Context: The acquisition of clinical skills is an essential part of the osteopathic medical school curriculum. Preclinical medical students, especially at osteopathic medical schools, have limited exposure to abnormal physical examination (PE) findings that are not typically seen in a student's peers or in a standardized patient (SP). The early exposure of first-year medical students (MS1s) to normal and abnormal findings in the simulation settings better equips them to identify abnormalities when they encounter them in a clinical setting.
Objectives: The aim of this project was to develop and implement the introductory course on learning abnormal PE signs and pathophysiology of abnormal clinical findings to address the educational needs of MS1s.
Methods: The didactic part of the course consisted of PowerPoint presentations and lecture on the topics related to the simulation. The practical skill session was 60 min, during which time students first practiced PE signs and then were assessed on their ability to accurately identify abnormal PE signs on a high-fidelity (HF) mannequin. Faculty instructors guided students through clinical cases and challenged them with probing questions in clinically relevant content. Before- and after-simulation evaluations were created to assess students' skills and confidence. Student satisfaction levels after the training course were also assessed.
Results: This study demonstrated significant improvements in five PE skills (p<0.0001) after the introductory course of abnormal PE clinical signs. The average score for five clinical skills increased from 63.1 to 88.74% (before to after simulation). The confidence of students in performing clinical skills and their understanding of the pathophysiology of abnormal clinical findings also increased significantly (p<0.0001) after simulation activity and educational instruction. The average confidence score increased from 3.3 to 4.5% (before to after simulation) on a 5-point Likert scale. Survey results demonstrated high satisfaction with the course among learners with mean satisfaction score 4.7 ± 0.4 on 5-point Likert scale. The introductory course was well received by MS1s and they left positive feedback.
Conclusions: This introductory course offered MS1s with novice PE skills the ability to learn a variety of abnormal PE signs, including heart murmurs and rhythms, lung sounds, measurement of blood pressure (BP), and palpation of the femoral pulse. This course also allowed abnormal PE findings to be taught in a time-efficient and faculty-resource-efficient manner.
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http://dx.doi.org/10.1515/jom-2022-0163 | DOI Listing |
Anal Chem
January 2025
Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, Fujian 350117, China.
Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma cells in the bone marrow. Despite therapeutic advancements, there remains a critical need for reliable, noninvasive methods to monitor multiple myeloma. Circulating plasma cells (CPCs) in peripheral blood are robust and independent prognostic markers, but their detection is challenging due to their low abundance.
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January 2025
INSERM, IMRBU955, Univ Paris Est Créteil, Créteil, France.
Purpose: Establishing an accurate prognosis remains challenging in older patients with cancer because of the population's heterogeneity and the current predictive models' reduced ability to capture the complex interactions between oncologic and geriatric predictors. We aim to develop and externally validate a new predictive score (the Geriatric Cancer Scoring System [GCSS]) to refine individualized prognosis for older patients with cancer during the first year after a geriatric assessment (GA).
Materials And Methods: Data were collected from two French prospective multicenter cohorts of patients with cancer 70 years and older, referred for GA: ELCAPA (training set January 2007-March 2016) and ONCODAGE (validation set August 2008-March 2010).
J Neural Transm (Vienna)
January 2025
Human Anatomy, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Roma 55, Pisa, 56100, PI, Italy.
Anorexia nervosa (AN) represents an eating disorder, which features the highest rate of mortality among all psychiatric disorders. The disease prevalence is increasing steadily, and an effective cure is missing. The neurobiology of the disease is largely unknown, and only a few studies were designed to disclose specific brain areas, where altered neural transmission may occur.
View Article and Find Full Text PDFBrain
January 2025
State Key Laboratory of Cardiology and Medical Innovation Center, Shanghai East Hospital, Clinical Center for Brain and Spinal Cord Research, School of Medicine, Tongji University, 200331, Shanghai, China.
Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease, with most sporadic cases lacking clear genetic causes. Abnormal pre-mRNA splicing is a fundamental mechanism in neurodegenerative diseases. For example, TAR DNA-binding protein 43 (TDP-43) loss-of-function (LOF) causes widespread RNA mis-splicing events in ALS.
View Article and Find Full Text PDFJ Imaging
December 2024
Technology Department, CERN, 1211 Geneva, Switzerland.
Detection and segmentation of brain abnormalities using Magnetic Resonance Imaging (MRI) is an important task that, nowadays, the role of AI algorithms as supporting tools is well established both at the research and clinical-production level. While the performance of the state-of-the-art models is increasing, reaching radiologists and other experts' accuracy levels in many cases, there is still a lot of research needed on the direction of in-depth and transparent evaluation of the correct results and failures, especially in relation to important aspects of the radiological practice: abnormality position, intensity level, and volume. In this work, we focus on the analysis of the segmentation results of a pre-trained U-net model trained and validated on brain MRI examinations containing four different pathologies: Tumors, Strokes, Multiple Sclerosis (MS), and White Matter Hyperintensities (WMH).
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