Orthopedic Diagnosis Research Articles

Outcomes of the My Therapy self-management program in people admitted for rehabilitation: A stepped wedge cluster randomized clinical trial

BackgroundSelf-management programs can increase the time spent on prescribed therapeutic exercises and activities in rehabilitation inpatients, which has been associated with better functional outcomes and shorter hospital stays. ObjectivesTo determine whether implementation of a self-management program (‘My Therapy’) improves functional independence relative to routine care in people admitted for physical rehabilitation. MethodsThis stepped wedge, cluster randomized trial was conducted over 54 weeks (9 periods of 6-week duration, April 2021 - April 2022) across 9 clusters (general rehabilitation wards) within 4 hospitals (Victoria, Australia). We included all adults (≥18 years) admitted for rehabilitation to participating wards. The intervention included routine care plus ‘My Therapy’, comprising a sub-set of exercises and activities from supervised sessions which could be performed safely, without supervision or assistance. The primary outcomes were the proportion of participants achieving a minimal clinically important difference (MCID) in the Functional Independence Measure, (FIM™) and change in total FIM™ score from admission to discharge. Results2550 participants (62 % women) were recruited (control: n = 1458, intervention: n = 1092), with mean (SD) age 77 (13) years and 37 % orthopedic diagnosis. Under intervention conditions, participants reported a mean (SD) of 29 (21) minutes/day of self-directed therapy, compared to 4 (SD 14) minutes/day, under control conditions. There was no evidence of a difference between control and intervention conditions in the odds of achieving an MCID in FIM™ (adjusted odds ratio 0.93, 95 % CI 0.65 to 1.31), or in the change in FIM™ score (adjusted mean difference: -0.27 units, 95 % CI -2.67 to 2.13). ConclusionsMy Therapy was delivered safely to a large, diverse sample of participants admitted for rehabilitation, with an increase in daily rehabilitation dosage. However, given the lack of difference in functional improvement with participation in My Therapy, self-management programs may need to be supplemented with other strategies to improve function in people admitted for rehabilitation. Trial registrationAustralian New Zealand Clinical Trials Registry (ACTRN12621000313831), https://www.anzctr.org.au/

Do preoperative glucose levels predict risk of complications in orthopaedic surgery?

Post-operative hyperglycemia is a known risk factor for post-surgical complications. The predictive value of pre-operative blood glucose levels, however, is less understood. This study aimed to determine if pre-operative screening blood glucose levels affect the rate of post-operative infection or wound complications. We also investigated if case urgency or anatomic location alters this relationship. A single-institution retrospective chart review was performed to evaluate patients treated between 2018 and 2021. Subjects ≥ 18years with closed, non-infected orthopaedic diagnoses requiring surgery were included. Case urgency, demographics, comorbidities, blood glucose level within twelve h prior to surgery, and hemoglobin A1c level within 3months of surgery, were collected. Infections and wound complications were recorded as outcomes. A total of 775 subjects with a mean age of 61 (range 18-96) were identified, including 543 elective and 232 trauma patients, with a mean pre-operative fasting glucose value of 127.7mg/dL (range, 49-388mg/dL) and average HbA1c of 6.9%. The odds of infectious complications were increased by a factor of 1.01 for every 1-point increase in blood glucose (95% CI 1.01-1.02; p < 0.01). Pre-operative blood glucose levels greater than 137mg/dL were associated with an increase in wound complications, but not deep infections. Infection rates stratified by anatomic site and case urgency were not impacted by pre-operative glucose levels. The increased risk of poor wound healing in patients with pre-operative hyperglycemia demonstrates that day of surgery point-of-care blood glucose screening can be a useful risk stratification tool.

Does Insurance Provide Adequate Coverage for Physical Therapy Visits for Common Orthopedic Diagnoses? A Survey Study.

This study aimed to analyze the association between physical therapists' recommended number of visits for a full recovery from common orthopedic injuries/surgeries and the extent of insurance coverage for these visits. A prospective observational study was conducted with board-certified physical therapists. A qualitative questionnaire was used to gather physical therapists' demographics and the recommended number of physical therapy visits to achieve a full recovery after 11 common orthopedic diagnoses. Physical therapists also were asked to report whether they believe that insurance provides an adequate number of visits overall. In addition to the qualitative survey, insurance coverage details of major Alabama companies were obtained for comparison. Descriptive statistics of the participating therapists were analyzed for sex, age, degree/training, and years of experience. Kruskal-Wallis statistics were used to analyze variance between the aforementioned groupings when compared with the reported average number of sessions. The survey (N = 251) collected data on the average number of physical therapy sessions that are necessary for a complete recovery as recommended by physical therapists for 11 common orthopedic diagnoses. From this survey, the average number of necessary visits ranged from 11.3 visits (ankle sprains) to 37.3 visits (anterior cruciate ligament reconstruction), with the overall average number of visits being 23.8. Only 24% of physical therapists believed that insurance companies provided enough coverage. Insurance coverage varied but often required additional procedures to allocate the adequate number of visits for the studied orthopedic pathologies. The majority of practicing physical therapists in Alabama perceive insufficient insurance coverage for physical therapy visits for most orthopedic diagnoses. This study has implications for healthcare decision making and patient-centered rehabilitation goals. Physicians and physical therapists can use this information to optimize treatment decisions and rehabilitation goals. Patients will benefit from improved physical and economic well-being. This study has the potential to drive further research and influence national insurance policies to better serve patients' needs.

Delayed postoperative neurological deficits from scoliosis correction: a case series and systematic review on clinical characteristics, treatment, prognosis, and recovery.

This study was designed to investigate the clinical features, treatment modalities, and risk factors influencing neurological recovery in patients who underwent scoliosis correction with delayed postoperative neurological deficit (DPND). Three patients with DPND were identified from 2 central databases for descriptive analysis. Furthermore, all DPND cases were retrieved from the PubMed and Embase databases. Neurological function recovery was categorized into complete and incomplete recovery groups based on the American Spinal Injury Association (ASIA) impairment scale. Two patients were classified as type 3, and one was classified as type 2 based on the MRI spinal cord classification. Intraoperative neurophysiological monitoring (IONM) was consistently negative throughout the corrective procedure, and intraoperative wake-up tests were normal. The average time to DPND development was 11.8h (range, 4-18h), and all three patients achieved complete recovery of neurological function after undergoing revision surgery. A total of 14 articles involving 31 patients were included in the literature review. The mean time to onset of DPND was found to be 25.2h, and 85.3% (29/34) of patients experienced DPND within the first 48h postoperatively, with the most common initial symptoms being decreased muscle strength and sensation (26 patients, 83.9%). Regarding neurological function recovery, 14 patients were able to reach ASIA grade E, while 14 patients were not able to reach ASIA grade E. Univariate analysis revealed that preoperative diagnosis (p = 0.004), operative duration (p = 0.017), intraoperative osteotomy method (p = 0.033), level of neurological deficit (p = 0.037) and deficit source (p = 0.0358) were significantly associated with neurological outcomes. Furthermore, multivariate regression analysis indicated a strong correlation between preoperative diagnosis (p = 0.003, OR, 68.633; 95% CI 4.299-1095.657) and neurological prognosis. Our findings indicate that spinal cord ischemic injury was a significant factor for patients experiencing DPND and distraction after corrective surgery may be a predisposing factor for spinal cord ischemia. Additionally, it is important to consider the possibility of DPND when limb numbness and decreased muscle strength occur within 48h after corrective scoliosis surgery. Moreover, emergency surgical intervention is highly recommended for DPND caused by mechanical compression factors with a promising prognosis for neurological function, emphasizing the importance of taking into account preoperative orthopedic diagnoses when evaluating the potential for neurological recovery.

Numerical study on the effect of temperature rise of humeral bone nails in magnetic resonance imaging based on the finite-element method.

Humeral fracture is a common long bone fracture in orthopedic clinical diagnosis and treatment. To investigate the local temperature increase owing to changes in the specific absorption ratio (SAR) of the human body caused by humeral bone nails during magnetic resonance imaging (MRI). A refined geometric model of the upper body was constructed via data segmentation and post-processing using the digital human image dataset. Finally, the geometric model was imported into COMSOL, a 3-T magnetic resonance coil was built, and the operating frequency (128 MHz) was set to analyze the SAR of the bone-nail pair and temperature changes. The analysis of the changes after bone-nail implantation under different tissue conditions revealed that the SAR and temperature after implantation and fixation were three times higher than those before, and the areas with abrupt changes in SAR and temperature were primarily concentrated in the bone-nail area. In MRI, metal implants can cause local elevation of the SAR near the implant in the human body, resulting in a temperature increase around the implant. Consequently, long-term scanning can damage the human body.

Association of Medicare Home Health Ratings With Older Adult Fall Injuries: An Instrumental Variables Analysis

ObjectivesTo understand the role of high-quality home health care for fall prevention. DesignA 100% sample of national Medicare claims and home health survey data (2015-2017) were used to assess fall injuries and receipt of a fall risk assessment among recently hospitalized Medicare fee-for-service home health users aged ≥66 years. Subanalyses examined patients by prior fall history status and hospital admission diagnosis type (eg, neurologic, respiratory, cardiovascular, infection, and orthopedic diagnoses). An instrumental variables design addressed potential endogeneity in home health care use by patient fall risk. Setting and ParticipantsHome health agencies and Medicare fee-for-service beneficiaries. MethodsMultivariate regression and instrumental variables. ResultsAmong 962,610 patients with hospital discharges to home health, being treated by home health agencies with the highest star ratings in a person's zip code was associated with a 1.8–percentage point (ppt) (95% CI: 0.1, 3.5; P = .03) higher likelihood of receipt of fall risk assessment. There was no overall change in 30-day (−0.6 ppt, 95% CI: −1.3, 0.1; P = .09), 15-day (−0.3 ppt, 95% CI: −0.0.8, 0.2; P = .35), or 7-day fall injury risk (−0.2 ppt, 95% CI: −0.5, 0.1; P = .22), but a 1.9-ppt (95% CI: −3.9, −0.02; P = .048) lower 30-day fall injury risk for individuals with a history of falls. Effects were directionally similar by diagnosis type. Conclusions and ImplicationsFall injury risk is reduced at higher-rated home health agencies. Star ratings may be adequate indicators of quality for key outcomes not explicitly measured in the ratings.

Can Patients Rely on ChatGPT to Answer Hand Pathology-Related Medical Questions?

In recent years, ChatGPT has become a popular source of information online. Physicians need to be aware of the resources their patients are using to self-inform of their conditions. This study investigates physician-graded accuracy and completeness of ChatGPT regarding various questions patients are likely to ask the artificial intelligence (AI) system concerning common upper limb orthopedic conditions. ChatGPT 3.5 was interrogated concerning 5 common orthopedic hand conditions: carpal tunnel syndrome, Dupuytren contracture, De Quervain tenosynovitis, trigger finger, and carpal metacarpal arthritis. Questions evaluated conditions' symptoms, pathology, management, surgical indications, recovery time, insurance coverage, and workers' compensation possibility. Each topic had 12 to 15 questions and was established as its own ChatGPT conversation. All questions regarding the same diagnosis were presented to the AI, and its answers were recorded. Each question was then graded for both accuracy (Likert scale of 1-6) and completeness (Likert scale of 1-3) by 10 fellowship trained hand surgeons. Descriptive statistics were performed. Overall, the mean accuracy score for ChatGPT's answers to common orthopedic hand diagnoses was 4.83 out of 6 ± 0.95. The mean completeness of answers was 2 out of 3 ± 0.59. Easily accessible online AI such as ChatGPT is becoming more advanced and thus more reliable in its ability to answer common medical questions. Physicians can anticipate such online resources being mostly correct, however incomplete. Patients should beware of relying on such resources in isolation.

Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significantly impair patients' quality of life but also complicate and raise the expense of therapy. It has been discovered in recent years that the pathophysiology of orthopedic disorders is significantly influenced by the microbiota. By employing machine learning and deep learning techniques to conduct a thorough analysis of the disease-causing microbiome, we can enhance our comprehension of the pathophysiology of many illnesses and expedite the creation of novel treatment approaches. Today's science is undergoing a revolution because to the introduction of machine learning and deep learning technologies, and the field of biomedical research is no exception. The genesis, course, and management of orthopedic disorders are significantly influenced by pathogenic microbes. Orthopedic infection diagnosis and treatment are made more difficult by the lengthy and imprecise nature of traditional microbial detection and characterization techniques. These cutting-edge analytical techniques are offering previously unheard-of insights into the intricate relationships between orthopedic health and pathogenic microbes, opening up previously unimaginable possibilities for illness diagnosis, treatment, and prevention. The goal of biomedical research has always been to improve diagnostic and treatment methods while also gaining a deeper knowledge of the processes behind the onset and development of disease. Although traditional biomedical research methodologies have demonstrated certain limits throughout time, they nevertheless rely heavily on experimental data and expertise. This is the area in which deep learning and machine learning approaches excel. The advancements in machine learning (ML) and deep learning (DL) methodologies have enabled us to examine vast quantities of data and unveil intricate connections between microorganisms and orthopedic disorders. The importance of ML and DL in detecting, categorizing, and forecasting harmful microorganisms in orthopedic infectious illnesses is reviewed in this work.

Demographic and Diagnostic Factors in Physical Therapy Attendance.

Introduction Physical therapy (PT) is an effective nonoperative treatment for various orthopedic diagnoses. However, patients may have many reasons to dismiss PT, including favoringanother intervention for their injury, time constraints, transportation, and cost. This dismissal of PT may contribute to inadequate patient compliance. This study aimed to elucidate patient compliance with a basic PT prescription and whether PT led to subjective injury improvement. Methods This is a retrospective study of patients observed in Stony Brook Orthopedic clinics from 08/01/2022 to 12/23/2022. Patients prescribed PT received a phone call six weeks after the PT prescription. The primary outcome was patient attendance at PT. Secondary outcomes were subjective; symptomatic improvement was listed asbetter, worse, or the same. Chi-square testing was used to compare outcomes. Results A total of 100 patients were enrolled in the study. Patients prescribed PT following surgery were more likely to attend compared to patients prescribed PT as a primary treatment (P value=0.027). The association between attendance at PT and a change in subjective symptoms (better, worse, same) was not significant. Patients' age, sex, and chronicity of injury were not significant factors in PT attendance. Of the 40 patients who did not attend PT, 14 cited time constraints, 11 utilized self-directed treatment, three cited insurance, two cited transportation, and 10 cited other reasons. Conclusions Overall, postoperative patients were more likely to attend PT compared to patients prescribed PT as a primary treatment. Factors such as age, sex, and chronicity of injury did not affect whether a patient attended PT. Of the patients enrolled, 71% stated subjective improvement in symptoms, but there was no association between symptoms and PT attendance. This study highlights the characteristics of those patient factors that may influence PT compliance and underscores the importance of further research into the population most likely to attend and benefit from PT.

Orthopedic surgery in Palau-Current capacity, needs, and future directions.

Palau, an island nation in Micronesia, is a medically underserved area with a shortage of specialty care services. Orthopedic diagnoses in Palau remain among the three most common reasons for costly off-island medical referral. The purpose of this study was to assess Palau's current orthopedic surgery capacity and needs to inform interventions to build capacity to improve care access and quality. Orthopedic needs and capacity assessment tools developed by global surgical outreach experts were utilized to gather information and prompt discussions with a broad range of Palau's most knowledgeable stakeholders (n=6). Results were reported descriptively. Finance, community impact, governance, and professional development were the lowest-scored domains from the Capacity Assessment Tool for orthopedic surgery (CAT-os), indicating substantial opportunity to build within these domains. According to administrators (n=3), governance and finance were the greatest capacity-building priorities, followed by professional development and partnership. Belau National Hospital (BNH) had adequate surgical infrastructure. Skin grafting, soft tissue excision/resection, infection management, and amputation were the most commonly selected procedures by stakeholders reporting orthopedic needs. This study utilizes a framework for orthopedic capacity-building in Palau which may inform partnership between Palau's healthcare system and orthopedic global outreach organizations with the goal of improving the quality, safety, and value of the care delivered. This demonstration of benchmarking, implementation planning, and subsequent re-evaluation lays the foundation for the understanding of capacity-building and may be applied to other medically underserved areas globally to improve access to high-quality orthopedic care.

Examining rehabilitation access disparities: an integrated analysis of electronic health record data and population characteristics through bivariate choropleth mapping.

Despite efforts to view electronic health records (EHR) data through an equity lens, crucial contextual information regarding patients' social environments remains limited. Integrating EHR data and Geographic Information Systems (GIS) technology can give deeper insights into the relationships between patients' social environments, health outcomes, and geographic factors. This study aims to identify regions with the fastest and slowest access to outpatient physical therapy services using bivariate choropleth maps to provide contextual insights that may contribute to health disparity in access. This was a retrospective cohort study of patients' access timelines for the first visit to outpatient physical therapy services (n = 10,363). The three timelines evaluated were (1) referral-to-scheduled appointment time, (2) scheduled appointment to first visit time, and (3) referral to first visit time. Hot and coldspot analyses (CI 95%) determined the fastest and slowest access times with patient-level characteristics and bivariate choropleth maps that were developed to visualize associations between access patterns and disadvantaged areas using Area Deprivation Index scores. Data were collected between January 1, 2016 and January 1, 2020. EHR data were geocoded via GIS technology to calculate geospatial statistics (Gi∗ statistic from ArcGIS Pro) in an urban area. Statistically significant differences were found for all three access timelines between coldspot (i.e., fast access group) and hotspot (i.e., slow access group) comparisons (p < .05). The hotspot regions had higher deprivation scores; higher proportions of residents who were older, privately insured, female, lived further from clinics; and a higher proportion of Black patients with orthopaedic diagnoses compared to the coldspot regions. Our study identified and described local areas with higher densities of patients that experienced longer access times to outpatient physical therapy services. Integration of EHR and GIS data is a more robust method to identify health disparities in access to care. With this approach, we can better understand the intricate interplay between social, economic, and environmental factors contributing to health disparities in access to care.

Validity of the ACS NSQIP surgical risk calculator as a tool to predict postoperative outcomes in subacute orthopedic trauma diagnoses

PurposeThis retrospective study aimed to validate the ACS NSQIP Surgical Risk Calculator (SCR) to predict 30-day postoperative outcomes in patients with one of the following subacute orthopedic trauma diagnoses; multiple rib fractures, pelvic ring/acetabular fracture, or unilateral femoral fracture. MethodsData of patients with these diagnoses treated between January 1, 2015 and September 19, 2020 were extracted from the patients’ medical files. Diagnostic performance, discrimination, calibration, and accuracy of the ACS NSQIP SRC to predict specific outcomes developing within 30 days after surgery was determined. ResultsThe total cohort of the three diagnoses consisted of 435 patients. ACS NSQIP SRC underestimated the risk for serious complications, especially in patients with multiple rib fractures (8.3% predicted vs 17.2% observed) or pelvic ring/acetabular fracture (6.1% vs 19.8%). Underestimation was more pronounced for the composite outcome ‘any complication’. Sensitivity ranged from 16.7% to 100% and specificity from 41.1% to 97.1%. Specificity exceeded sensitivity for pelvic ring/acetabular and femoral fractures. Discrimination was good for predicting death (femoral fracture), fair for readmission (femoral fracture), serious complication (multiple rib fractures), and any complication (multiple rib fractures), but poor in all other outcomes and diagnoses. Calibration and accuracy were adequate for all three diagnoses (p-value for Hosmer-Lemeshow test >0.05 and Brier scores <0.25). ConclusionPerformance of the ACS NSQIP SRC in the studied cohort was variable for all three diagnoses. Although it underestimated the risk of most outcomes, calibration and accuracy seemed generally adequate. For most outcomes, adequate diagnostic performance and discrimination could not be confirmed.

Characterizing NSAID Allergy and Strategies for Management in Patients with Rheumatological and Orthopaedic Conditions, in a Single Tertiary Hospital in Hong Kong

Background Non-steroidal anti-inflammatory drugs (NSAIDs) are amongst the most frequently prescribed medications, their associated hypersensitivity reactions can not only lead to potentially severe reactions, but also limit analgesic and anti-inflammation options. This is especially true for those who are ailed with rheumatological or orthopaedic diseases leading to chronic pain and inflammatory conditions. This highlights the importance of identifying different types of NSAID hypersensitivity, and to find safe alternatives, namely selective COX-2 inhibitors, to groups of patients that may benefit the most from its utility. Objective To assess and categorise patients with suspected NSAID hypersensitivity, and to successfully provide alternatives to those with chronic rheumatologic and orthopedic ailments. Methods 115 patients with suspected NSAID hypersensitivity were referred to Queen Mary Hospital for specialist evaluation between Jan 2023 and March 2024, those suitable were later challenged and delabelled. Remaining patients were assessed as clinically compatible with NSAID hypersensitivity, and later separated into whether they had background of orthopedic or rheumatological conditions, hence strong indications for NSAIDs, and without, to which selective COX-2 inhibitors tolerance tests were offered. Results Of 115 patients, 20% (23/115) were assessed as unlikely to have NSAID hypersensitivity, and later challenged. 18.2% (21/115) had negative challenges and were delabelled; only 2 patients had positive reactions, confirming NSAID hypersensitivity, of which symptoms were mild and did not require hospitalization. 82% of the remaining patients (94/115) were then later stratified into different NSAID hypersensitivity reactions according to European Academy of Allergy &amp; Clinical Immunology (EAACI) guidelines. 57.3% (66/115) of patients were able to resume use of NSAIDs either by finding an alternative NSAID, namely a selective COX2 inhibitor (45/115, 39.1%), or through a negative drug challenge (21/115, 18.2%). Overall there was no significant difference in the proportion of patients with successful COX2 inhibitor challenges between the group with rheumatological and orthopedic diagnoses against those without (62% vs 54% p=0.414). 29 patients are still pending workup, likely underestimating the amount of patients that are able to resume NSAIDs. Conclusion NSAID hypersensitivity is amongst the most commonly reported drug allergies, and may present with many different clinical phenotypes. Patients with suspected NSAID hypersensitivity require allergist evaluation, and if not clinically suggestive of allergy, would benefit from drug challenges, especially in cases with underlying rheumatological or orthopedic conditions, where NSAIDs are essential. In situations where NSAID hypersensitivity is considered likely, selective COX-2 inhibitors can often be considered as a suitable alternative.

Ab. No. 22 Effectiveness of Combined Core Exercises and Routine Rehabilitation in Improving Muscle Strength and Functionality in Knee Osteoarthritis: A 4-Week Intervention Study

Introduction: KOA is progressively disabling in nature, and developing effective treatment strategies is crucial to impede disease progression. Recent research has explored the role of core muscle exercises in mitigating KOA progression. This study evaluates the effectiveness of integrating core strengthening exercises into standard KOA rehabilitation. The study aims to assess the efficacy of incorporating core strengthening exercises and a routine rehabilitation program for knee osteoarthritis (KOA) over 4 weeks and evaluate its impact on physical function tests, knee muscle strength, and core endurance. Methods: Fifteen participants meeting specific KOA criteria completed a four-week intervention combining conventional rehabilitation and core exercises. Selection criteria included orthopedic diagnosis, incorporating medical history, radiographic imaging, and clinical indicators of KOA. A pre-post analysis was done, wherein a portable dynamometer was used to assess for knee muscle strength and physical function tests (stair climb, 30-second sit-to-stand, 40-meter fast-paced walking, and timed up-and-go), and core endurance was evaluated. Statistical analysis using JAMOVI was done, with a significance level of P &lt; 0.05. Result: Knee muscle strength in the affected knee’s flexors and unaffected knee’s extensors and 30-second sit-to-stand showed no significant difference. In contrast, the timed up-and-go test, stair climb test, 40-second fast-paced walking test, and endurance test showed statistically significant differences. Conclusion: After a four-week supervised exercise program, participants exhibited enhanced core endurance and physical function, showcasing the positive effects of exercise in these domains. However, knee muscle strength did not significantly differ, resulting in the need for longer follow-up studies. The study implies that integrating core exercises into routine KOA rehabilitation can enhance physical function and endurance, emphasizing the need for their inclusion in long-term treatment plans for KOA patients.

Deep Learning-Based Hip X-ray Image Analysis for Predicting Osteoporosis

Osteoporosis is a common problem in orthopedic medicine, and it has become an important medical issue in orthopedics as Taiwan is gradually becoming an aging society. In the diagnosis of osteoporosis, the bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the main criterion for orthopedic diagnosis of osteoporosis, but due to the high cost of this equipment and the lower penetration rate of the equipment compared to the X-ray images, the problem of osteoporosis has not been effectively solved for many people who suffer from osteoporosis. At present, in clinical diagnosis, doctors are not yet able to accurately interpret X-ray images for osteoporosis manually and must rely on the data obtained from DXA. In recent years, with the continuous development of artificial intelligence, especially in the fields of machine learning and deep learning, significant progress has been made in image recognition. Therefore, it is worthwhile to revisit the question of whether it is possible to use a convolutional neural network model to read a hip X-ray image and then predict the patient’s BMD. In this study, we proposed a hip X-ray image segmentation model and a hip X-ray image recognition classification model. First, we used the U-Net model as a framework to segment the femoral neck, greater trochanter, Ward’s triangle, and the total hip in the hip X-ray images. We then performed image matting and data augmentation. Finally, we constructed a predictive model for osteoporosis using deep learning algorithms. In the segmentation experiments, we used intersection over union (IoU) as the evaluation metric for image segmentation, and both the U-Net model and the U-Net++ model achieved segmentation results greater than or equal to 0.5. In the classification experiments, using the T-score as the classification basis, the total hip using the DenseNet121 model has the highest accuracy of 74%.

PECULIARITIES OF CORRELATION PATTERNS BETWEEN MUSCULOSKELETAL AND DENTOALVEOLAR SYSTEM DISORDERS AND ELEVATED PHYSICAL ACTIVITY IN CHILDREN

Introduction. The physical development and engagement in sports activities have a direct impact on the overall formation of the human body. Previous research on the impact of sports on orthopedic and dental conditions in children has primarily focused on factors and features related to injuries. While some studies have explored the influence of sports on orthopedic conditions, comprehensive research addressing orthopedic and stomatological pathology in connection with sports activities has been lacking.&#x0D; The objective of this study is to investigate the influence of physical activity on the status of both the locomotor and maxillofacial systems and to evaluate their correlation with fundamental anthropometric indicators.&#x0D; Materials and Methods. For this study, a cohort of 78 children (38 girls and 40 boys), aged 14 to 17 years with an average age of 15.5 years, underwent examinations in both 2019-2020 and 2023. A thorough statistical analysis of the gathered data was conducted to draw meaningful conclusions.&#x0D; Orthopedic pathology was observed in 37.21% of individuals engaged in sports and 22.86% of those who did not participate (p=0.263). Dental pathology was found in 23.26% of individuals involved in sports compared to 17.14% in those who did not engage in sports (p=0.581). Over a span of 3 years, individuals participating in sports experienced an average weight change of 14.82 kg, while those not involved in sports had an average change of 10.31 kg (p=0.02). The average height was 177.0 cm in individuals with orthopedic pathology and 170.0 cm in those without a diagnosed orthopedic condition (p=0.008). The mean growth over 3 years was 15.0 cm in individuals with orthopedic pathology and 9.0 cm in those without an established orthopedic diagnosis (p=0.032). Children with dental pathology gained an average of 8.34 kg of body weight over 3 years, whereas those without dental pathology gained 13.89 kg (p=0.019).&#x0D; Conclusions. Engaging in sports activities does not significantly impact the occurrence or development of orthopedic and stomatological pathology. Anthropometric indicators, specifically height and body weight, are associated with orthopedic and dental pathology, respectively. Children exhibiting greater and more intensive growth tend to have a higher frequency of orthopedic pathology. Dental pathology is more prevalent in children with lower body weight.

Application and prospect of machine learning in orthopaedic trauma

To review the current applications of machine learning in orthopaedic trauma and anticipate its future role in clinical practice. A comprehensive literature review was conducted to assess the status of machine learning algorithms in orthopaedic trauma research, both nationally and internationally. The rapid advancement of computer data processing and the growing convergence of medicine and industry have led to the widespread utilization of artificial intelligence in healthcare. Currently, machine learning plays a significant role in orthopaedic trauma, demonstrating high performance and accuracy in various areas including fracture image recognition, diagnosis stratification, clinical decision-making, evaluation, perioperative considerations, and prognostic risk prediction. Nevertheless, challenges persist in the development and clinical implementation of machine learning. These include limited database samples, model interpretation difficulties, and universality and individualisation variations. The expansion of clinical sample sizes and enhancements in algorithm performance hold significant promise for the extensive application of machine learning in supporting orthopaedic trauma diagnosis, guiding decision-making, devising individualized medical strategies, and optimizing the allocation of clinical resources.

Applications of Natural Language Processing Tools in Orthopaedic Surgery: A Scoping Review

The advent of many popular commercial forms of natural language processing tools has changed the way we can utilise digital technologies to tackle problems with big data. The objective of this review is to evaluate the current research and landscape of natural language processing tools and explore their potential use and impact in the field of orthopaedic surgery. In doing so, this review aims to answer the research question of how NLP tools can be utilised to streamline processes within orthopedic surgery. To do this, a scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Arksey and O’Malley framework for scoping reviews, as well as a computer-assisted literature search on the Medline, Embase and Google Scholar databases. Papers that evaluated the use of natural language processing tools in the field of orthopaedic surgery were included. Our literature search identified 24 studies that were eligible for inclusion. Our scoping review captured articles that highlighted multiple uses of NLP tools in orthopaedics. In particular, one study reported on the use of NLP for intraoperative monitoring, six for detection of adverse events, five for establishing orthopaedic diagnoses, two for assessing the patient experience, two as an informative resource for patients, one for predicting readmission, one for triaging, five for auditing and one for billing and coding. All studies assessed these various uses of NLP through its tremendous computational ability in extracting structured and unstructured text from the medical record, including operative notes, pathology and imaging reports, and progress notes, for use in orthopaedic surgery. Our review demonstrates that natural language processing tools are becoming increasingly studied for use and integration within various processes of orthopaedic surgery. These AI tools offer tremendous promise in improving efficiency, auditing and streamlining tasks through their immense computational ability and versatility. Despite this, further research to optimise and adapt these tools within the clinical environment, as well as the development of evidence-based policies, guidelines and frameworks are required before their wider integration within orthopaedics can be considered.

Evaluating the Use of PROMs in Paediatric Orthopaedic Registries.

Patient-reported outcome measures (PROMs) provide structured information on the patient's health experience and facilitate shared clinical decision-making. Registries that collect PROMs generate essential information about the clinical course and efficacy of interventions. Whilst PROMs are increasingly being used in adult orthopaedic registries, their use in paediatric orthopaedic registries is not well known. The purpose of this systematic review was to identify the frequency and scope of registries that collect PROMs in paediatric orthopaedic patient groups. In July 2023, six databases were systematically searched to identify studies that collected PROMs using a registry amongst patients aged under 18 years with orthopaedic diagnoses. Of 3190 identified articles, 128 unique registries were identified. Three were exclusively paediatric, 27 were majority paediatric, and the remainder included a minority of paediatric patients. One hundred and twenty-eight registries collected 72 different PROMs, and 58% of these PROMs were not validated for a paediatric population. The largest group of orthopaedic registries collected PROMs on knee ligament injuries (21%). There are few reported dedicated orthopaedic registries collecting PROMs in paediatric populations. The majority of PROMs collected amongst paediatric populations by orthopaedic registries are not validated for patients under the age of 18 years. The use of non-validated PROMs by registries greatly impedes their utility and impact. Dedicated orthopaedic registries collecting paediatric-validated PROMs are needed to increase health knowledge, improve decision-making between patients and healthcare providers, and optimise orthopaedic management.

Semiquantitative index of symptomatic minor instability of the lateral elbow at CT arthrography (SMILE index): clinical applicability and reproducibility study.

To assess the applicability of a semiquantitative index for symptomatic minor instability of the lateral elbow (SMILE). CT arthrograms of consecutive patients with lateral elbow pain who underwent ultrasound-guided CT arthrography at our orthopedic center between April 2019 and May 2022 were included. Images were acquired at 100 kVp and 80 mAs. An expert radiologist (R1) and a radiology resident (R2) retrospectively performed an independent, blinded evaluation of the arthrograms to assess the presence of imaging findings suggestive of elbow instability. The SMILE index (0-8) was obtained adding (I) radial head chondromalacia (0 - 1); (II) humeral capitellum chondromalacia (0 - 1); (III) humeral trochlear ridge chondromalacia (0 - 1); (IV) annular ligament laxity (0 - 2); (V) synovial thickening (0 - 1); (VI) humeroradial joint asymmetry (0 - 1); and (VII) capsular tear (0 - 1). R1 repeated the assessment after 14days. Cohen's weighted κ statistic and raw concordance were used to appraise reproducibility. Eighty patients (median age 49years, interquartile range 40-53years, 49, 61% males) underwent CT arthrography at our center, and 10 (12%) of them underwent bilateral elbow examination, leading to 90 included CT arthrograms. Median SMILE index was 4 (IQR: 2-5) for R1, 4 (IQR: 2-5) for R2, and 4 (IQR: 2-5) for the second assessment by R1. Intra-reader agreement was excellent (κ = 0.94, concordance 87%), while inter-reader agreement was substantial (κ = 0.75, concordance 67%). The proposed SMILE index showed good reproducibility; further studies are warranted to correlate our index with clinical and surgical data. Our scoring system allows a standardized evaluation of patients with lateral elbow pain and instability suitable for application into clinical practice, complementing the orthopedic surgeon's clinical diagnosis with imaging findings that may aid treatment choices. • Lateral elbow pain is often interpreted clinically as lateral epicondylitis, but it can also encompass intra-articular pathology. • The proposed arthrographic index allows comprehensive quantification of lateral elbow pathology with good reproducibility and application times. • Our index provides the orthopedic surgeon with information regarding intra-articular findings, aiding treatment choices.