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1.
Article in English | MEDLINE | ID: mdl-38996226

ABSTRACT

INTRODUCTION: This study aimed to evaluate the influence of training background on the frequency and indications of elbow arthroplasty performed by early-career surgeons. METHODS: A review of the American Board of Orthopaedic Surgery Part II Oral Examination Case List database from 2010 to 2021 was completed. The number of cases performed by surgeons from each individual training background were calculated and compared with the total number of surgeons who completed each fellowship during the study period. RESULTS: Hand surgeons performed the most elbow arthroplasty cases (132, 44%), but a higher percentage of shoulder/elbow surgeons performed elbow arthroplasty in comparison (15% vs. 7%). The mean number of TEA cases performed by shoulder/elbow surgeons was significantly higher than in other subspecialties (P < 0.01). However, when comparing only surgeons who performed elbow arthroplasty during the board collection period, there was no significant difference between training backgrounds (P = 0.20). DISCUSSION: While hand surgeons performed the most elbow arthroplasty cases, a higher percentage of shoulder/elbow surgeons performed elbow arthroplasty during the study period. The high prevalence of distal humerus fracture as an indication for arthroplasty reflected a shift in indications and was not related to training background.


Subject(s)
Arthroplasty, Replacement, Elbow , Databases, Factual , Orthopedics , Humans , United States , Orthopedics/education , Orthopedic Surgeons/education , Specialty Boards , Elbow Joint/surgery
2.
J Orthop Trauma ; 38(8S): Si, 2024 Aug 01.
Article in English | MEDLINE | ID: mdl-39007627

Subject(s)
Orthopedics , Humans
3.
Musculoskelet Sci Pract ; 72: 102985, 2024 08.
Article in English | MEDLINE | ID: mdl-39002993
4.
PLoS One ; 19(7): e0306971, 2024.
Article in English | MEDLINE | ID: mdl-38990914

ABSTRACT

BACKGROUND: The learning environment in medical education is crucial for student development, encompassing social, psychological, and physical aspects that significantly affect learning. This study aimed to assess undergraduate medical students' perception of the orthopaedic ward's learning environment and examine the factors influencing their overall satisfaction during clinical rotation. METHODS: This cross sectional quantitative study was conducted in a private medical college in Pakistan. Data was collected through a pre-validated questionnaire, "The Healthcare Education Micro-Learning Environment Measure (HEMLEM)." Data analysis was done using SPSS version 23 software. RESULTS: A total of 205/300 students (response rate 68.33%) [103 (50.2%) males and 102(49.85) females] participated in this survey. Notably, 116 (56.6%) appreciated the ward's welcoming, friendly, and open atmosphere, and 114(55.6%) of the respondents appreciated the ward culture where they felt free to ask questions or comment. Additionally, 111(54.7%) appreciated the faculty's enthusiasm for teaching. A comparison between male and female students showed significantly higher satisfaction among males regarding staff attitudes and behaviours (p < .019). CONCLUSION: Undergraduate students held a predominantly positive view of the orthopaedic ward's learning environment, with differences observed based on gender and year of study. The study highlights the importance of both staff attitude and teaching quality in shaping the educational experience. It suggests that medical institutions should focus on enhancing teaching skills among clinicians to improve learning experiences and ultimately benefit patient care and the healthcare system.


Subject(s)
Orthopedics , Personal Satisfaction , Students, Medical , Humans , Female , Male , Students, Medical/psychology , Surveys and Questionnaires , Cross-Sectional Studies , Orthopedics/education , Learning , Education, Medical, Undergraduate/methods , Adult , Pakistan , Young Adult , Perception
6.
J Bone Joint Surg Am ; 106(11): 939-940, 2024 Jun 05.
Article in English | MEDLINE | ID: mdl-38984729

Subject(s)
Orthopedics , Humans
7.
JBJS Rev ; 12(5)2024 May.
Article in English | MEDLINE | ID: mdl-39021638

ABSTRACT

Purpose: Underrepresentation and misrepresentation of historically underrepresented populations in randomized controlled trials (RCTs) may have implications for the validity of research results and their application for diverse populations. To evaluate the representation of historically linguistically, racially, and ethnically underrepresented participants in orthopaedic randomized controlled trials (RCTs) and to assess the use of translated and culturally adapted patient reported outcome measures (PROMs). Methods: Separate and comprehensive literature searches of PubMed, Web of Science, and Embase databases were performed to identify RCTs utilizing PROMs between the years 2012 - 2022 among the top five highest 5-year impact factor orthopaedic journals according to the 2021 Journal Citation Reports database. The primary outcomes of interest included reporting of linguistic, racial and ethnic demographic characteristics of trial participants and the utilization of translated PROMs. The methodological quality of each clinical trial was assessed using the Jadad Criteria. Results: 230 RCTs met inclusion criteria. The language of participants was reported in 14% of trials and in 17% of trials when searching both the published text and clinical trial registration information. In addition, race and/or ethnicity was reported in 11% of trials, and the use of translated PROMs was reported in 7% of trials. Among the six multinational studies, none reported the language of the study population nor the use of translated PROMs. Notably, four studies (2%) reported utilizing culturally adapted PROMs. The average Jadad score was 3.07. Conclusion: Participant language, race, and ethnicity are infrequently reported in orthopaedic clinical trials, potentially limiting the application and interpretation of study results. Similarly, the linguistic and cultural adaptation of PROMs utilized are often not reported, which also limits interpretations of the validity and generalizability of orthopedic study results. Researchers and journals should promote standard reporting of demographic data and methods of PROM adaptation to ensure results are generalizable to diverse patient populations. Level of Evidence: III.


Subject(s)
Cultural Diversity , Orthopedics , Humans , Randomized Controlled Trials as Topic , Language , Patient Reported Outcome Measures
9.
Zhonghua Yi Shi Za Zhi ; 54(3): 140-144, 2024 May 28.
Article in Chinese | MEDLINE | ID: mdl-38987004

ABSTRACT

Humans processed gypsum for their everyday use at least 7000 years ago. They have been using fixed limb methods for fracture treatment for nearly 5000 years. Hippocrates recognized the importance of the splint and the "roller bandage" for fracture treatment, and made the bandage hard by adding wax, pitch, lard or resin to the multi-layer cloth bandage, but not gypsum. Arabian physician El Zahrawi (936 -1013) also described a clay glue mixture, and flour and egg white as fracture fixation materials. From 970, Persian physician Muwafak used gypsum as the exclusive material for fracture fixation. The rudimentary form of modern plaster bandages was developed in the mid-19th century and spread widely after that, using methods from the Russian Pyrogov by soaking canvas in a gypsum slurry and Dutchman Massson wrapped gypsum powder in cotton cloth strips.


Subject(s)
Calcium Sulfate , Orthopedics , Calcium Sulfate/history , History, Ancient , Humans , Orthopedics/history , History, Medieval , History, 19th Century , History, 20th Century , History, 18th Century , History, 17th Century
10.
JBJS Rev ; 12(7)2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38991098

ABSTRACT

¼ Artificial intelligence is an umbrella term for computational calculations that are designed to mimic human intelligence and problem-solving capabilities, although in the future, this may become an incomplete definition. Machine learning (ML) encompasses the development of algorithms or predictive models that generate outputs without explicit instructions, assisting in clinical predictions based on large data sets. Deep learning is a subset of ML that utilizes layers of networks that use various inter-relational connections to define and generalize data.¼ ML algorithms can enhance radiomics techniques for improved image evaluation and diagnosis. While ML shows promise with the advent of radiomics, there are still obstacles to overcome.¼ Several calculators leveraging ML algorithms have been developed to predict survival in primary sarcomas and metastatic bone disease utilizing patient-specific data. While these models often report exceptionally accurate performance, it is crucial to evaluate their robustness using standardized guidelines.¼ While increased computing power suggests continuous improvement of ML algorithms, these advancements must be balanced against challenges such as diversifying data, addressing ethical concerns, and enhancing model interpretability.


Subject(s)
Bone Neoplasms , Machine Learning , Humans , Bone Neoplasms/diagnostic imaging , Clinical Decision-Making , Orthopedics , Medical Oncology
11.
Reumatol Clin (Engl Ed) ; 20(6): 326-333, 2024.
Article in English | MEDLINE | ID: mdl-38991826

ABSTRACT

INTRODUCTION AND OBJECTIVES: The Colegio Mexicano de Reumatología (CMR) is a corporation whose brand has two elements-image and identity-that differentiate it from other corporations. We evaluated aspects of CMR's corporate image and identity. SUBJECTS AND METHODS: To assess corporate image, we designed a survey using proof-of-concept and discrete-choice-experiments approaches. It assessed which definition (orthopedist, rheumatologist, or rehabilitator) was most meaningful in four pain scenarios in healthy adults from the country's Western region. We used discourse analysis and five readability indices of the CMR website to assess corporate identity. RESULTS: In total, 700 respondents were included. For every rheumatologist chosen in the hand scenario, respondents chose 1.13 orthopedists and 0.70 rehabilitators. For every rheumatologist chosen in the knee scenario, respondents chose 2.36 orthopedists and 0.64 rehabilitators, whereas 0.85 orthopedists and 0.58 rehabilitators were chosen in the arthritis scenario. Only 38% of the respondents preferred the CMR's definition of a rheumatologist to describe a rheumatologist. The younger age group preferred orthopedists to rheumatologists (50% vs. 31%, p<0.001). In the arthritis scenario, the choice of rheumatologist increased from 27% in the elementary school group to 49% in the university group (p<0.001). Mother was the most influential in healthcare seeking. The discursive analysis revealed that the CMR is positioned as a "we" restricted to "colleagues;" the patient did not have agentive representation. The semiotic structure of the CMR's mission/vision was deemed imprecise and lacking in statements of value and purpose; the readability scores indicated that the text was challenging and dry. CONCLUSIONS: The CMR's corporate image does not differentiate it from other health providers. CMR's identity seems ambiguous with restricted directionality. It seems pertinent to redefine the CMR.


Subject(s)
Professional Corporations , Humans , Female , Adult , Male , Middle Aged , Mexico , Rheumatology , Orthopedics , Aged , Young Adult , Surveys and Questionnaires
12.
J Surg Orthop Adv ; 33(2): 68-71, 2024.
Article in English | MEDLINE | ID: mdl-38995059

ABSTRACT

Victor McKusick, an iconic figure in medicine and considered the founding father of medical genetics, lived an exemplary life bound to inspire others. As a geneticist, McKusick was heavily involved in the Human Genome Project and the development of the widely used Online Mendelian Inheritance in Man. As a researcher and prolific writer, he published more than 700 research articles, reviews, and books. McKusick educated and inspired thousands of students, doctors, and scientists while performing landmark studies in hereditary disorders and skeletal dysplasias. This brief history describes the life of Dr. Victor McKusick and his tremendous impact on orthopaedic surgery. (Journal of Surgical Orthopaedic Advances 33(2):068-071, 2024).


Subject(s)
Genetics, Medical , Orthopedics , History, 20th Century , Orthopedics/history , Genetics, Medical/history , Humans , History, 21st Century
13.
Sci Rep ; 14(1): 16105, 2024 Jul 12.
Article in English | MEDLINE | ID: mdl-38997335

ABSTRACT

AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases inherent within these models remains largely unexplored. This study tackles these concerns by thoroughly re-examining AI-driven segmentation for hip and knee bony anatomy. While advanced imaging modalities like CT and MRI offer comprehensive views, plain radiographs (X-rays) predominate the standard initial clinical assessment due to their widespread availability, low cost, and rapid acquisition. Hence, we focused on plain radiographs to ensure the utilization of our contribution in diverse healthcare settings, including those with limited access to advanced imaging technologies. This work provides insights into the underlying causes of biases in AI-based knee and hip image segmentation through an extensive evaluation, presenting targeted mitigation strategies to alleviate biases related to sex, race, and age, using an automatic segmentation that is fair, impartial, and safe in the context of AI. Our contribution can enhance inclusivity, ethical practices, equity, and an unbiased healthcare environment with advanced clinical outcomes, aiding decision-making and osteoarthritis research. Furthermore, we have made all the codes and datasets publicly and freely accessible to promote open scientific research.


Subject(s)
Artificial Intelligence , Humans , Male , Female , Middle Aged , Image Processing, Computer-Assisted/methods , Bias , Knee Joint/diagnostic imaging , Knee/diagnostic imaging , Adult , Algorithms , Hip Joint/diagnostic imaging , Magnetic Resonance Imaging/methods , Aged , Tomography, X-Ray Computed/methods , Orthopedics
15.
Bone Joint J ; 106-B(7): 640-641, 2024 Jul 01.
Article in English | MEDLINE | ID: mdl-38945530
17.
J Orthop Res ; 42(8): 1631-1640, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38897819

ABSTRACT

Proteomics is a growing field that offers insights into various aspects of disease processes and therapy responses. Within the field of orthopedics, there are a variety of diseases that have a poor prognosis due to a lack of targeted curative therapy or disease modifying therapy. Other diseases have been difficult to manage in part due to lack of clinical biomarkers that offer meaningful insight into disease progression or severity. As an emerging technology, proteomics has been increasingly applied in studying bone biology and an assortment of orthopedics related diseases, such as osteoarthritis, osteosarcoma and bone tumors, osteoporosis, traumatic bone injury, spinal cord injury, hip and knee arthroplasty, and fragile healing. These efforts range from mechanistic studies for elucidating novel insights in tissue activity and metabolism to identification of candidate biomarkers for diagnosis, prognosis, and targeted treatment. The knowledge gained from these proteomic and functional studies has provided unique perspectives in studying orthopedic diseases. In this review, we seek to report on the current state of the proteomic study in the field of orthopedics, overview the advances in clinically applicable discoveries, and discuss the opportunities that may guide us for future research.


Subject(s)
Proteomics , Humans , Translational Research, Biomedical , Orthopedics , Animals , Biomarkers/metabolism
20.
Tunis Med ; 102(6): 354-359, 2024 Jun 05.
Article in French | MEDLINE | ID: mdl-38864199

ABSTRACT

INTRODUCTION: The increase in hip arthroplasties predicts a rise in periprosthetic fractures in Morocco, posing challenges for orthopedic surgeons. Therapeutic strategies vary considerably, highlighting the absence of a universally accepted treatment protocol. AIM: To analyze the management of per-prosthetic hip fractures, while addressing the challenges associated with them. METHODS: This was a retrospective study, conducted in the trauma-orthopedics department between December 2015 and November 2022. Nineteen patients who presented to the hospital with fractures around a hip prosthesis were included. RESULT: Nineteen periprosthetic fractures were observed. The majority of patients (68%) were women, with an average age of 68. The Vancouver classification showed that 52.6% of the fractures were type B1, and 21.1% type C, while the other fracture types were distributed differently. These fractures were mainly associated with diagnoses such as femoral neck fracture (63.2%) and coxarthrosis (31.6%). We observed variations in treatment recommendations and results between the different series analyzed. We noted discrepancies with certain series concerning fracture types and therapeutic choices. However, in our series, we achieved satisfactory results, with successful consolidation and the absence of complications in all patients. CONCLUSION: These results underline the importance of an individualized approach to fracture management, taking into account the specificities of each case.


Subject(s)
Arthroplasty, Replacement, Hip , Hip Fractures , Hospitals, University , Periprosthetic Fractures , Humans , Female , Retrospective Studies , Periprosthetic Fractures/epidemiology , Periprosthetic Fractures/therapy , Periprosthetic Fractures/surgery , Periprosthetic Fractures/etiology , Periprosthetic Fractures/diagnosis , Male , Morocco/epidemiology , Aged , Middle Aged , Arthroplasty, Replacement, Hip/statistics & numerical data , Arthroplasty, Replacement, Hip/methods , Hospitals, University/statistics & numerical data , Hip Fractures/epidemiology , Hip Fractures/surgery , Hip Fractures/therapy , Aged, 80 and over , Traumatology/standards , Traumatology/methods , Orthopedics/statistics & numerical data , Hip Prosthesis/statistics & numerical data , Adult
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