exerting a high anti-cancer effect. In our study, we determined the effects of PON1 enzyme activity on the proliferation and aggressiveness of glioblastoma cancer treated with TQ and EF-24 from lysates of the glioblastoma cell line U87MG. The results were determined as increased PON1 activity after treatment with TQ and EF-24 in the U87MG cell line (p < 0.0001).

Eye tracking in digital pathology: A comprehensive literature review

Eye tracking has been used for decades in attempt to understand the cognitive processes of individuals. From memory access to problem-solving to decision-making, such insight has the potential to improve workflows and the education of students to become experts in relevant fields. Until recently, the traditional use of microscopes in pathology made eye tracking exceptionally difficult. However, the digital revolution of pathology from conventional microscopes to digital whole slide images allows for new research to be conducted and information to be learned with regards to pathologist visual search patterns and learning experiences. This has the promise to make pathology education more efficient and engaging, ultimately creating stronger and more proficient generations of pathologists to come. The goal of this review on eye tracking in pathology is to characterize and compare the visual search patterns of pathologists. The PubMed and Web of Science databases were searched using 'pathology' AND 'eye tracking' synonyms. A total of 22 relevant full-text articles published up to and including 2023 were identified and included in this review. Thematic analysis was conducted to organize each study into one or more of the 10 themes identified to characterize the visual search patterns of pathologists: (1) effect of experience, (2) fixations, (3) zooming, (4) panning, (5) saccades, (6) pupil diameter, (7) interpretation time, (8) strategies, (9) machine learning, and (10) education. Expert pathologists were found to have higher diagnostic accuracy, fewer fixations, and shorter interpretation times than pathologists with less experience. Further, literature on eye tracking in pathology indicates that there are several visual strategies for diagnostic interpretation of digital pathology images, but no evidence of a superior strategy exists. The educational implications of eye tracking in pathology have also been explored but the effect of teaching novices how to search as an expert remains unclear. In this article, the main challenges and prospects of eye tracking in pathology are briefly discussed along with their implications to the field.

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support "Learning Health Systems" with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support "Learning Health Systems" by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented.

Evaluation of a field deployable, high-throughput RT-LAMP device as an early warning system for COVID-19 through SARS-CoV-2 measurements in wastewater

Quantification of SARS-CoV-2 RNA copies in wastewater can be used to estimate COVID-19 prevalence in communities. While such results are important for mitigating disease spread, SARS-CoV-2 measurements require sophisticated equipment and trained personnel, for which a centralized laboratory is necessary. This significantly impacts the time to result, defeating its purpose as an early warning detection tool. The objective of this study was to evaluate a field portable device (called MINI) for detecting SARS-CoV-2 viral loads in wastewater using real-time reverse transcriptase loop-mediated isothermal amplification (real-time RT-LAMP). The device was tested using wastewater samples collected from buildings (with 430 to 1430 inhabitants) that had known COVID-19-positive cases. Results show comparable performance of RT-LAMP against reverse transcriptase polymerase chain reaction (RT-qPCR) when detecting SARS-CoV-2 copies in wastewater. Both RT-LAMP and RT-qPCR detected SARS-CoV-2 in wastewater from buildings with at least three positive individuals within a 6-day time frame prior to diagnosis. The large 96-well throughput provided by MINI provided scalability to multi-building detection. The portability of the MINI device enabled decentralized on-site detection, significantly reducing the time to result. The overall findings support the use of RT-LAMP within the MINI configuration as an early detection system for COVID-19 infection using wastewater collected at the building scale.

Predicting isocitrate dehydrogenase status among adult patients with diffuse glioma using patient characteristics, radiomic features, and magnetic resonance imaging: Multi-modal analysis by variable vision transformer

OBJECTIVES

To evaluate the performance of the multimodal model, termed variable Vision Transformer (vViT), in the task of predicting isocitrate dehydrogenase (IDH) status among adult patients with diffuse glioma.

MATERIALS AND METHODS

vViT was designed to predict IDH status using patient characteristics (sex and age), radiomic features, and contrast-enhanced T1-weighted images (CE-T1WI). Radiomic features were extracted from each enhancing tumor (ET), necrotic tumor core (NCR), and peritumoral edematous/infiltrated tissue (ED). CE-T1WI were split into four images and input to vViT. In the training, internal test, and external test, 271 patients with 1070 images (535 IDH wildtype, 535 IDH mutant), 35 patients with 194 images (97 IDH wildtype, 97 IDH mutant), and 291 patients with 872 images (436 IDH wildtype, 436 IDH mutant) were analyzed, respectively. Metrics including accuracy and AUC-ROC were calculated for the internal and external test datasets. Permutation importance analysis combined with the Mann-Whitney U test was performed to compare inputs.

RESULTS

For the internal test dataset, vViT correctly predicted IDH status for all patients. For the external test dataset, an accuracy of 0.935 (95% confidence interval; 0.913-0.945) and AUC-ROC of 0.887 (0.798-0.956) were obtained. For both internal and external test datasets, CE-T1WI ET radiomic features and patient characteristics had higher importance than other inputs (p < 0.05).

CONCLUSIONS

The vViT has the potential to be a competent model in predicting IDH status among adult patients with diffuse glioma. Our results indicate that age, sex, and CE-T1WI ET radiomic features have key information in estimating IDH status.

Cytopathology fellowship match: Pros and cons

A cytopathology fellowship match would create an enforced and structured recruitment timeline for the benefit of applicants and programs. Major benefits would include delaying fellowship applications to allow residents to explore different subspecialty areas, a standardized application process for administrative ease, and optimization of matches between applicants and programs based on ranked preferences rather than use of time-limited "exploding offers." The overall gains in efficiency and achieving the primary goals of supporting trainees and recruiting in an equitable and inclusive manner outweigh any downsides to instituting a cytopathology fellowship match. We aim to review the major discussions around this ongoing debate, arriving at the same conclusion as others in the literature that a pan-pathology fellowship match is ideal and that leadership from the Association of Pathology Chairs will be essential in unifying the fractured fellowship recruitment process.

Cytopathology fellowship and practice: Are our trainees and cytopathologists diverse?

Over the last several years, there has been increased focus on diversity, equity, and inclusion within all areas of pathology and laboratory medicine. Many of the specialty societies within pathology have taken up the mantle of diversity. While there is little research into the diversity of cytopathologists in practice, the Accreditation Council for Graduate Medical Education (ACGME) has been collecting diversity data on pathology and laboratory medicine trainees since 2011. This data are an opportunity to explore how diverse our trainees in cytopathology are, and by extrapolation, allows us to develop some ideas as to how diverse attending level cytopathologists are. The author will also share personal observations from her own training and career regarding diversity in cytopathology.

A multi-institutional survey of apheresis services among institutions in the United States

INTRODUCTION

Apheresis practices in the United States (US) have not been comprehensively characterized to date. This study aimed to address this gap by evaluating apheresis therapy through a national survey.

METHODS

A multi-institutional survey was conducted between April and July 2023. The survey, comprising 54 questions, focused on institutional demographics, procedures, equipment, staffing, training, and impacts of the Coronavirus Disease 2019 (COVID-19) pandemic. Responses from 22 institutions, primarily academic medical centers, were analyzed.

RESULTS

Therapeutic plasma exchange (TPE) was the most common procedure, followed by hematopoietic progenitor cell collection (HPC-A) and red blood cell exchange (RCE). CAR-T cell collections were widespread, with some institutions supporting over 30 protocols concurrently. Most sites used the Spectra Optia Apheresis System, were managed by a transfusion medicine service, and employed internal apheresis providers. Insufficient staffing levels, exacerbated by the COVID-19 pandemic, were common and most often addressed using overtime.

DISCUSSION

The survey highlighted the ubiquity of TPE, expanding cellular collections and staffing challenges. The role of apheresis in supporting cellular therapy, particularly in newly developing cell and gene therapies and clinical trials, was evident. Staffing issues during the pandemic emphasized the need for innovative recruitment strategies.

CONCLUSION

This nationwide survey provides the most comprehensive analysis to date of apheresis practices in large US academic centers.

Interactive Pathology Tutorial in Neoplastic Hematology Disorders for Medical Hematology-Oncology Fellows

Hematology-oncology (HO) fellows receive limited instruction in the process of establishing a diagnosis for hematologic neoplasms, and learning neoplastic hematology often occurs in limited encounters. In the current study, we developed a web-based interactive pathology tutorial in neoplastic hematologic disorders for HO fellows to work up simulated cases and establish the diagnosis. An online system ("Pathology Playground") was utilized to load case materials including microscopic images and ancillary studies. Twelve high-yield simulated cases of common leukemias and lymphoma were included. At the beginning of each case, trainees review the clinical history and slide images, and then, they are given the option to request additional pathology work-up. Based on the results, they can enter their diagnostic impression. If the diagnosis is correct, the user is shown a short educational presentation. If the diagnosis is not correct, the user gets notified by the message "Incorrect." The tutorial was integrated in the educational curriculum of our HO fellowship program, and bimonthly teaching sessions were held to review two cases each time. During the sessions, trainees request ancillary studies to complete the diagnostic work-up using the software and interpret the findings. As the case is being worked up by the trainee, the hematopathologists and HO fellowship program director discuss the findings, the appropriate work-up tools, and the implications on management. All of our six HO fellows attended the sessions, and a survey from the trainees showed high ease of use of the system and they viewed it as a very useful educational tool. A pre-test and post-test were administered for one of the sessions, and the result showed improvement in the average from 62 to 73%. Expanding the use of this online interactive tutorial and incorporating additional cases would enhance its value as a learning resource.

COVID and cytopathology training: Impact and innovations

Graduate medical education and training in Cytopathology faced numerous unexpected challenges during the COVID-19 pandemic of 2020. It was caused by the SARS-Co-V2 coronavirus and transmitted by breathing droplets or aerosol particles containing the virus and less commonly by contact with infected surfaces and fomites. To mitigate the rapid spread of disease non-essential services were closed, surgical procedures were prioritized, and "social distancing" was implemented. These measures led to a marked decline in the volume of specimens, number of fine needle aspiration (FNA) and rapid on-site evaluation procedures performed. The trainees in Pathology were required to stay at home either entirely or partly during the early period of the pandemic. This led to re-designing of the cytopathology training program nationwide. Many innovative methods and protocols were put in place to overcome the challenges faced and adjustments made in creating the virtual training program in Cytopathology. On May 5th, 2023, the WHO declared that COVID-19 was no longer a global emergency. Regulations were lifted and healthcare services returned to pre-pandemic era. Graduate medical education and training returned to normal however many changes were incorporated into the training program moving forward. Herein the impacts and innovations that COVID-19 had on Cytopathology training are described.

Impact of the adjunction of a short video to an original article for the recognition of newly described tumor entities in pathology: An interventional prospective study

CONTEXT

Merkel cell carcinoma diagnosis is often based on microscopic examination by pathologists. While histopathologic diagnosis primarily hinges on conscious and analytical cognition, the pathologist's decision-making process is also influenced by a rapid "gist" or "gestalt" approach. In this study, using cases of Merkel cell carcinoma as a model, we aim to assess how pathologists' viewing short videos containing conceptual clues and visual aids, in conjunction with reading an original article as a reference, may enhance their diagnostic performance.

METHOD

Sixteen pathologists were included in the present work. After participants had read the original article, their ability to distinguish Merkel cell polyomavirus (MCPyV)+ and MCPyV- Merkel cell carcinoma cases was evaluated on a first preliminary series of 20 cases. Following this test, the participants watched the video and then evaluated a second "experimental" series of 20 independent cases.

RESULTS

After reading the original article, for each case, a median number of 12 participants (75%, Q1-Q3: 10-13) classified the specimen in the correct category (92 incorrect answers in the whole series). An important interobserver variability was observed in this setting (Kappa coefficient = 0.465). By contrast, following the video, all cases were correctly classified by most of the participants, with only 12 incorrect answers on the whole series and excellent interobserver reproducibility (Kappa coefficient = 0.846).

CONCLUSION

Our study demonstrated that providing a short video together with an original article may enhance pathologists' performance in diagnosing Merkel cell carcinoma.

Medical students' preferences for asynchronous online or face-to-face learning strategies in learning gross anatomy and neuroanatomy during the COVID-19 pandemic

Gross anatomy and neuroanatomy are fundamental subjects in medical education. However, learning different anatomical terms and understanding the complexity of the subjects are often challenging for medical students. At National Taiwan University, the 2020-2021 cohort adopted a face-to-face (F2F) learning strategy for gross anatomy and neuroanatomy lecture and laboratory courses until May 17, 2021. After the aforementioned date, the same cohort learned the rest of the gross anatomy and neuroanatomy courses via asynchronous online learning. This study aimed to evaluate the benefits of and students' preferences for F2F and asynchronous online learning strategies in learning gross anatomy and neuroanatomy. A survey with closed-ended and open-ended questions was used to quantitatively and qualitatively explore medical students' learning preferences for two teaching strategies in gross anatomy and neuroanatomy. The results identified different learning preferences among students in learning gross anatomy and neuroanatomy-satisfied with both learning strategies, satisfied with only F2F learning strategy, satisfied with only asynchronous online learning strategy, and satisfied with neither learning strategy. The survey results with closed-ended and open-ended questions showed that medical students preferred F2F learning for anatomical laboratory courses but favored asynchronous online learning for neuroanatomical laboratory courses. In addition, medical students considered peer discussion more critical in learning gross anatomy than neuroanatomy. These findings provide valuable information about medical students' preference for gross anatomy and neuroanatomy courses, which anatomy teachers can consider when planning to enhance their curriculum in the future.

Patient-Portal Compared with Supplemental In-Office Tablet Screening for Health-Related Social Needs in Primary Care

BACKGROUND

Screening for health-related social needs (HRSN) has become more widespread but the best method of delivering the screening tool is not yet known.

OBJECTIVE

Describe HRSN screening completion rate, specifically portal-based and in-person tablet-based screening.

DESIGN

Cross-sectional retrospective observational study.

PARTICIPANTS

Adults age 18 or older who had a non-acute primary care visit at one of three internal medicine primary care clinics at a large, urban, academic medical center between July 2022 and July 2023.

MAIN MEASURES

We identified the proportion of individuals who were screened using the HRSN questionnaire, whether screening was completed by patient-portal or tablet, as well as the degree of burden of HRSN. Using the electronic health record, we explored associations between sociodemographic characteristics and HRSN attributes.

KEY RESULTS

Our study included 24,597 patients, of whom 37% completed the HRSN questionnaire. A smaller proportion of Black/African American patients and those with Medicaid insurance completed the questionnaire, yet they comprised a greater percentage of those who screened positive for unmet HRSN (p ≤ 0.001). Most patients completed the questionnaire by patient-portal (86.1%) compared with in-office tablets (14.0%). A larger proportion of those who completed screening by tablet screened positive for HRSN. Of all patients screened, 21.8% were positive for an unmet HRSN and 11.5% had more than one unmet HRSN.

CONCLUSIONS

A majority of patients are not being screened for HRSN and results illustrate disparities when screening patients for HRSN through portal-based compared with supplemental in-office tablet-based screening. Prevalence of unmet HRSN varied by demographics such as race and insurance status.

Responding to the workforce crisis: consensus recommendations from the Second Workforce Summit of the American Society of Pediatric Nephrology

IMPORTANCE

Pediatric patients with complex medical problems benefit from pediatric sub-specialty care; however, a significant proportion of children live greater than 80 mi. away from pediatric sub-specialty care.

OBJECTIVE

To identify current knowledge gaps and outline concrete next steps to make progress on issues that have persistently challenged the pediatric nephrology workforce.

EVIDENCE REVIEW

Workforce Summit 2.0 employed the round table format and methodology for consensus building using adapted Delphi principles. Content domains were identified via input from the ASPN Workforce Committee, the ASPN's 2023 Strategic Plan survey, the ASPN's Pediatric Nephrology Division Directors survey, and ongoing feedback from ASPN members. Working groups met prior to the Summit to conduct an organized literature review and establish key questions to be addressed. The Summit was held in-person in November 2023. During the Summit, work groups presented their preliminary findings, and the at-large group developed the key action statements and future directions.

FINDINGS

A holistic appraisal of the effort required to cover inpatient and outpatient sub-specialty care will help define faculty effort and time distribution. Most pediatric nephrologists practice in academic settings, so work beyond clinical care including education, research, advocacy, and administrative/service tasks may form a substantial amount of a faculty member's time and effort. An academic relative value unit (RVU) may assist in creating a more inclusive assessment of their contributions to their academic practice. Pediatric sub-specialties, such as nephrology, contribute to the clinical mission and care of their institutions beyond their direct billable RVUs. Advocacy throughout the field of pediatrics is necessary in order for reimbursement of pediatric sub-specialist care to accurately reflect the time and effort required to address complex care needs. Flexible, individualized training pathways may improve recruitment into sub-specialty fields such as nephrology.

CONCLUSIONS AND RELEVANCE

The workforce crisis facing the pediatric nephrology field is echoed throughout many pediatric sub-specialties. Efforts to improve recruitment, retention, and reimbursement are necessary to improve the care delivered to pediatric patients.

Application of Artificial Intelligence in the Headache Field

PURPOSE OF REVIEW

Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article.

RECENT FINDINGS

We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Roadmap for providing and leveraging annotated data by cytologists in the PDAC domain as open data: support for AI-based pathology image analysis development and data utilization strategies

Pancreatic cancer is one of the most lethal cancers worldwide, with a 5-year survival rate of less than 5%, the lowest of all cancer types. Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive pancreatic cancer and has been classified as a health emergency in the past few decades. The histopathological diagnosis and prognosis evaluation of PDAC is time-consuming, laborious, and challenging in current clinical practice conditions. Pathological artificial intelligence (AI) research has been actively conducted lately. However, accessing medical data is challenging; the amount of open pathology data is small, and the absence of open-annotation data drawn by medical staff makes it difficult to conduct pathology AI research. Here, we provide easily accessible high-quality annotation data to address the abovementioned obstacles. Data evaluation is performed by supervised learning using a deep convolutional neural network structure to segment 11 annotated PDAC histopathological whole slide images (WSIs) drawn by medical staff directly from an open WSI dataset. We visualized the segmentation results of the histopathological images with a Dice score of 73% on the WSIs, including PDAC areas, thus identifying areas important for PDAC diagnosis and demonstrating high data quality. Additionally, pathologists assisted by AI can significantly increase their work efficiency. The pathological AI guidelines we propose are effective in developing histopathological AI for PDAC and are significant in the clinical field.

TelePi: an affordable telepathology microscope camera system anyone can build and use

Telepathology facilitates histological diagnoses through sharing expertise between pathologists. However, the associated costs are high and frequently prohibitive, especially in low-resource settings, where telepathology would paradoxically be of paramount importance due to a paucity of pathologists.We have constructed a telepathology system (TelePi) with a budget of < €120 using the small, single-board computer Raspberry Pi Zero and its High-Quality Camera Module in conjunction with a standard microscope and open-source software. The system requires no maintenance costs or service contracts, has a small footprint, can be moved and shared across several microscopes, and is independent from other computer operating systems. TelePi uses a responsive and high-resolution web-based live stream which allows remote consultation between two or more locations. TelePi can serve as a telepathology system for remote diagnostics of frozen sections. Additionally, it can be used as a standard microscope camera for teaching of medical students and for basic research. The quality of the TelePi system compared favorable to a commercially available telepathology system that exceed its cost by more than 125-fold. Additionally, still images are of publication quality equal to that of a whole slide scanner that costs 800 times more.In summary, TelePi is an affordable, versatile, and inexpensive camera system that potentially enables telepathology in low-resource settings without sacrificing image quality.

Exploring p53 protein expression and its link to TP53 mutation in myelodysplasia-related malignancies-Interpretive challenges and potential field of applications

AIMS

TP53 alterations have a significant prognostic effect in myeloid neoplasms. Our objective was to investigate the TP53 gene mutation status, p53 protein expression and their relationship in dysplasia-related myeloid neoplasms with varying levels of myeloblast counts.

METHODS AND RESULTS

A total of 76 bone marrow biopsy samples with different blast counts were analysed. Total and strong (3+) p53 expression was determined. Dual immunohistochemical staining was performed to determine the cell population associated with p53 expression. NGS analysis was performed using the Accel-Amplicon Comprehensive TP53 panel. Both p53 expression and TP53 VAF showed a significant correlation with the myeloblast ratio (P < 0.0001); however, p53 expression was also present in other cell lineages. The VAF value exhibited a significant correlation with p53 expression. A high specificity (0.9800) was observed for TP53 mutation using the ≥ 10% strong (3+) p53 cut-off value, although the sensitivity (0.4231) was low.

CONCLUSIONS

Strong (3+) p53 expression using a ≥ 10% cut-off value accurately predicts TP53 mutation but does not reveal the allelic state. The p53 expression is significantly influenced by myeloblast count, and histological interpretation should consider the presence of intermixed non-neoplastic marrow cells with varying physiological p53 expression.

Comfort levels and experiences of middle school and high school age children in anatomical donor-based anatomy outreach sessions

Many health professions schools host anatomy outreach sessions for high school students that utilize anatomical donors. However, teaching with anatomical donors for younger learners is uncommon. This study aimed to assess the comfort levels and experiences of students who attended the anatomy sessions as part of summer programs at Rutgers New Jersey Medical School. Younger learners (students entering grades 7-10; n = 25) and older learners (students entering grades 11-12; n = 33) completed pre- and post-session surveys about their comfort using a 5-point Likert scale. Before the sessions, most students felt comfortable or very comfortable learning from isolated organs (μ = 2.7, SD = 1.3) or full-body donors (μ = 2.4, SD = 1.4), even though most have never been to an anatomical donor lab before. After the sessions, the comfort level significantly increased for both isolated organs (μ = 3.3, SD = 1.1; p = 0.02) and full-body donors (μ = 3.1, SD = 1.2; p = 0.004). For isolated organs, there was no significant difference in the comfort level between younger and older learners before (p = 0.50) or after (p = 0.56) the sessions. Similarly, for full-body donors, there was no significant difference in the comfort level between younger and older learners before (p = 0.95) or after (p = 0.75) the sessions. Most students expressed that the experience was unique and positive. In conclusion, most students entering grades 7-12 felt comfortable learning from isolated organs and full-body anatomical donors prior to the sessions and felt more comfortable after the sessions. With this, anatomy outreach programs that utilize anatomical donors could be expanded to include younger learners to provide more dynamic teaching experiences for students of various ages.

Improving Patient Portal Activation for Newborns in the Well Baby Nursery

BACKGROUND

Patient portals provide parents access to their child's health information and direct communication with providers. Our study aimed to improve portal activation rates of newborns during nursery hospitalization to >70% over 6 months. Secondarily, we describe the facilitators and barriers to portal use.

METHODS

The study design used a mixed-methodology framework of quality improvement (QI) and cross-sectional analyses. The Model for Improvement guided QI efforts. The primary outcome was the proportion of portals activated for newborns during nursery hospitalization. Interventions included portal activation algorithm, staff huddles, and documentation templates. Telephone interviews were conducted with a randomized sample of mothers of infants who activated the portal. These mothers were divided into portal "users" and "nonusers." We examined sociodemographic variables and health care utilization outcomes in the 2 groups.

RESULTS

Portal activation increased from 12.9% to 85.4% after interventions. Among 482 mothers with active portals, 127 (26.3%) were interviewed. Of those, 70% (89 of 127) reported using the portal, and 85.4% (76 of 89) found it useful. Reasons for accessing the portal included checking appointments and reviewing test results. Lack of knowledge of portal functionality was the main barrier to portal use (42.1%). Portal users were less likely to have a no-show to primary care appointments compared with nonusers (44.9% versus 78.9%, P < .001).

CONCLUSIONS

Portal activation rates increased after QI interventions in the nursery. Most parents accessed the portal and found it useful. Portals can improve health care delivery and patient engagement in the newborn period.

Science, Medicine, and Cytology: an educational program of the Diversity, Equity, and Inclusion Committee of the American Society of Cytopathology

INTRODUCTION

As our field of pathology continues to grow, our trainee numbers are on the decline. To combat this trend, the ASC Diversity, Equity, and Inclusion Committee established the Science, Medicine, and Cytology SumMer Certificate program to improve exposure to pathology/cytopathology with a focus on diversity, equity, and inclusion. Herein, we report our findings of the first 2 years of the program.

MATERIALS AND METHODS

An online course was developed targeting students who are underrepresented in medicine at the high school and college level. It consisted of several didactic sessions, presenting the common procedures involving cytopathologists and cytologists. Interviews with cytopathologists were also included. Participants were surveyed for demographic information and provided course evaluations.

RESULTS

In the first year of the program (2021), 34 participants completed the program, which increased to 103 in 2022. In both years there was a diversity in participant demographic backgrounds; however, only a minority of participants self-identified as being underrepresented in medicine. A vast majority (>85%) of participants in both years were high school or college students. In 2021, 100% of participants stated that the program format was effective and 94% thought the content was appropriate for their level of education; in 2022 the results were similar. In 2021, 66% considered health care as a potential career; this value increased in 2022 to 83%. In 2021 and 2022, 31% and 38%, respectively, considered cytology as a career.

CONCLUSIONS

Evaluations were excellent, generating interest in cytopathology. Barriers in reaching underrepresented minorities exist and additional work is needed. Expansion to a wider audience may increase outreach.

Learning pathways composed of core subjects with features of reducing cognitive load have better learning outcomes

BACKGROUND

Changing the course duration or timing of subjects in learning pathways would influence medical students' learning outcomes. Curriculum designers need to consider the strategy of reducing cognitive load and evaluate it continuously. Our institution underwent gradual curricular changes characterized by reducing cognitive load since 2000. Therefore, we wanted to explore the impact of this strategy on our previous cohorts.

METHODS

This cohort study explored learning pathways across academic years of more than a decade since 2000. Eight hundred eighty-two medical students between 2006 and 2012 were included eventually. Learning outcomes included an average and individual scores of subjects in different stages. Core subjects were identified as those where changes in duration or timing would influence learning outcomes and constitute different learning pathways. We examined whether the promising learning pathway defined as the pathway with the most features of reducing cognitive load has higher learning outcomes than other learning pathways in the exploring dataset. The relationship between features and learning outcomes was validated by learning pathways selected in the remaining dataset.

RESULTS

We found nine core subjects, constituting four different learning pathways. Two features of extended course duration and increased proximity between core subjects of basic science and clinical medicine were identified in the promising learning pathway 2012, which also had the highest learning outcomes. Other pathways had some of the features, and pathway 2006 without such features had the lowest learning outcomes. The relationship between higher learning outcomes and cognitive load-reducing features was validated by comparing learning outcomes in two pathways with and without similar features of the promising learning pathway.

CONCLUSION

An approach to finding a promising learning pathway facilitating students' learning outcomes was validated. Curricular designers may implement similar design to explore the promising learning pathway while considering potential confounding factors, including students, medical educators, and learning design of the course.

Assessment of Student Perceptions of Aspects of a Career in Radiation Oncology

PURPOSE

To determine medical students' views of various aspects of a career in radiation oncology (RO) to identify areas that may benefit from reform and to guide initiatives to stimulate broader and more diverse student interest in the specialty.

METHODS AND MATERIALS

An electronic survey was sent to student oncology interest group members at seven US medical schools. The survey asked students to rate 19 aspects of RO on a 5-point bipolar Likert-type scale. Descriptive statistics are reported, along with subgroup analyses based on participants' demographics.

RESULTS

The response rate was 51.1% (n = 275 of 538). The most favorably rated aspects of RO were outpatient working hours (mean ± SD Likert-type rating of 4.51 ± 0.82), routinely working with other physicians (4.45 ± 0.76), and use of advanced technology to treat patients. The most unfavorably rated aspects of RO were less geographic flexibility for residency or employment (1.98 ± 1.04), spending a lot of time on a computer doing treatment planning (2.80 ± 1.21), and having a job that is not well understood by most doctors and the general public (2.89 ± 1.02). Gender was associated with significant differences in 8 of 19 questions in how each aspect of RO was viewed. Few differences were observed based on race or ethnicity, though Asian participants had a significantly more favorable view of RO being a more science-oriented specialty compared with White or underrepresented students, respectively (3.50 versus 3.21 versus 2.84, P = .01).

CONCLUSIONS

These findings inform the RO community in the development of more effective initiatives to encourage students to fully explore the specialty.

#PathX: #PathTwitter's Transformation and a Discussion on Different Social Media Platforms Used by Pathologists in 2024

#PathTwitter is a well-known virtual community that has historically been positive for pathologists, trainees, and medical students worldwide to communicate, collaborate, and connect for free. However, in 2023, the popular social media platform Twitter (parent company: X Corp.) transitioned to "X" and, with this, #PathTwitter evolved into #PathX. Although the overall user experience of X and Twitter has not changed significantly, this transition brought much anecdotal hesitancy from the online virtual pathology community early on. Thus, the purpose of this review is to discuss the background of Twitter's importance in pathology, the implications of this transition to the online pathology community, current views from this community regarding Twitter versus X, and to provide an overview of pertinent changes in the platform, as well as of different popular social media platforms that may be used by pathologists in 2024.

Scoping Review Shows the Dynamics and Complexities Inherent to the Notion of "Responsibility" in Artificial Intelligence within the Healthcare Context

The increasing integration of artificial intelligence (AI) in healthcare presents a host of ethical, legal, social, and political challenges involving various stakeholders. These challenges prompt various studies proposing frameworks and guidelines to tackle these issues, emphasizing distinct phases of AI development, deployment, and oversight. As a result, the notion of responsible AI has become widespread, incorporating ethical principles such as transparency, fairness, responsibility, and privacy. This paper explores the existing literature on AI use in healthcare to examine how it addresses, defines, and discusses the concept of responsibility. We conducted a scoping review of literature related to AI responsibility in healthcare, searching databases and reference lists between January 2017 and January 2022 for terms related to "responsibility" and "AI in healthcare", and their derivatives. Following screening, 136 articles were included. Data were grouped into four thematic categories: (1) the variety of terminology used to describe and address responsibility; (2) principles and concepts associated with responsibility; (3) stakeholders' responsibilities in AI clinical development, use, and deployment; and (4) recommendations for addressing responsibility concerns. The results show the lack of a clear definition of AI responsibility in healthcare and highlight the importance of ensuring responsible development and implementation of AI in healthcare. Further research is necessary to clarify this notion to contribute to developing frameworks regarding the type of responsibility (ethical/moral/professional, legal, and causal) of various stakeholders involved in the AI lifecycle.

Dermatology residents' perspectives on virtual dermatopathology education

BACKGROUND

Dermatopathology education accounts for 30% of U.S. dermatology residency training. The COVID-19 pandemic expedited the implementation of virtual dermatopathology in place of traditional microscopy for resident education. This study examined U.S. dermatology residents' perceptions of virtual dermatopathology, as research in this area is lacking.

METHODS

An anonymous, confidential, institutional review board-approved survey was electronically distributed to U.S. dermatology residents consisting of 16 questions comparing attitudes towards virtual and traditional dermatopathology education. Responses were n = 59. Statistical analysis was performed using SAS software.

RESULTS

Participants believe virtual imaging is superior to conventional microscopy in schedule flexibility (96.6% vs. 1.7%, p < 0.0001), lecture convenience (94.8% vs. 0.0%, p < 0.0001), personal review (96.6% vs. 0.0%, p < 0.0001), cost-effectiveness (64.4% vs. 6.8%, p < 0.0001), and board exam preparation (52.5% vs. 16.9%, p = 0.0005). Conventional microscopy was favored for image quality (50.8% vs. 25.4%, p = 0.0127) and overall utility (50.8% vs. 27.1%, p = 0.0195).

CONCLUSIONS

Our study supports virtual dermatopathology utilization as a valuable tool in dermatology residency training. Also it is shown that conventional microscopy training continues to play a key role. Further studies should examine whether, if ever, virtual dermatopathology could gradually replace conventional microscopy with the advent of newer and more powerful digital and scanning technology.

Possible benefits, challenges, pitfalls, and future perspective of using ChatGPT in pathology

The much-hyped artificial intelligence (AI) model called ChatGPT developed by Open AI can have great benefits for physicians, especially pathologists, by saving time so that they can use their time for more significant work. Generative AI is a special class of AI model, which uses patterns and structures learned from existing data and can create new data. Utilizing ChatGPT in Pathology offers a multitude of benefits, encompassing the summarization of patient records and its promising prospects in Digital Pathology, as well as its valuable contributions to education and research in this field. However, certain roadblocks need to be dealt like integrating ChatGPT with image analysis which will act as a revolution in the field of pathology by increasing diagnostic accuracy and precision. The challenges with the use of ChatGPT encompass biases from its training data, the need for ample input data, potential risks related to bias and transparency, and the potential adverse outcomes arising from inaccurate content generation. Generation of meaningful insights from the textual information which will be efficient in processing different types of image data, such as medical images, and pathology slides. Due consideration should be given to ethical and legal issues including bias.

Differential utilization of the online patient portal for completion of health-related social needs screening during routine gynecologic cancer care

BACKGROUND

Telehealth technologies offer efficient ways to deliver health-related social needs (HRSN) screening in cancer care, but these methods may not reach all populations. The authors examined patient characteristics associated with using an online patient portal (OPP) to complete HRSN screening as part of gynecologic cancer care.

METHODS

From June 2021 to June 2023, patients in a gynecologic oncology clinic completed validated HRSN screening questions either (1) using the OPP (independently before the visit) or (2) in person (verbally administered by clinic staff). The authors examined the prevalence of HRSN according to activated OPP status and, in a restricted subgroup, used stepwise multivariate Poisson regression to identify associations between patient and visit characteristics and using the OPP.

RESULTS

Of 1616 patients, 87.4% (n = 1413) had an activated OPP. Patients with inactive OPPs (vs. activated OPPs) more frequently reported two or more needs (10% vs 5%; p < .01). Of 986 patients in the restricted cohort, 52% used the OPP to complete screening. The final multivariable model indicated that patients were less likely to use the OPP if they were Black (vs. White; adjusted relative risk [aRR], 0.70; 95% confidence interval [CI], 0.59-0.83); not employed (vs. employed; aRR, 0.81; 95% CI, 0.68-0.97), or had low measures of OPP engagement (aRR, 0.80; 95% CI, 0.68-0.92). New versus established patients were 21% more likely to use the OPP (aRR, 1.21; 95% CI, 1.06-1.38).

CONCLUSIONS

Differential use of the OPP suggested that over-reliance on digital technologies could limit the ability to reach those populations that have social factors already associated with cancer outcome disparities. Cancer centers should consider using multiple delivery methods for HRSN screening to maximize reach to all populations.

Developing an entrustable professional activity for providing health education and consultation in occupational therapy and examining its validity

BACKGROUND

Entrustable Professional Activities (EPA)-based assessment is easily and intuitively used in evaluating the learning outcomes of competency-based medical education (CBME). This study aimed to develop an EPA for occupational therapy focused on providing health education and consultation (TP-EPA3) and examine its validity.

METHODS

Nineteen occupational therapists who had completed online training on the EQual rubric evaluation participated in this study. An expert committee identified six core EPAs for pediatric occupational therapy. TP-EPA3 was developed following the EPA template and refined through consensus meetings. The EQual rubric, a 14-item, five-point criterion-based anchor system, encompassing discrete units of work (DU), entrustable, essential, and important tasks of the profession (EEIT), and curricular role (CR), was used to evaluate the quality of TP-EPA3. Overall scores below 4.07, or scores for DU, EEIT, and CR domains below 4.17. 4.00, and 4.00, respectively, indicate the need for modifications.

RESULTS

The TP-EPA3 demonstrated good validity, surpassing the required cut-off score with an average overall EQual score of 4.21 (SD = 0.41). Specific domain scores for DU, EEIT, and CR were 3.90 (SD = 0.69), 4.46 (SD = 0.44), and 4.42 (SD = 0.45), respectively. Subsequent revisions clarified observation contexts, enhancing specificity and focus. Further validation of the revised TP-EPA3 and a thorough examination of its reliability and validity are needed.

CONCLUSION

The successful validation of TP-EPA3 suggests its potential as a valid assessment tool in occupational therapy education, offering a structured approach for developing competency in providing health education and consultation. This process model for EPA development and validation can guide occupational therapists in creating tailored EPAs for diverse specialties and settings.

Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings

Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases.

Diagnostic Procedures for Inflammatory Bowel Disease: Laboratory, Endoscopy, Pathology, Imaging, and Beyond

Diagnosing inflammatory bowel disease (IBD) can often be challenging, and differentiating between Crohn's disease and ulcerative colitis can be particularly difficult. Diagnostic procedures for IBD include laboratory tests, endoscopy, pathological tests, and imaging tests. Serological and stool tests can be easily performed in an outpatient setting and provide critical diagnostic clues. Although endoscopy is an invasive procedure, it offers essential diagnostic information and allows for tissue biopsy and therapeutic procedures. Video capsule endoscopy and device-assisted enteroscopy are endoscopic procedures used to evaluate the small bowel. In addition to endoscopy, magnetic resonance imaging, computed tomography, and ultrasound (US) are valuable tools for small bowel assessment. Among these, US is noninvasive and easily utilized, making its use highly practical in daily clinical practice. Endoscopic biopsy aids in the diagnosis of IBD and is crucial for assessing the histological activity of the disease, facilitating a thorough evaluation of disease remission, and aiding in the development of treatment strategies. Recent advances in artificial intelligence hold promise for enhancing various aspects of IBD management, including diagnosis, monitoring, and precision medicine. This review compiles current procedures and promising future tools for the diagnosis of IBD, providing comprehensive insights.

How to overcome constraints imposed by microsporidian genome features to ensure gene prediction?

Since the advent of sequencing techniques and due to their continuous evolution, it has become easier and less expensive to obtain the complete genome sequence of any organism. Nevertheless, to elucidate all biological processes governing organism development, quality annotation is essential. In genome annotation, predicting gene structure is one of the most important and captivating challenges for computational biology. This aspect of annotation requires continual optimization, particularly for genomes as unusual as those of microsporidia. Indeed, this group of fungal-related parasites exhibits specific features (highly reduced gene sizes, sequences with high rate of evolution) linked to their evolution as intracellular parasites, requiring the implementation of specific annotation approaches to consider all these features. This review aimed to outline these characteristics and to assess the increasingly efficient approaches and tools that have enhanced the accuracy of gene prediction for microsporidia, both in terms of sensitivity and specificity. Subsequently, a final part will be dedicated to postgenomic approaches aimed at reinforcing the annotation data generated by prediction software. These approaches include the characterization of other understudied genes, such as those encoding regulatory noncoding RNAs or very small proteins, which also play crucial roles in the life cycle of these microorganisms.

Machine Learning-Enhanced Extraction of Biomarkers for High-Grade Serous Ovarian Cancer from Proteomics Data

Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow that was applied to unveil high-performing protein markers for high-grade serous ovarian carcinoma (HGSOC) from publicly available ovarian cancer tissue and serum proteomics datasets. Diagnosis of HGSOC, an aggressive form of ovarian cancer, currently relies on diagnostic methods based on tissue biopsy and/or non-specific biomarkers such as the cancer antigen 125 (CA125) and human epididymis protein 4 (HE4). Our newly developed ML-based approach enabled the identification of new serum proteomic biomarkers for HGSOC. The performance verification of these marker combinations using two independent cohorts affirmed their outperformance against known biomarkers for ovarian cancer including clinically used serum markers with >97% AUC. Our analysis also added novel biological insights such as enriched cancer-related processes associated with HGSOC.

Defining the value of medical microbiology consultation

Medical microbiologists, defined as doctoral-level laboratory directors with subspecialty training in medical microbiology, lead the clinical laboratory operations through activities such as clinical consultations, oversight of diagnostic testing menu, institutional leadership, education, and scholastic activities. However, unlike their clinical colleagues, medical microbiologists are largely unable to bill for clinical consultations performed within the hospital and, therefore, unable to generate relative value units or a similar quantifiable metric. As hospital budgets tighten and justification of staffing becomes a necessity, this may present a challenge to the medical microbiologist attempting to prove their value to the organization. To aid in providing tangible data, the Personnel Standards and Workforce subcommittee of the American Society for Microbiology conducted a multi-center study across seven medical centers to document clinical consultations and their impact. Consults were generated equally from internal (laboratory-based) and external (hospital-based) parties, with the majority directly impacting patient management. Near universal acceptance of the medical microbiologist's recommendation highlights the worth derived from their expertise. External consults required more time commitment from the medical microbiologist than internal consults, although both presented ample opportunity for secondary value, including impact through stewardship, education, clinical guidance, and cost reduction. This study is a description of the content and impact of consultations that underscore the importance of the medical microbiologist as a key member of the healthcare team.

IMPORTANCE

Medical microbiologists are invaluable to the clinical microbiology laboratory and the healthcare system as a whole. However, as medical microbiologists do not regularly generate relative value units, capturing and quantifying the value provided is challenging. As hospital budgets tighten, justification of staffing becomes a necessity. To aid in providing tangible data, the Personnel Standards and Workforce subcommittee of the American Society for Microbiology conducted a multi-center study across seven medical centers to document clinical consultations and their impact. To our knowledge, this is the first study to provide detailed evaluation of the consultative value provided by medical microbiologists.

Not in the file: How competency committees work with undocumented contributions

INTRODUCTION

Competence committees (CCs) centre their work around documentation of trainees' performance; undocumented contributions (i.e. informal, unrecorded material like personal judgements, experiential anecdotes and contextual information) evoke suspicion even though they may play a role in decision making. This qualitative multiple case study incorporates insights from a social practice perspective on writing to examine the use of undocumented contributions by the CCs of two large post-graduate training programmes, one in a more procedural (MP) speciality and the other in a less procedural (LP) one.

METHODS

Data were collected via observations of meetings and semi-structured interviews with CC members. In the analysis, conversations were organised into triptychs of lead-up, undocumented contribution(s), and follow-up. We then created thick descriptions around the undocumented contributions, drawing on conversational context and interview data to assign possible motivations and significance.

RESULTS

We found no instances in which undocumented contributions superseded the contents of a trainee's file or stood in for missing documentation. The number of undocumented contributions varied between the MP CC (six instances over two meetings) and the LP CC (22 instances over three meetings). MP CC discussions emphasised Entrustable Professional Activity (EPA) observations, whereas LP CC members paid more attention to narrative data. The divergent orientations of the CCs-adding an 'advis[ing]/guid[ing]' role versus focusing simply on evaluation-offers the most compelling explanation. In lead-ups, undocumented contributions were prompted by missing and flawed documentation, conflicting evidence and documentation at odds with members' perceptions. Recognising other 'red flags' in documentation often required professional experience. In follow-ups, purposes served by undocumented contributions varied with context and were difficult to generalise; we, therefore, provide deeper analysis of two vignettes to illustrate.

CONCLUSIONS

Our data suggest undocumented contributions often serve best efforts to ground decisions in documentation. We would encourage CC practices and policies be rooted in more nuanced approaches to documentation.

Does high body mass index (>25 kg/m2) or weight (>80 kg) reduce the effectiveness of anti-D prophylaxis in Rh(D)-negative pregnant women? A systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

Haemolytic disease of the foetus and newborn (HDFN) occurs when maternal antibodies, often triggered by foetal antigens, destroy foetal and neonatal red blood cells. Factors like antibody strength, quantity and gestational age influence HDFN severity. Routine antenatal anti-D prophylaxis (RAADP) has significantly reduced HDFN cases. However, the effect of overweight/obesity (body mass index [BMI] > 25/30 kg/m2) on anti-D prophylaxis efficacy remains unclear. This systematic review will examine the impact of BMI on anti D prophylaxis effectiveness in Rh(D) negative pregnant women.

MATERIALS AND METHODS

We conducted a systematic review and meta-analysis following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocols. We searched databases from 1996 to 2023, focusing on studies exploring the link between high BMI/weight and anti-D serum levels in Rh(D)-negative pregnant women with Rh(D)-positive foetuses. Ten eligible studies were included, three suitable for meta-analysis. Study quality was assessed using the Strengthening the Reporting Observation Studies in Epidemiology (STROBE) checklist. Statistical analyses included Pearson correlation coefficients and risk differences.

RESULTS

Our meta-analysis revealed a significant negative correlation (r = -0.59, 95% confidence interval [CI]: -0.83 to -0.35, p = 0.007) between high BMI/weight and serial anti-D levels in in Rh(D)-negative pregnant women with Rh(D)-positive foetuses. High BMI/weight had lower odds of serial anti-D level exceeding 30 ng/mL (arcsine risk difference [ARD] = 0.376, 95% CI: 0.143-0.610, p = 0.002). Heterogeneity among studies was low (I2 = 0).

CONCLUSION

While our analysis suggests a potential linkage between high BMI/weight and reduced efficacy of anti-D prophylaxis, caution is warranted due to study limitations. Variability in study design and confounding factors necessitate careful interpretation. Further research is needed to confirm these findings and refine clinical recommendations.

Ethical Checklists for Clinical Research Projects and laboratory medicine: two tools to evaluate compliance with bioethical principles in different settings

OBJECTIVES

To develop two ethical checklists to evaluate (i) management of ethical concerns in research projects and (ii) awareness of ethical conduct of healthcare laboratory professionals.

METHODS

Comprehensive discussion among the members of IFCC Task Force on Ethics based on pertinent literature.

RESULTS

This Checklist for Clinical Research Projects should be useful to evaluate research proposals from an ethical perspective before submitting it to an IRB or its equivalent, thereby diminishing rejection rates and resulting in more time-effective projects. The checklist designed to evaluate the ethical conduct in laboratory medicine could be useful for self evaluation (internal audits) and for certification/accreditation processes performed by third parties.

CONCLUSIONS

These checklists are simple but powerful tools useful to guide professionals to adhere to ethical principles in their practice, especially in developing countries where accredited ethics committees may be difficult to find.

Potential rapid intraoperative cancer diagnosis using dynamic full-field optical coherence tomography and deep learning: A prospective cohort study in breast cancer patients

An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical coherence tomography (D-FFOCT), a label-free optical imaging method, and deep learning for bedside tumor diagnosis during surgery. To classify the benign and malignant breast tissues, we conducted a prospective cohort trial. In the modeling group (n = 182), D-FFOCT images were captured from April 26 to June 20, 2018, encompassing 48 benign lesions, 114 invasive ductal carcinoma (IDC), 10 invasive lobular carcinoma, 4 ductal carcinoma in situ (DCIS), and 6 rare tumors. Deep learning model was built up and fine-tuned in 10,357 D-FFOCT patches. Subsequently, from June 22 to August 17, 2018, independent tests (n = 42) were conducted on 10 benign lesions, 29 IDC, 1 DCIS, and 2 rare tumors. The model yielded excellent performance, with an accuracy of 97.62%, sensitivity of 96.88% and specificity of 100%; only one IDC was misclassified. Meanwhile, the acquisition of the D-FFOCT images was non-destructive and did not require any tissue preparation or staining procedures. In the simulated intraoperative margin evaluation procedure, the time required for our novel workflow (approximately 3 min) was significantly shorter than that required for traditional procedures (approximately 30 min). These findings indicate that the combination of D-FFOCT and deep learning algorithms can streamline intraoperative cancer diagnosis independently of traditional pathology laboratory procedures.

How (Cautious) Social Media Use May Improve Education and Pipeline Efforts of a Growing Postpandemic Forensic Pathologist Workforce Shortage

ABSTRACT

Many subspecialties of pathology have initiated novel methods and strategies to connect with medical students and residents, stimulate interest, and offer mentorship. Emerging concern about the future of forensic pathology has been highlighted in contemporary literature as recruitment of new fellows has stagnated and workforce shortage concerns have blossomed. Amidst these challenges, the potential role of social networking platforms like social media (SoMe) in enhancing autopsy pathology/forensics education has garnered attention, yet literature focusing specifically on its application in autopsy and forensic pathology remains limited. This review aims to provide a comprehensive narrative overview of the current literature on the established uses of SoMe in forensic pathology. It seeks to build upon existing recommendations, introducing a contemporary compilation of online resources designed to facilitate virtual engagement among pathologists, learners, patients, and families. The review supports the idea that strategic, ethical, and conscientious use of SoMe has a place in addressing the growing workforce shortages and closing educational gaps in forensic pathology by enhancing exposure to the field and dispelling antiquated stereotypes.

Representation of International Medical Graduates Among Diagnostic Radiology Chairs, Neuroradiology Chiefs, and Program Directors

RATIONALE AND OBJECTIVES

The number of international medical graduates (IMGs) entering radiology residencies and neuroradiology fellowships averaged 9.7% and 20.9% from 2021 to 2023, respectively. We aimed to determine whether IMG graduates are populating leadership roles at a proportionate rate in diagnostic radiology (DR) and neuroradiology.

MATERIALS AND METHODS

We surveyed 191 DR program directors, 94 neuroradiology program directors (PDs), 192 chairs of radiology, and 91 directors of neuroradiology inquiring about their original citizenship and medical school (American Medical Graduates [AMG] vs IMG). We reviewed institutional websites to obtain missing data and recorded H indices for each person using Scopus.

RESULTS

We confirmed the original citizenship and medical school location in 61-75% and 93-98% of each leadership group. We found that 16.2% of DR program directors, 43.7% of neuroradiology PDs, 28.5% of Chairs, and 40.6% of neuroradiology directors were not originally US citizens. The IMG rate was 18/188 (9.6%), 20/90 (22.2%), 26/186 (14.0%), and 19/85 (22.4%) for the same groups respectively. The most common country of origin and medical school cited was India for all leadership groups. IMGs had a median H index of 14 while AMG 10, significantly different (p = 0.021) CONCLUSION: Compared to the rate of diagnostic and neuroradiology trainees entering from 2021 to 2023, IMGs are proportionately represented at the leadership positions studied. The H index of the IMGs was higher than AMG. We conclude that IMGs have made substantial and proportionate inroads in radiology and neuroradiology leadership.

Medical laboratory scientist motivation to pursue graduate education

BACKGROUND

Medical laboratory staffing shortages have persisted, with challenges in maintaining adequate medical laboratory professionals. The career trajectory for medical laboratory scientists beyond entry level is ambiguous, but advancement opportunities are enhanced with specialist certifications and advanced degrees.

OBJECTIVE

This study explored the motivation and preferences of medical laboratory scientists in pursuing graduate medical laboratory science education based on the importance of professional development, career advancement, recognition, and employment benefits.

METHODS

A quantitative, cross-sectional, and descriptive correlational study surveyed American Society for Clinical Pathology Board of Certification-credentialed medical laboratory scientists using an online questionnaire.

RESULTS

The overall response rate was 2.5%, and 1247 complete surveys were analyzed. Educational preferences varied by respondent age and amount of laboratory experience. Professional development, career advancement, recognition, and employment benefits were all important motivators for seeking graduate degrees, but those who were younger and had less experience indicated they were more important.

CONCLUSION

This study suggests several areas of improvement for educational programs, health care organizations, and professional organizations to support the motivation of medical laboratory scientists to pursue graduate education.

Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art

Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premalignant disease manifesting as large polyps, greater accuracy in diagnostic and therapeutic precision is needed right from the time of first endoscopic encounter. Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocyanine green (ICG)) can enable colonoscopic tissue classification and prognostic stratification for significant polyps, in a similar manner to contemporary dynamic radiological perfusion imaging but with the advantage of being able to do so directly within interventional procedural time frames. It can provide an explainable method for immediate digital biopsies that could guide or even replace traditional forceps biopsies and provide guidance re margins (both areas where current practice is only approximately 80% accurate prior to definitive excision). Here, we discuss the concept and practice of AI enhanced ICG perfusion analysis for rectal cancer surgery while highlighting recent and essential near-future advancements. These include breakthrough developments in computer vision and time series analysis that allow for real-time quantification and classification of fluorescent perfusion signals of rectal cancer tissue intraoperatively that accurately distinguish between normal, benign, and malignant tissues in situ endoscopically, which are now undergoing international prospective validation (the Horizon Europe CLASSICA study). Next stage advancements may include detailed digital characterisation of small rectal malignancy based on intraoperative assessment of specific intratumoral fluorescent signal pattern. This could include T staging and intratumoral molecular process profiling (e.g. regarding angiogenesis, differentiation, inflammatory component, and tumour to stroma ratio) with the potential to accurately predict the microscopic local response to nonsurgical treatment enabling personalised therapy via decision support tools. Such advancements are also applicable to the next generation fluorophores and imaging agents currently emerging from clinical trials. In addition, by providing an understandable, applicable method for detailed tissue characterisation visually, such technology paves the way for acceptance of other AI methodology during surgery including, potentially, deep learning methods based on whole screen/video detailing.

Medical student interactions with children in their daily lives

Learning to communicate effectively with children in clinical interactions can be challenging. This study aimed to determine the extent to which medical students are exposed to children in their daily lives, in order to understand the experience students bring when entering paediatric rotations.

METHODS

A cross-sectional survey of medical students entering paediatric rotations from two medical schools was conducted. Students were asked to rate the frequency of their interactions with infants, preschool-aged and school-aged children and their confidence in doing so.

RESULTS

339 out of 476 students participated in this study. Interactions with infants and preschool-aged children were rare, with most students reporting interactions once or two times per year or less (83% and 67%, respectively). Students interacted with school-aged children more frequently (43% most weeks or days). Students who interacted more frequently with children were more confident when entering their paediatric placements.

CONCLUSIONS

Medical students have limited exposure to infants and preschool-aged children in their daily lives and this affects their confidence. Supervisors should incorporate activities aimed at building confidence interacting with young children early in clinical attachments.

Quality indicators in respiratory therapy

Quality indicators in healthcare refer to measurable and quantifiable parameters used to assess and monitor the performance, effectiveness, and safety of healthcare services. These indicators provide a systematic way to evaluate the quality of care offered, and thereby to identify areas for improvement and to ensure that patient care meets established standards and best practices. Respiratory therapists play a vital role in areas of clinical administration such as infection control practices and quality improvement initiatives. Quality indicators serve as essential metrics for respiratory therapy departments to assess and enhance the overall quality of care. By systematically tracking and analyzing indicators related to infection control, treatment effectiveness, and adherence to protocols, respiratory care practitioners can identify areas to improve and implement evidence-based changes. This article reviewed how to identify, implement, and monitor quality indicators specific to the respiratory therapy departments to set benchmarks and enhance patient outcomes.

ChatGPT prompts for generating multiple-choice questions in medical education and evidence on their validity: a literature review

ChatGPT's role in creating multiple-choice questions (MCQs) is growing but the validity of these artificial-intelligence-generated questions is unclear. This literature review was conducted to address the urgent need for understanding the application of ChatGPT in generating MCQs for medical education. Following the database search and screening of 1920 studies, we found 23 relevant studies. We extracted the prompts for MCQ generation and assessed the validity evidence of MCQs. The findings showed that prompts varied, including referencing specific exam styles and adopting specific personas, which align with recommended prompt engineering tactics. The validity evidence covered various domains, showing mixed accuracy rates, with some studies indicating comparable quality to human-written questions, and others highlighting differences in difficulty and discrimination levels, alongside a significant reduction in question creation time. Despite its efficiency, we highlight the necessity of careful review and suggest a need for further research to optimize the use of ChatGPT in question generation. Main messages  Ensure high-quality outputs by utilizing well-designed prompts; medical educators should prioritize the use of detailed, clear ChatGPT prompts when generating MCQs. Avoid using ChatGPT-generated MCQs directly in examinations without thorough review to prevent inaccuracies and ensure relevance. Leverage ChatGPT's potential to streamline the test development process, enhancing efficiency without compromising quality.

Effects of remote ischemic preconditioning on early markers of intestinal injury in experimental hemorrhage in rats

The maintenance of intestinal integrity and barrier function under conditions of restricted oxygen availability is crucial to avoid bacterial translocation and local inflammation. Both lead to secondary diseases after hemorrhagic shock and might increase morbidity and mortality after surviving the initial event. Monitoring of the intestinal integrity especially in the early course of critical illness remains challenging. Since microcirculation and mitochondrial respiration are main components of the terminal stretch of tissue oxygenation, the evaluation of microcirculatory and mitochondrial variables could identify tissues at risk during hypoxic challenges, indicate an increase of intestinal injury, and improve our understanding of regional pathophysiology during acute hemorrhage. Furthermore, improving intestinal microcirculation or mitochondrial respiration, e.g. by remote ischemic preconditioning (RIPC) that was reported to exert a sufficient tissue protection in various tissues and was linked to mediators with vasoactive properties could maintain intestinal integrity. In this study, postcapillary oxygen saturation (µHbO2), microvascular flow index (MFI) and plasmatic D-lactate concentration revealed to be early markers of intestinal injury in a rodent model of experimental hemorrhagic shock. Mitochondrial function was not impaired in this experimental model of acute hemorrhage. Remote ischemic preconditioning (RIPC) failed to improve intestinal microcirculation and intestinal damage during hemorrhagic shock.