Specialties preference by gender among medical students at Sefako Makgatho Health Sciences University, South Africa.

BACKGROUND:  To determine the speciality preferences and the gender differences in the choice of speciality among medical students at Sefako Makgatho Health Sciences University, South Africa. METHODS:  This cross-sectional study was conducted among fourth- to sixth-year medical students. A structured self-administered questionnaire was used to collect the data. Data analysis was performed using STATA version 16 (StataCorp, College Station, TX, United States). RESULTS:  A total of 174 students participated (response rate of 74%). Their median age was 23 years with interquartile range of 2 years. More than half (57%) were females. About 83% had no previous qualifications. Most (89%) have shown interest in pursuing specialist training. Surgery, obstetrics and gynaecology and internal medicine were the most selected specialities, while family medicine, ophthalmology, forensic medicine, public health medicine, ear, nose and throat, and accident and emergency medicine were the least preferred. Males were more likely interested in surgery and internal medicine, while females preferred obstetrics and gynaecology. CONCLUSION:  The majority of the medical students intends to pursue their postgraduate medical training. Even though the results were not statistically significant, there are gender differences in speciality preferences. There is a need to develop and implement career guidance and recruitment plans to deal with specialities with poor recruitment and gender imbalance.Contribution: To deal with specialties with poor and gender imbalance, career guidance and recruitment plans must be developed and implemented.

Variation in Oral Board Examination Accommodations Among Specialties.

Importance: Board certification can have broad implications for candidates' career trajectories, and prior research has found sociodemographic disparities in pass rates. Barriers in the format and administration of the oral board examinations may disproportionately affect certain candidates. Objective: To characterize oral certifying examination policies and practices of the 16 Accreditation Council for Graduate Medical Education (ACGME)-accredited specialties that require oral examinations. Design, Setting, and Participants: This cross-sectional study was conducted from March 1 to April 15, 2023, using data on oral examination practices and policies (examination format, dates, and setting; lactation accommodations; and accommodations for military deployment, family emergency, or medical leave) as well as the gender composition of the specialties' boards of directors obtained from websites, telephone calls and email correspondence with certifying specialists. The percentages of female residents and residents of racial and ethnic backgrounds who are historically underrepresented in medicine (URM) in each specialty as of December 31, 2021, were obtained from the Graduate Medical Education 2021 to 2022 report. Main Outcome and Measures: For each specialty, accommodation scores were measured by a modified objective scoring system (score range: 1-13, with higher scores indicating more accommodations). Poisson regression was used to assess the association between accommodation score and the diversity of residents in that specialty, as measured by the percentages of female and URM residents. Linear regression was used to assess whether gender diversity of a specialty's board of directors was associated with accommodation scores. Results: Included in the analysis were 16 specialties with a total of 46 027 residents (26 533 males [57.6%]) and 233 members of boards of directors (152 males [65.2%]). The mean (SD) total accommodation score was 8.28 (3.79), and the median (IQR) score was 9.25 (5.00-12.00). No association was found between test accommodation score and the percentage of female or URM residents. However, for each 1-point increase in the test accommodation score, the relative risk that a resident was female was 1.05 (95% CI, 0.96-1.16), and the relative risk that an individual was a URM resident was 1.04 (95% CI, 1.00-1.07). An association was found between the percentage of female board members and the accommodation score: for each 10% increase in the percentage of board members who were female, the accommodation score increased by 1.20 points (95% CI, 0.23-2.16 points; P = .03). Conclusions and Relevance: This cross-sectional study found considerable variability in oral board examination accommodations among ACGME-accredited specialties, highlighting opportunities for improvement and standardization. Promoting diversity in leadership bodies may lead to greater accommodations for examinees in extenuating circumstances.

LightPRA: A Lightweight Temporal Convolutional Network for Automatic Physical Rehabilitation Exercise Assessment.

Research evidence shows that physical rehabilitation exercises prescribed by medical experts can assist in restoring physical function, improving life quality, and promoting independence for physically disabled individuals. In response to the absence of immediate expert feedback on performed actions, developing a Human Action Evaluation (HAE) system emerges as a valuable automated solution, addressing the need for accurate assessment of exercises and guidance during physical rehabilitation. Previous HAE systems developed for the rehabilitation exercises have focused on developing models that utilize skeleton data as input to compute a quality score for each action performed by the patient. However, existing studies have focused on improving scoring performance while often overlooking computational efficiency. In this research, we propose LightPRA (Light Physical Rehabilitation Assessment) system, an innovative architectural solution based on a Temporal Convolutional Network (TCN), which harnesses the capabilities of dilated causal Convolutional Neural Networks (CNNs). This approach efficiently captures complex temporal features and characteristics of the skeleton data with lower computational complexity, making it suitable for real-time feedback provided on resource-constrained devices such as Internet of Things (IoT) devices and Edge computing frameworks. Through empirical analysis performed on the University of Idaho-Physical Rehabilitation Movement Data (UI-PRMD) and KInematic assessment of MOvement for remote monitoring of physical REhabilitation (KIMORE) datasets, our proposed LightPRA model demonstrates superior performance over several state-of-the-art approaches such as Spatial-Temporal Graph Convolutional Network (STGCN) and Long Short-Term Memory (LSTM)-based models in scoring human activity performance, while exhibiting lower computational cost and complexity.

[Understanding hypersensitivity reactions to monoclonal antibodies]. / Comprendre les réactions d'hypersensibilité aux anticorps monoclonaux.

Biologic drugs are complex molecules synthesized by a living organism. Their use is increasingly prevalent across all medical specialties, exposing a growing number of patients to potential adverse reactions. In this review, we discuss the new classification of hypersensitivity reactions, along with the specific characteristics of monoclonal antibodies. We also address the available diagnostic tools and discuss the management of those reactions, including for patients requiring the continuation of these biologic drugs.

Les médicaments biologiques sont des molécules complexes synthétisées par un organisme vivant. Ils sont de plus en plus utilisés dans toutes les spécialités médicales, exposant ainsi les patients à des réactions indésirables. Dans cet article, nous abordons la nouvelle classification des réactions d'hypersensibilité ainsi que les caractéristiques spécifiques des anticorps monoclonaux. Nous évoquons également les outils diagnostiques disponibles et discutons de la prise en charge, y compris pour les patients nécessitant la poursuite de l'administration des médicaments biologiques.

Factors affecting the choice of medical specialties in Turkiye: an analysis based on cross-sectional survey of medical graduates.

BACKGROUND: Modern healthcare systems require the right mix of medical specialties for effective provision of high-quality services. Despite increased availability of general physicians and specialists, Türkiye lags behind high-income countries in terms of availability of specialists. The purpose of the study is to identify several specific factors that affect the choice of medical specialization. METHODS: All 350 medical school graduates in a specialty examination preparation bootcamp were requested to participate in the survey and 333 completed the self-administered questionnaire. The survey asked questions about factors affecting choice of medical specialty by medical graduates. RESULTS: The empirical results indicate that surgical specialties, compared to other broad medical specializations, are selected because of its higher income-earning potential and social prestige. The likelihood of selecting surgical specialties is negatively affected by rigorousness of the training program, high work-load, risk of malpractice lawsuits and risk of workplace violence. Male participants were 2.8 times more likely to select surgery specialty compared to basic medical science. Basic medical science areas were selected at a higher rate by female graduates and graduates with high level of academic performance in medical schools. CONCLUSIONS: It is critically important to improve trust and inter-personal communications between the patients and physicians in all specialties to lower the likelihood of malpractice lawsuits and workplace violence. Policy-makers may adopt policies to affect income earning potential and social prestige of targeted specializations to improve their supply.

Medicine-Both a Science (Care) and an Art (CARE).

This Viewpoint discusses the concept of CARE (compassion, assistance, respect, and empathy) as a way physicians can practice the art of medicine in the current era of care that increasingly incorporates predictive analytics and artificial intelligence.

Professional Experiences and Career Trajectories of Mid- to Senior-Career Women Clinician-Scientists: A Qualitative Study.

Importance: Despite increasing evidence and recognition of persistent gender disparities in academic medicine, qualitative data detailing the association of gender-based experiences with career progression remain sparse, particularly at the mid- to senior-career stage. Objective: To investigate the role gender has played in everyday professional experiences of mid- to senior-career women clinician-scientists and their perceptions of gender-related barriers experienced across their careers. Design, Setting, and Participants: In this qualitative study, a total of 60 of 159 invited clinician-scientists who received National Institutes of Health K08 or K23 awards between 2006 and 2009 and responded to a survey in 2021 agreed to participate. Invitees were selected using random, purposive sampling to support sample heterogeneity. Semistructured in-depth interviews were conducted January to May 2022. For this study, interviews from 31 women were analyzed using the framework approach to thematic analysis. Data analyses were performed between August and October 2023. Main Outcomes and Measures: Descriptive themes of participant experiences of gender and gender-based barriers in academic medicine. Results: A total of 31 women clinician-scientists (8 identifying as Asian [25.8%], 14 identifying as White [45.2%], and 9 identifying as members of a minority group underrepresented in medicine [29.0%]; 14 aged 40-49 years [45.2%] and 14 aged 50-59 years [45.2%]) were included. Among them, 17 participants (54.8%) had children who required adult supervision or care, 7 participants (22.6%) had children who did not require supervision or care, and 6 participants (19.4%) did not have children. There were 4 dominant themes identified within participant experiences in academic medicine: the mental burden of gendered expectations at work and home, inequitable treatment of women in bureaucratic processes, subtle and less subtle professional exclusion of women, and value of communities built on shared identities, experiences, and solidarity. Conclusions and Relevance: This study found that women perceived the institution of academic medicine as a male-centric system misaligned with the needs of women, with associated feelings of exclusion, disillusionment, and loss of trust in their institutions. Findings suggest that the confluence of domestic obligations and unaccommodating institutional environments may make it difficult for women clinician-scientists to achieve established timelines of career progression and productivity; these findings may have long-term implications for the well-being and retention of women in academic medicine.

[Motivational factors for early option choice by laboratory medicine residents in France]. / Facteurs de motivation pour le choix d'option précoce par les internes de biologie médicale en France.

In France, both students from medicine and pharmacy background can have access to the residency in laboratory medicine (LM). The current curriculum of LM residency includes an early choice of option after the first two years of residency, which subsequently guides the rest of the training. This study aimed to analyze these choice and motivational factors, since its implementation in 2017. A national survey was conducted among LM residents and former residents who underwent the early option choice process. A questionnaire was developed and sent to residents via Google Forms. Several groups of items corresponding to potential motivational factors were included and rated on a 5-point Likert scale. A psychometric analysis allowed to identify the main motivational factors. A total of 178 responses from 24 residency regions were recorded. The median age was 28 years, with a slight female predominance (52%), and three-quarters of the participants had a pharmacy training background. The "hematology and immunology" option was the most chosen (35%). The psychometric analysis enabled to identify 7 motivational factors, and the most important is the training during the residency, which weights approximately 21 % in the choice. Several associations have been observed between the motivational factors and the background training, origin, the chosen option and the planned career. Several factors influence the choice of early option among LM residents, and some of these factors are associated with the background training, origin, chosen option and planned career.

[On the 120th anniversary of A. A. Otelin - scientist, morphologist, pedagogue and organizer].

The article presents scientific biography of A. A. Otelin - outstanding morphologist, Doctor of Medical Sciences, Professor, representative of scientific school of Academician V. P. Vorobyov. The contribution of A. A. Otelin into becoming of morphological chairs in medical institutes of Kharkov, Lvov, Vinnitsa, Kishinev, Kursk and Kemerovo and in formation of scientific morphological schools in the regions of the RSFSR and the Republics of the USSR is demonstrated. The particular attention is paid to results of scientific studies of A. A. Otelin in the 1970s carried out jointly with scientists of the Institute of Brain of the USSR Academy of Medical Sciences and the I. P. Pavlov Institute of Physiology of the USSR Academy of Sciences concerning investigation of morphology of sensitive receptors - Vater-Pacini corpuscules.

[The review of the monograph "Ambroise Paré. The first surgeon of the Kingdom" by E. E. Berger].

The review considers the approach placing famous French surgeon A. Paré into more general European context of European Renaissance of XVI century and into local context of intellectual life of Paris of this period. The refutation of widespread in history of medicine opinion about strict separation of university medicine from artisan surgery in Medieval Europe is discussed.

[Essentials for high-quality development of fangjiomics].

The development of modern omics technology has facilitated in-depth research on many disciplines in the field of medicine. For instance, the introduction of omics-related technology has facilitated research on the mechanism of formula's action and led to the innovative development of sophisticated pharmacological analysis methods. However, in general, the previous ideas are only limited to the application level, failing to integrate with the discipline connotation of formulaology. Furthermore, they are unable to fulfill their potential role in the future evolution of formulaology and steer comprehensive research on the clinical efficacy and safety of formulas. We should not forget our origins, which are compatible with other countries, and embrace the future. Therefore, this paper proposes the three essentials of "holism, macro, and practice" to investigate the future direction of high-quality development in fangjiomics.

Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis. Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided. Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses. Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included. Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.