Medical Literature Research Articles

Machine learning in cardiac stress test interpretation: a systematic review

Abstract Coronary artery disease (CAD) is a leading health challenge worldwide. Exercise stress testing is a foundational non-invasive diagnostic tool. Nonetheless, its variable accuracy prompts the exploration of more reliable methods. Recent advancements in machine learning (ML), including deep learning and natural language processing, have shown potential in refining the interpretation of stress testing data. Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic review of ML applications in stress electrocardiogram (ECG) and stress echocardiography for CAD prognosis. Medical Literature Analysis and Retrieval System Online, Web of Science, and the Cochrane Library were used as databases. We analysed the ML models, outcomes, and performance metrics. Overall, seven relevant studies were identified. Machine-learning applications in stress ECGs resulted in sensitivity and specificity improvements. Some models achieved rates of above 96% in both metrics and reduced false positives by up to 21%. In stress echocardiography, ML models demonstrated an increase in diagnostic precision. Some models achieved specificity and sensitivity rates of up to 92.7 and 84.4%, respectively. Natural language processing applications enabled the categorization of stress echocardiography reports, with accuracy rates nearing 98%. Limitations include a small, retrospective study pool and the exclusion of nuclear stress testing, due to its well-documented status. This review indicates the potential of artificial intelligence applications in refining CAD stress testing assessment. Further development for real-world use is warranted.

Is Incentive Spirometry Superior to Standard Care in Postoperative Cardiac Surgery on Clinical Outcomes and Length of Hospital and Intensive Care Unit Stay? A Systematic Review with Meta-Analysis.

Cardiac surgery is a frequent surgical procedure and may present a high risk of complications. Among the prophylactic strategies studied to decrease the rates of negative outcomes, respiratory care seems to reduce pulmonary complications. Incentive spirometry (IS) is a low-cost, respiratory exercise technique, used for the prevention and treatment of postoperative pulmonary complications (PPC). The aim of this review was to evaluate whether IS is superior to respiratory care, mobilization exercises, and noninvasive ventilation on PPC, and clinical outcomes. Systematic review. Medical Literature Analysis and Retrieval System Online (or MEDLINE®), Embase®, Cochrane Central Register of Controlled Trials (or CENTRAL), Physiotherapy Evidence Database (or PEDro), Cumulative Index of Nursing and Allied Health (or CINAHL®), Latin American and Caribbean Health Sciences Literature (or LILACS), Scientific Electronic Library Online (or SciELO), Allied, Scopus®, and OpenGrey databases, clinical trial registration sites, conferences, congresses, and symposiums were searched. Twenty-one randomized trials and one quasi-randomized trial (1,677 participants) were included. For partial pressure of oxygen (PaO2), IS was inferior to respiratory care (mean difference [MD] -4.48; 95% confidence interval [CI] -8.32 to -0.63). Flow-oriented IS was inferior to respiratory care on PaO2 (MD -4.53; 95% CI -8.88 to -0.18). However, compared to respiratory care, flow-oriented IS was superior on recovery vital capacity. This meta-analysis revealed that IS was not superior to standard respiratory care for PPCs and clinical outcomes, therefore its use should not be widely recommended until further studies with high quality be performed to ensure this clinical guidance.

Transparent medical image AI via an image-text foundation model grounded in medical literature.

Building trustworthy and transparent image-based medical artificial intelligence (AI) systems requires the ability to interrogate data and models at all stages of the development pipeline, from training models to post-deployment monitoring. Ideally, the data and associated AI systems could be described using terms already familiar to physicians, but this requires medical datasets densely annotated with semantically meaningful concepts. In the present study, we present a foundation model approach, named MONET (medical concept retriever), which learns how to connect medical images with text and densely scores images on concept presence to enable important tasks in medical AI development and deployment such as data auditing, model auditing and model interpretation. Dermatology provides a demanding use case for the versatility of MONET, due to the heterogeneity in diseases, skin tones and imaging modalities. We trained MONET based on 105,550 dermatological images paired with natural language descriptions from a large collection of medical literature. MONET can accurately annotate concepts across dermatology images as verified by board-certified dermatologists, competitively with supervised models built on previously concept-annotated dermatology datasets of clinical images. We demonstrate how MONET enables AI transparency across the entire AI system development pipeline, from building inherently interpretable models to dataset and model auditing, including a case study dissecting the results of an AI clinical trial.

Malignant Infantile Osteopetrosis Masquerading as Isolated Fetal Femoral Fracture: First Indian Case Report and Review of Literature

AbstractMalignant infantile osteopetrosis is a rare case of isolated fetal femoral fracture, a scarcely documented phenomenon in medical literature. Through detailed examination and genetic testing, it unveils malignant infantile osteopetrosis as an unexpected etiology, challenging existing diagnostic paradigms. This groundbreaking case emphasizes the critical role of genetic testing in unraveling complex fetal anomalies and underscores the necessity for comprehensive approaches in prenatal diagnostics, offering new insights into prenatal manifestations of skeletal dysplasias.

Validating the knowledge represented by a self-organizing map with an expert-derived knowledge structure.

Professionals are reluctant to make use of machine learning results for tasks like curriculum development if they do not understand how the results were generated and what they mean. Visualizations of peer reviewed medical literature can summarize enormous amounts of information but are difficult to interpret. This article reports the validation of the meaning of a self-organizing map derived from the Medline/PubMed index of peer reviewed medical literature by its capacity to coherently summarize the references of a core psychiatric textbook. Reference lists from ten editions of Kaplan and Sadock's Comprehensive Textbook of Psychiatry were projected onto a self-organizing map trained on Medical Subject Headings annotating the complete set of peer reviewed medical research articles indexed in the Medline/PubMed database (MedSOM). K-means clustering was applied to references from every edition to examine the ability of the self-organizing map to coherently summarize the knowledge contained within the textbook. MedSOM coherently clustered references into six psychiatric knowledge domains across teneditions (1967-2017). Clustering occurred at the abstract level of broad psychiatric practice including General/adult psychiatry, Child psychiatry, and Administrative psychiatry. The uptake of visualizations of published medical literature by medical experts for purposes like curriculum development depends upon validation of the meaning of the visualizations. The current research demonstrates that a self-organizing map (MedSOM) can validate the stability and coherence of the references used to support the knowledge claims of a standard psychiatric textbook, linking the products of machine learning to a widely accepted standard of knowledge.

On the formation of Russian pulmonology: the development of the doctrine of lung diseases (first half of the 20th century)

The articles on the history of Russian pulmonology presented in the historical, medical and therapeutic literature contain materials for this history, but their authors did not solve the problem of its consistent presentation, highlighting the stages of formation and founders. The authors of this study critically reviewed the literary and archival primary sources, for the first time proposed the identification of three stages in the development of Russian pulmonology and indicated eight of its founders at these stages. The abundance of material did not allow us to present it in one article. This article is devoted to the 1st stage of the history of pulmonology - the formation of the doctrine of lung diseases. The second (development of pulmonology as an independent scientific direction in internal diseases) and the third (organizational design of pulmonology as a new independent clinical scientific and educational discipline and medical specialty, i.e. its institutionalization) stages will be discussed in the next articles.

SYNE1 gene mutation: A recessive ataxic syndrome presenting with weakness and muscle atrophy. A case report

BackgroundAutosomal recessive spinocerebellar ataxia type 8 (SCAR8) is a rare neurodegenerative disease that can be manifest in a wide spectrum from ataxias and motoneuron syndromes. ObjectiveTo report a case of mutation in the SYNE1 gene with predominant motoneuron disease signs. MethodsIndex case medical report and literature review. ResultsA 32-year-old woman onset with pyramidal and lower motoneuron signs and symptoms during the second decade of life, with marked dysarthria showing associated cerebellar pattern. Clinical investigation with electroneuromyography showed chronic preganglionic disease and brain MRI showed cerebellar atrophy. Genetic testing confirmed pathogenic mutation in homozygosity in the SYNE1 gene. ConclusionsRare neurological condition that may be associated with signs of impairment of the pyramidal pathway and second motoneuron (amyotrophic lateral sclerosis-like syndrome), in addition to cerebellar ataxia in insidious course.

Fostering engagement in virtual anatomy learning for healthcare students

BackgroundThe use of virtual learning platforms is on the rise internationally, however, successful integration into existing curricula is a complex undertaking fraught with unintended consequences. Looking beyond medical and pedagogic literature can provide insight into factors affecting the user experience. The technology acceptance model, widely used in software evaluation, can be used to identify barriers and enablers of engagement with virtual learning platforms. Here, the technology acceptance model was used to scaffold the exploration of the factors that influenced students' perceptions of the virtual anatomy platform, Anatomage and how these shaped their intention to use it.MethodsFocus groups identified factors influencing students use of the Anatomage tables. Interventions were rolled out to address these findings, then further focus groups and the technology acceptance model identified how factors including self-efficacy, enjoyment, and social norms influenced students’ intention to use the Anatomage table in the future.ResultsStudents raised significant concerns about understanding how to use the Anatomage table. Moreover, students who considered themselves to be poor at using technology perceived the Anatomage table as more complicated to use. The subjective norm of the group significantly altered the perceived ease of use and usefulness of the Anatomage. However, enjoyment had the greatest impact in influencing both perceived usefulness and perceived ease of use. Indicating that enjoyment is the largest contributing factor in altering technology engagement in healthcare cohorts and has the biggest potential to be manipulated to promote engagement.ConclusionsFocus groups used in tandem with the technology acceptance model provide an effective way to understand student perceptions around technology used in the healthcare curricula. This research determined interventions that promote student engagement with virtual learning platforms, which are important in supporting all healthcare programmes that incorporate technology enhanced learning.

Risk of Corneal Transplant Rejection Following COVID-19 Vaccination: A Systematic Review and Meta-analysis.

The COVID-19 pandemic has initiated an unparalleled global vaccination campaign, raising concerns about the vaccine's effects on various health conditions, including the risk of corneal transplant rejection. This systematic review aimed to identify the relationship between COVID-19 vaccination and rejection of corneal transplant, filling a significant gap in the existing medical literature. A literature search was performed across multiple databases up to February 12, 2024, to identify studies evaluating the risk of corneal transplant rejection post-COVID-19 vaccination. Eligible studies were original research that reported outcomes of corneal graft rejection following vaccination. Nested Knowledge web software facilitated screening and data extraction. The Newcastle-Ottawa Scale was employed for quality assessment. A meta-analysis was conducted to calculate the aggregated relative risk (RR) utilizing R software version 4.3. Six studies were included in the qualitative synthesis, with four meeting the criteria for meta-analysis. These studies varied in geographic location, surgical techniques, and types of vaccines used. The pooled RR for corneal transplant rejection following COVID-19 vaccination was 0.816 (95% CI 0.178-1.453), indicating no significant risk of rejection. No statistical heterogeneity was observed among the studies (I2 = 0%). This review and meta-analysis found no significant evidence that COVID-19 vaccination increases the risk of corneal graft rejection. However, the current evidence is insufficient to conclusively determine the vaccine's safety for corneal transplant recipients. These findings underscore the need for additional research to confirm these preliminary results and investigate the long-term effects of COVID-19 vaccination on corneal transplants, aiming to provide evidence-based guidance to healthcare providers and patients.

Performance of ChatGPT on Factual Knowledge Questions Regarding Clinical Pharmacy.

ChatGPT is a language model that was trained on a large dataset including medical literature. Several studies have described the performance of ChatGPT on medical exams. In this study, we examine its performance in answering factual knowledge questions regarding clinical pharmacy. Questions were obtained from a Dutch application that features multiple-choice questions to maintain a basic knowledge level for clinical pharmacists. In total, 264 clinical pharmacy-related questions were presented to ChatGPT and responses were evaluated for accuracy, concordance, quality of the substantiation, and reproducibility. Accuracy was defined as the correctness of the answer, and results were compared to the overall score by pharmacists over 2022. Responses were marked concordant if no contradictions were present. The quality of the substantiation was graded by two independent pharmacists using a 4-point scale. Reproducibility was established by presenting questions multiple times and on various days. ChatGPT yielded accurate responses for 79% of the questions, surpassing pharmacists' accuracy of 66%. Concordance was 95%, and the quality of the substantiation was deemed good or excellent for 73% of the questions. Reproducibility was consistently high, both within day and between days (>92%), as well as across different users. ChatGPT demonstrated a higher accuracy and reproducibility to factual knowledge questions related to clinical pharmacy practice than pharmacists. Consequently, we posit that ChatGPT could serve as a valuable resource to pharmacists. We hope the technology will further improve, which may lead to enhanced future performance.

Repurposing non-pharmacological interventions for Alzheimer's disease through link prediction on biomedical literature

Non-pharmaceutical interventions (NPI) have great potential to improve cognitive function but limited investigation to discover NPI repurposing for Alzheimer's Disease (AD). This is the first study to develop an innovative framework to extract and represent NPI information from biomedical literature in a knowledge graph (KG), and train link prediction models to repurpose novel NPIs for AD prevention. We constructed a comprehensive KG, called ADInt, by extracting NPI information from biomedical literature. We used the previously-created SuppKG and NPI lexicon to identify NPI entities. Four KG embedding models (i.e., TransE, RotatE, DistMult and ComplEX) and two novel graph convolutional network models (i.e., R-GCN and CompGCN) were trained and compared to learn the representation of ADInt. Models were evaluated and compared on two test sets (time slice and clinical trial ground truth) and the best performing model was used to predict novel NPIs for AD. Discovery patterns were applied to generate mechanistic pathways for high scoring candidates. The ADInt has 162,212 nodes and 1,017,284 edges. R-GCN performed best in time slice (MR = 5.2054, Hits@10 = 0.8496) and clinical trial ground truth (MR = 3.4996, Hits@10 = 0.9192) test sets. After evaluation by domain experts, 10 novel dietary supplements and 10 complementary and integrative health were proposed from the score table calculated by R-GCN. Among proposed novel NPIs, we found plausible mechanistic pathways for photodynamic therapy and Choerospondias axillaris to prevent AD, and validated psychotherapy and manual therapy techniques using real-world data analysis. The proposed framework shows potential for discovering new NPIs for AD prevention and understanding their mechanistic pathways.

Describing the Landscape of Medical Education Preprints on MedRxiv: Current Trends and Future Recommendations.

A preprint is a version of a research manuscript posted to a preprint server prior to peer review. Preprints enable authors to quickly and openly share research, afford opportunities for expedient feedback, and enable immediate listing of research on grant and promotion applications. In medical education, most journals welcome preprints, which suggests preprints play a role in the field's discourse. Yet, little is known about medical education preprints, including author characteristics, preprint use, and ultimate publication status. This study provides an overview of preprints in medical education to better understand their role in the field's discourse. The authors queried medRxiv, a preprint repository, to identify preprints categorized as "medical education" and downloaded related metadata. CrossRef was queried to gather information on preprints later published in journals. Data were analyzed using descriptive statistics. Between 2019 and 2022, 204 preprints were classified in medRxiv as "medical education," with most deposited in 2021 (n = 76, 37.3%). On average, preprint full-texts were downloaded 1,875.2 times, and all were promoted on social media. Preprints were authored, on average, by 5.9 authors. Corresponding authors were based in 41 countries, with 45.6% in the United States, United Kingdom, and Canada. Almost half (n = 101, 49.5%) became published articles in predominantly peer-reviewed journals. Preprints appeared in 65 peer-reviewed journals, with BMC Medical Education (n = 9, 8.9%) most represented. Medical education research is being deposited as preprints, which are promoted, heavily accessed, and subsequently published in peer-reviewed journals, including medical education journals. Considering the benefits of preprints and the slowness of medical education publishing, it is likely that preprint depositing will increase and preprints will be integrated into the field's discourse. The authors propose next steps to facilitate responsible and effective creation and use of preprints.

Neuropsychiatric Manifestations and Cognitive Decline in Patients With Long-Standing Lyme Disease: A Scoping Review.

Lyme disease (LD), or Lyme borreliosis, is a vector-borne disease that is caused by the transmission of the bacterium Borrelia burgdorferi through a tick bite. The symptoms of LD can persist in individuals chronically, even after the treatment and resolution of the initial infection. These symptoms include various neuropsychiatric manifestations and cognitive decline. The purpose of this review was to report the neuropsychiatric manifestations, cognitive decline, and effects of a delayed diagnosis on symptom severity in patients with long-standing LD (LSLD). A scoping review was conducted utilizing the electronic databases Embase, Ovid Medical Literature Analysis and Retrieval System Online (MEDLINE), and Web of Science. A total of 744 articles were retrieved and considered for inclusion. After a rigorous screening process, 10 articles that met the inclusion criteria for this review were included (i.e., reported neuropsychiatric manifestations and cognitive decline in patients with LSLD and the effects of a delayed diagnosis). Neuropsychiatric manifestations in the patients consisted of suicidal ideation, homicidal tendencies, extreme anger, depressive symptoms, aggression, and anxiety. Cognitive symptoms included dysfunctions in working memory, verbal learning/memory, non-verbal learning/memory, alertness, visuoconstructive, and frontal executive functioning. A delayed LD diagnosis increased symptom severity in most patients. The findings of this review indicate that neuropsychiatric and cognitive symptoms tend to present for a chronic period, even after disease recovery. Although researchers have established a link between a delayed LD diagnosis and increased symptom severity, LSLD is often an overlooked diagnosis in patients with neuropsychiatric symptoms and cognitive decline. More research is needed to compare the time to diagnosis and symptom severity in patients with LSLD.

Surgical Treatment of Post-Amputation Foot Deformations in Diabetic Neuropathy

Relevance The number of amputations performed on patients with diabetic foot syndrome is increasing all over the world. Almost half of these operations are the so-called “minor amputations” carried out within the foot. The high recurrence rate of neuropathic ulcers, impaired biomechanics, and a decrease in the quality of life of patients after these surgeries encourage the study of this problem and the search for possible treatment options due to the capabilities of surgical treatment for post-amputation foot deformities.Aim of study To evaluate the nature of surgical interventions for post-amputation foot deformities in patients with diabetic neuropathy.Material and methods The literature search was carried out in the databases of medical publications PubMed, CyberLeninka, Google Scholar, Scopus, Medline, eLIBRARY among articles in English and Russian. The search was performed using the following terms: transmetatarsal resection, diabetic foot syndrome, transmetatarsal amputation, minor amputation.Results Surgical treatment methods for deformities after amputation of part of the forefoot are widely presented in the world literature and are more studied. The possibilities of correcting foot deformities that occurred after amputation of the entire anterior section (from transmetatarsal amputation to the level of the Chopart`s joint) are less covered, this direction and methods have been studied to a lesser extent.Conclusions Surgical methods for the correction of post-amputation foot deformities have firmly entered the wide international practice. Their effectiveness is confirmed by studies with a high level of evidence. Nevertheless, a wider, academic research of the problem of orthopedic status in patients with this pathology and the corresponding methods of surgical treatment is required.

La sébocystomatose: étude de cas clinique

Sebocystomatosis, a rare skin disease characterized by sebum-filled skin cysts, affected a 28-year-old female. Lesions started at 12 years, initially located on the sternum, then extending to the forearms and abdomen. A biopsy confirmed the diagnosis of sebocystomatosis, revealing epidermal cysts in the dermis with sebaceous glands. Sebocystomatosis is sparsely documented in medical literature. Our patient presents persistent skin lesions, diagnosed as sebocystomatosis by biopsy. Early recognition is crucial for management, emphasizing the importance of biopsy for the accurate diagnosis of this skin disease.

Leveraging meta-regression to test if medication effects on cue-induced craving are associated with clinical efficacy.

The alcohol cue exposure paradigm is a common method for evaluating new treatments for alcohol use disorder (AUD); however, it is unclear if medication-related reductions in cue-induced craving in the human laboratory can predict the clinical success of those medications in reducing alcohol consumption during clinical trials. To use a novel meta-analytic approach to test whether medication effect sizes on cue-induced alcohol craving are associated with clinical efficacy in clinical trials. We searched the literature for medications tested for AUD treatment using both the alcohol cue-reactivity paradigm and randomized clinical trials (RCTs). For alcohol cue-reactivity studies, we computed medication effect sizes for cue-induced alcohol craving (k = 36 studies, 15 medications). For RCTs, we calculated medication effect sizes for heavy drinking and abstinence (k = 139 studies, 19 medications). Using medication as the unit of analysis, we applied the Williamson-York bivariate weighted least squares estimation to account for errors in both independent and dependent variables. We also conducted leave-one-out cross validation simulations to examine the predictive utility of cue-craving medication effect sizes on RCT heavy drinking and abstinence endpoints. There was no significant relationship between medication effects on cue-induced alcohol craving in the human laboratory and medication effects on heavy drinking ( = 0.253, SE = 0.189,p = 0.090) and abstinence ( = 0.829, SE = 0.747,p = 0.133) in RCTs. The preliminary results of the current study challenge the assumption that alcohol cue-reactivity alone can be used as an early efficacy indicator for AUD pharmacotherapy development. These findings suggest that a wider range of early efficacy indicators and experimental paradigms be considered for Phase II testing of novel compounds.

Li-Fraumeni syndrome in a young patient with colorectal carcinoma

Li-Fraumeni syndrome is characterized as a mutation of the TP53 gene, belonging to a strain of tumor suppressor genes. Patients with mutations in this gene accumulate, throughout their lives, a greatly increased probability for the development of various types of malignant tumors. This report has as its main objective to report a clinical case of a young patient affected by a colon neoplasm, whose laboratory and anatomopathological tests indicated microsatellite instabilities. A survey was conducted in medical records of the care, exams and surgeries to which the patient was submitted for important data collection. The information obtained was compared as present in. Scientific and medical literature, and it was possible to conclude, although there is no specific genetic test that detects the TP53 gene mutation in this patient, that it presents significant changes in DNA segments, compatible with Li-Fraumeni syndrome.

The Hamas massacre of Oct 7, 2023, and its aftermath, medical crimes, and the Lancet commission report on medicine, Nazism, and the Holocaust

BackgroundThe report of the Lancet Commission on medicine, Nazism, and the Holocaust, released in November 2023, calls for this history to be required for all health professions education, to foster morally courageous health professionals who speak up when necessary.Main bodyThe report was released a month after Hamas’ October 7 invasion of Israel, with the accompanying massacre of over 1200 people, taking of civilian hostages, and gender-based violence. These acts constitute crimes against humanity including genocide. Post-October 7, war in Gaza resulted, with a legitimate objective of Israel defending itself within international law. The authors discuss an accompanying Statement to the report condemning Hamas crimes and denouncing the perpetrators’ use of their own civilians as human shields, including in healthcare facilities, and with the Hamas attack unleashing immense and ongoing suffering in Israel and beyond. With some exceptions, the medical literature shows a marked absence of condemnation of Hamas atrocities and includes unsubstantiated criticisms of Israel’s military. A significant surge in global antisemitism including on university campuses since October 7, 2023, has occurred; and health professionals, according to the Commission, have a special responsibility to fight antisemitism and discrimination of all kinds. In this context, the authors discuss the controversy and criticism regarding diversity, equity, and inclusion education programs (“DEI”) including such programs failing to protect Jews on campuses, especially as the U.S. President Biden’s “The U.S. National Strategy to Counter Antisemitism,” released in May 2023, calls for the inclusion of issues of antisemitism and religious discrimination within all DEI education programs. The authors support an evidence-based approach to the Hamas massacre, its aftermath and its relevance to health professionals both within medicine and their global citizenship, including refuting the international community accusations and anti-Israel libel.ConclusionsThe report of the Lancet Commission on medicine, Nazism, and the Holocaust has striking relevance to the Hamas massacre of October 7, 2023 and its aftermath. This is further conveyed in an accompanying Statement, that describes the report’s implications for contemporary medicine, including: 1) provision of skills required to detect and prevent crimes against humanity and genocide; (2) care for victims of atrocities; (3) upholding the healing ethos central to the practice of medicine; and (4) fostering history-informed morally courageous health professionals who speak up when necessary.

Incidence of Type 2 Diabetes Mellitus in Transgender Individuals Undergoing Gender Affirming Hormonal Therapy: A Systematic Review.

Gender-affirming hormonal therapy (GAHT), which includes estrogen, testosterone, androgen agonists, is commonly used in transgender individuals to change their secondary sexual characteristics to align with their gender identity. However, this treatment could result in metabolic side effects that could increase the chances of acquiring type 2 diabetes mellitus. Thus, this study aims to compare differences in body mass index (BMI), insulin resistance, and the incidence of type 2 diabetes mellitus between cisgender and transgender individuals undergoing GAHT. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards, we conducted a systematic review searching through PubMed, Google Scholar, Medline (Medical Literature Analysis and Retrieval System Online), and ResearchGate for articles published between 2014 and 2024. The final search was conducted in February 2024. Out of the 3,934 articles reviewed, 11 were selected, focusing on insulin sensitivity/resistance, diabetes incidence, and BMI changes with GAHT. Although our result findings did not show clear evidence of increased diabetes incidence among GAHT patients, it was observed that GAHT does increase BMI and insulin resistance in transgender individuals. Notably, compared to transgender men, transgender women on GAHT were found to be more prone to insulin resistance. We recommend regularly monitoring insulin sensitivity parameters and HbA1c during GAHT to monitor metabolic side effects. Further research and more clinical trials are needed to confirm the GAHT's impact on insulin resistance and to evaluate its role in the onset of type 2 diabetes mellitus.

Storylines of Trauma in Health Professions Education: A Critical Metanarrative Review

Phenomenon Learners in medical education are often exposed to content and situations that might be experienced as traumatic, which in turn has both professional and personal implications. The purpose of this study was to synthesize the literature on how trauma has been conceptualized and approached within medical education, and the implications thereof. Approach A metanarrative approach was adopted following the RAMESES guidelines. Searches of 7 databases conducted in January 2022 with no date limitations yielded 7,280 articles, of which 50 were identified for inclusion through purposive and theoretical sampling. An additional 5 articles were added from manual searches of reference lists. Iterative readings, interpretive and reflexive analysis, and research team discussions were performed to identify and refine metanarratives. Findings Five metanarratives were identified, including the concept of trauma, the trauma event, the person with trauma, the impact of trauma, and addressing trauma, with each metanarrative encompassing multiple dimensions. A biomedical concept of trauma predominated, with lack of conceptual clarity. Theory was not integrated or developed in the majority of articles reviewed, and context was often ambiguous. Trauma was described in myriad ways among studies. Why certain events were experienced as trauma and the context in which they took place were not well characterized. The impact of trauma was largely concentrated on harmful effects, and manifestations beyond symptoms of post-traumatic stress were often not considered. Furthermore, the dominant focus was on the individual, yet often in a circumscribed way that did not seek to understand the individual experience. In addressing trauma, recommendations were often generic, and earlier research emphasized individually-focused interventions while more recent studies have considered systemic issues. Insights Multiple dimensions of trauma have been discussed in the medical education literature and from many conceptual standpoints, with biomedical, epidemiologic, and individualized perspectives predominating. Greater precision and clarity in defining and understanding trauma is needed to advance research and theory around trauma in medical education and the associated implications for practice. Exploring trauma from intersectional and collective experiences and impacts of trauma and adapting responses to individual needs offers ways to deepen our understanding of how to better support learners impacted by trauma.