Orthopaedic Experts Research Articles

Periprosthetic acetabular fractures: classifications, treatment and challenges

Periprosthetic acetabular fractures (PPAF) are fractures of the acetabulum with ahip endoprosthesis in place. They are arare complication, although they are occurring more frequently due to the increase in patients being fitted with total hip arthroplasty (THA) and the long service life of the implants. At present, only asmall amount of scientific literature exists, particularly regarding the surgical treatment of these fracture types.The aim of this paper is to provide an overview of the topic of PPAF with acritical review of the current literature and to present the necessary surgical treatment.An evaluation of the current literature on the topic of PPAF with afocus on the surgical treatment of fractures is carried out.Surgical treatment is technically demanding due to the pelvic ring instability with removal of the bone tension for secure acetabular cup fixation and should lead to the recovery of the biomechanical stability of the pelvis and thus the secure anchoring of the acetabular cup. An interdisciplinary approach requiring both trauma surgery and orthopaedic expertise is certainly recommended, as older and comorbid patients with poor bone quality are particularly frequently affected.The treatment of periprosthetic acetabular fractures, especially in older patients, requires not only the individual expertise of surgeon involved in the operation but also agoal-oriented and consistent interdisciplinary approach by the surgeons involved from the fields of orthopaedics and trauma surgery in view of the patients' frequent comorbidities. By working together, the optimal and individualized operation can be performed for the patient.

Critical elements of international academic partnerships in orthopaedic surgery: a modified Delphi approach.

Despite the recent emphasis on promoting international collaborations within orthopaedic surgery, criteria for determining the strengths of such partnerships has not been established. The purpose of this study was to evaluate orthopaedic experts' perceptions of the most valuable characteristics of international academic partnerships. This study was conducted using a modified Delphi methodology. Experts were identified through the Consortium of Orthopaedic Academic Traumatologists (COACT). Responses were collected from February to September 2022. Three rounds of surveys listing possible topics on a 5-point Likert scale were used to develop consensus among a group of experts. Consensus criteria for topic inclusion in the final scale was determined as a rating of "strongly agree" or "agree" by ≥70% of the participants in the third survey. The Round 1 survey was distributed to 96 invited participants within the COACT network, of which 50 experts (52.1%) completed the first survey. Consensus was reached on 54 topics organized into the following 5 categories: Research, Advocacy/Leadership, Training/Surgical Skills, Education/Knowledge Exchange, and Sustainability and Safety (RATES Criteria). Determining the most valuable characteristics of successful international academic partnerships can lead to more sustainable, mutually beneficial collaborations. The criteria identified in this study can provide the foundation for developing new partnerships and assessing existing ones.

Study on automatic and rapid diagnosis of distal radius fracture by X-ray

This article aims to combine deep learning with image analysis technology and propose an effective classification method for distal radius fracture types. Firstly, an extended U-Net three-layer cascaded segmentation network was used to accurately segment the most important joint surface and non joint surface areas for identifying fractures. Then, the images of the joint surface area and non joint surface area separately were classified and trained to distinguish fractures. Finally, based on the classification results of the two images, the normal or ABC fracture classification results could be comprehensively determined. The accuracy rates of normal, A-type, B-type, and C-type fracture on the test set were 0.99, 0.92, 0.91, and 0.82, respectively. For orthopedic medical experts, the average recognition accuracy rates were 0.98, 0.90, 0.87, and 0.81, respectively. The proposed automatic recognition method is generally better than experts, and can be used for preliminary auxiliary diagnosis of distal radius fractures in scenarios without expert participation.

One Year of Experience in the Orthopaedic and Trauma Surgical Care of War Refugees and Soldiers from Ukraine in a Maximum Care Trauma Centre.

According to the United Nations, around 8,400 people have been injured and over 5,800 killed on the Ukrainian side in the Ukraine war, which has been going on for over 14 months. Extensive humanitarian aid operations were carried out to support Ukraine, so that war-wounded people from Ukraine were also cared for in Germany. In a retrospective cohort study, 10 patients were examined who were treated in the department between February 24th 2022 and February 24th 2023, using the cloverleaf system from Ukraine.The average duration of inpatient treatment was 53.10 days. The average ISS was 23.7. The patients were operated on an average of 3.3 times in our institution. All patients received consultative psychological care. All patients were initially put into protective isolation until the results of a corona test and microbiological swabs were available. After preliminary protective isolation, further isolation had to be carried out in 5 cases due to germs requiring isolation. Eight patients were released to state accommodation. Three patients were transferred back to Ukraine at their own request.The treatment of war-injured patients from Ukraine represents a particular challenge. It absolutely requires an interdisciplinary treatment concept that, in addition to special trauma surgery and orthopaedic expertise, also requires plastic-reconstructive, microbiological and, last but not least, psychological care. Due to the high rate of infections requiring isolation, long, costly therapy with multiple revision operations is often necessary.

Research on automated rapid diagnosis of distal radius fractures using X-ray images

The primary diagnostic method for distal radius fractures remains conventional X-ray imaging. In emergency situations, rapid assessment and decision-making are often required from non-orthopedic physicians or junior radiologists in the emergency room. Therefore, an accurate and efficient auxiliary diagnostic technology for distal radius fractures is of great significance. This paper combines deep learning with image analysis techniques to propose an effective classification method for types of distal radius fractures. Firstly, an extended U-Net three-level cascade segmentation network is used for precise segmentation of the most critical joint surface and non-joint surface areas for fracture identification. The edge is further optimized using the central pixel image block classification method. Then, fracture identification is performed separately on the joint surface and non-joint surface areas. Finally, based on the classification results of the two types of images, a comprehensive judgment is made to determine normal or ABC fracture types. The experimental X-ray data comes from three tertiary hospitals, with a total of 12,000 images in the training set, 3,000 of each type, and 1,200 images in the test set, 300 of each type. To further demonstrate the generalization performance of the classification experiment, an additional 500 images were added for fracture classification testing, coming from collaborative medical institutions in the United States and Germany. All images were annotated by orthopedic medical experts with more than ten years of experience. The accuracy rates for normal, type A, type B, and type C fractures in the test set were 0.99, 0.92, 0.91, and 0.82, respectively. For orthopedic medical experts, the average recognition accuracy rates were 0.98, 0.90, 0.87, and 0.81. The proposed automatic recognition method overall performs better than experts and can be used for preliminary auxiliary diagnosis of distal radius fractures without expert participation.

Research on automated rapid diagnosis of distal radius fractures using X-ray images

The primary diagnostic method for distal radius fractures remains conventional X-ray imaging. In emergency situations, rapid assessment and decision-making are often required from non-orthopedic physicians or junior radiologists in the emergency room. Therefore, an accurate and efficient auxiliary diagnostic technology for distal radius fractures is of great significance. This paper combines deep learning with image analysis techniques to propose an effective classification method for types of distal radius fractures. Firstly, an extended U-Net three-level cascade segmentation network is used for precise segmentation of the most critical joint surface and non-joint surface areas for fracture identification. The edge is further optimized using the central pixel image block classification method. Then, fracture identification is performed separately on the joint surface and non-joint surface areas. Finally, based on the classification results of the two types of images, a comprehensive judgment is made to determine normal or ABC fracture types. The experimental X-ray data comes from three tertiary hospitals, with a total of 12,000 images in the training set, 3,000 of each type, and 1,200 images in the test set, 300 of each type. To further demonstrate the generalization performance of the classification experiment, an additional 500 images were added for fracture classification testing, coming from collaborative medical institutions in the United States and Germany. All images were annotated by orthopedic medical experts with more than ten years of experience. The accuracy rates for normal, type A, type B, and type C fractures in the test set were 0.99, 0.92, 0.91, and 0.82, respectively. For orthopedic medical experts, the average recognition accuracy rates were 0.98, 0.90, 0.87, and 0.81. The proposed automatic recognition method overall performs better than experts and can be used for preliminary auxiliary diagnosis of distal radius fractures without expert participation.

A Blinded Comparison of Three Generative Artificial Intelligence Chatbots for Orthopaedic Surgery Therapeutic Questions.

Objective To compare the quality of responses from three chatbots (ChatGPT, Bing Chat, and AskOE) across various orthopaedic surgery therapeutic treatment questions. Design We identified a series of treatment-related questions across a range of subspecialties in orthopaedic surgery. Questions were "identically" entered into one of three chatbots (ChatGPT, Bing Chat, and AskOE) and reviewed using a standardized rubric. Participants Orthopaedic surgery experts associated with McMaster University and the University of Toronto blindly reviewed all responses. Outcomes The primary outcomes were scores on a five-item assessment tool assessing clinical correctness, clinical completeness, safety, usefulness, and references. The secondary outcome was the reviewers' preferred response for each question. We performed a mixed effects logistic regression to identify factors associated with selecting a preferred chatbot. Results Across all questions and answers, AskOE was preferred by reviewers to a significantly greater extent than both ChatGPT (P<0.001) and Bing (P<0.001). AskOE also received significantly higher total evaluation scores than both ChatGPT (P<0.001) and Bing (P<0.001). Further regression analysis showed that clinical correctness, clinical completeness, usefulness, and references were significantly associated with a preference for AskOE. Across all responses, there were four considered as having major errors in response, with three occurring with ChatGPT and one occurring with AskOE. Conclusions Reviewers significantly preferred AskOE over ChatGPT and Bing Chat across a variety of variables in orthopaedic therapy questions. This technology has important implications in a healthcare setting as it provides access to trustworthy answers in orthopaedic surgery.

Incidence of Intraoperative Cardiothoracic Intervention During Open Surgery Following Acute Posterior Sternoclavicular Joint Injury: A Case Series and Review of the Literature.

Acute posterior sternoclavicular joint injuries are rare but potentially lethal injuries-signs of mediastinal compression range from nonspecific to neurovascular compromise. Currently, orthopaedic experts recommend a cardiothoracic surgeon be placed on standby during open surgery for potential intraoperative complications. However, few studies have reported on how often cardiothoracic intervention is required. First, we identified patients in our institution by CPT codes 23530, 23525, and 23532 from January 1, 2002 to May 1, 2023. Demographic variables and intraoperative cardiothoracic intervention rates were collected. Second, we systematically reviewed the literature to identify articles on acute posterior sternoclavicular injury using PubMed, Embase, and CINAHL databases (through August 20, 2023). Exclusion criteria included conservative treatment, successful closed reduction, chronic injury (>6wk) cadaver studies, reviews, and nonavailable text. Thirteen local patients underwent open surgery for an acute posterior sternoclavicular joint injury, 11 males and 2 females with an average age of 18.2 years old (range: 15 to 32.4). The most common mechanism of injury was sports (n=9; 69.2%). Four (30.8%) patients had physical or radiographic evidence of mediastinal compression. No patients required intraoperative cardiothoracic intervention in our institution. The literature search yielded 132 articles and 512 open surgeries for acute posterior sternoclavicular joint injuries. Four patients required intraoperative cardiothoracic intervention, all of whom presented with polytrauma and/or clinical or radiographic signs of neurovascular compromise, giving a combined overall rate of 0.76%. Expert opinion commonly recommends cardiothoracic backup during open surgery for acute posterior sternoclavicular joint injuries. On the basis of our local data and systematic literature review, we found an overall cardiothoracic intervention rate of 0.76%. In the presence of polytrauma and/or findings of neurovascular compromise, we suggest having cardiothoracic surgery on close standby during the procedure. However, a patient with an isolated acute posterior sternoclavicular joint injury and no clinical or radiographic findings of neurovascular compromise does not appear to require a cardiothoracic surgeon on standby. Ultimately, the decision to involve cardiothoracic backup during open surgery for an acute posterior sternoclavicular injury should be made on a case-by-case basis after a thorough physical and radiographic evaluation of the patient. Level III.

Conception and validation of A 3d printed learning model of supra condylar fracture of children

The supracondylar fracture of the child is a common fracture. Its physiology, physiopathology and treatment use periosteum. As far as we know, there is no 3D printed model of this typical fracture in children with periosteum. The purposes of the research are to present the concept of an educational 3D printed supra condylar model with periosteum of the child and its expert validation. Materials and methodsThe basis for the paediatric elbow model was a 3D scan of a four-year-old girl. Once the data had been extracted, the models were constructed using 3D Slicer®, Autodesk fusion 360® and Ultimaker Cura® software's. The Creality 3D Ender 6 SE Printer® used PLA filaments to print bone and TPU for periosteum. Printing took place at the University Hospital and the steps were modelled by hand. 3D printed bones and 3D printed periosteum were manually assembled. ParticipantsExpert validation with twelve paediatric orthopaedic surgeons took place in three University hospitals of the North of France. ResultsFour Lagrange and Rigault 3D printed models of supracondylar fractures with periosteum were obtained with 200 h of design, printing and manual assembly based on a four-year-old elbow. According to the paediatric orthopaedic surgery experts, the size of the model is very good, but the model itself is of little interest compared to the information provided by the reconstruction of a 3D scanner. In total, with 9 out of 12 questions scoring higher than 8/10, the model was considered to be a good model for informing parents and teaching students. ConclusionsThis study details the design of the first 3D-printed supra condylar fracture model in children with a full-size physeal and periosteum. The model has been validated by paediatric orthopaedic surgery experts.

Using Mixed Reality Simulation to Improve Junior Medical Trainees’ Preparedness to Manage High-Acuity Trauma

High-acuity trauma necessitates experienced and rapid intervention to prevent patient harm. However, upskilling junior trainees through hands-on management of real trauma cases is rarely feasible without compromising patient safety. This...

Consensus on the definition and criteria for failure of surgical treatment in bacterial arthritis of a native joint: An international Delphi study.

The literature presents a wide range of success rates for a single surgical intervention of bacterial-septic-arthritis, and there is a lack of clear criteria for identifying treatment failure and making decisions about reintervention. This Delphi study aims to establish a consensus among an international panel of experts regarding the definition of treatment failure and the criteria for reintervention in case of bacterial arthritis. The conducting and reporting Delphi studies (CREDES) criteria were used. Data from a systematic review was provided as the basis for the study. A list of 100 potential experts were identified. The study was designed and conducted as follows: (I) identification and invitation of an expert panel, (II) informing the participating expert panel on the research question and subject, and (III) conducting two or three Delphi rounds to reach consensus on explicit research items. Potential criteria were rated on a five-point Likert scale. Sixty orthopaedic experts from nine countries participated in this Delphi study, with 55 completing all three rounds. The mean experience as an orthopaedic surgeon was 15 years (SD ± 9). Strong (96%) consensus was reached on the definition of treatment failure: the persistence of physical signs of arthritis (e.g., pain and swelling) and/or systemic inflammation (e.g., fever and no improvement in CRP) despite surgical and antibiotic treatment. Furthermore, consensus (>80%) was reached on six criteria influencing the decision for reintervention; pain (81%), sepsis (98%), fever (88%), serum CRP (93%), blood culture (82%), and synovial fluid culture (84%). The definition of treatment failure for bacterial arthritis after a single surgical intervention was established through a three-round Delphi study. Additionally, consensus was reached on six criteria that are helpful for determining the need for reintervention. This definition and these criteria may help in the development of clinical guidelines, and will empower physicians to make more precise and consistent decisions regarding reintervention for patients, ultimately aiming to reduce over- and undertreatment and improve patient outcomes. Level V.

A New Deep Learning Algorithm for Detecting Spinal Metastases on Computed Tomography Images.

Retrospective diagnostic study. To automatically detect osteolytic bone metastasis lesions in the thoracolumbar region using conventional computed tomography (CT) scans, we developed a new deep learning (DL)-based computer-aided detection model. Radiographic detection of bone metastasis is often difficult, even for orthopedic surgeons and diagnostic radiologists, with a consequent risk for pathologic fracture or spinal cord injury. If we can improve detection rates, we will be able to prevent the deterioration of patients' quality of life at the end stage of cancer. This study included CT scans acquired at Tokyo Medical and Dental University (TMDU) Hospital between 2016 and 2022. A total of 263 positive CT scans that included at least one osteolytic bone metastasis lesion in the thoracolumbar spine and 172 negative CT scans without bone metastasis were collected for the datasets to train and validate the DL algorithm. As a test data set, 20 positive and 20 negative CT scans were separately collected from the training and validation datasets. To evaluate the performance of the established artificial intelligence (AI) model, sensitivity, precision, F1-score, and specificity were calculated. The clinical utility of our AI model was also evaluated through observer studies involving six orthopaedic surgeons and six radiologists. Our AI model showed a sensitivity, precision, and F1-score of 0.78, 0.68, and 0.72 (per slice) and 0.75, 0.36, and 0.48 (per lesion), respectively. The observer studies revealed that our AI model had comparable sensitivity to orthopaedic or radiology experts and improved the sensitivity and F1-score of residents. We developed a novel DL-based AI model for detecting osteolytic bone metastases in the thoracolumbar spine. Although further improvement in accuracy is needed, the current AI model may be applied to current clinical practice. Level III.

Efficacy of Faradic Foot Baths and Short Foot Exercises in Symptomatic Flatfoot: A Review.

Flatfoot is a common condition among adults, according to orthopedic experts. Flatfoot is defined in this document as a foot condition that occurs after the completion of skeletal growth and is characterized by either partial or complete reduction of the medial longitudinal arch (MLA). The purpose of this study was to evaluate the effects of short foot exercise (SFE) and faradic foot baths on people who have flat feet. This review focused on comprehensive original primary articles written in English. Numerous studies have been conducted in order to determine the effects of both interventions. The search yielded a wide range of papers, including editorials, review articles, freely available full texts, and abstracts. The results showed that both SFE and faradic foot baths effectively improved flat feet.

Segmentation of measurable images from standard plane of Graf hip ultrasonograms based on Mask Region-Based Convolutional Neural Network.

This study proposed a Mask Region-Based Convolutional Neural Network (R-CNN)-based automatic segmentation to accurately detect the measurable standard plane of Graf hip ultrasonography images via segmentation of the labrum, lower limb of ilium, and the iliac wing. The study examined the hip ultrasonograms of 675 infants (205 males, 470 females; mean age: 7±2.8 weeks; range, 3 to 20 weeks) recorded between January 2011 and January 2018. The standard plane newborn hip ultrasound images were classified according to Graf's method by an experienced ultrasonographer. The hips were grouped as type 1, type 2a, type 2b, and type 2c-D. Two hundred seventy-five ultrasonograms were utilized as training data, 30 were validation data, and 370 were test data. The three anatomical regions were simultaneously segmented by Mask-R CNN in the test data and defective ultrasonograms. Automatic instance-based segmentation results were compared with the manual segmentation results of an experienced orthopedic expert. Success rates were calculated using Dice and mean average precision (mAP) metrics. Of these, 447 Graf type 1, 175 type 2a or 2b, 53 type 2c and D ultrasonograms were utilized. Average success rates with respect to hip types in the whole data were 96.95 and 96.96% according to Dice and mAP methods, respectively. Average success rates with respect to anatomical regions were 97.20 and 97.35% according to Dice and mAP methods, respectively. The highest average success rates were for type 1 hips, with 98.46 and 98.73%, and the iliac wing, with 98.25 and 98.86%, according to Dice and mAP methods, respectively. Mask R-CNN is a robust instance-based method in the segmentation of Graf hip ultrasonograms to delineate the standard plane. The proposed method revealed high success in each type of hip for each anatomic region.

Integrated spine trauma team protocol: Combined neurosurgical and orthopedic experience for the management of traumatic spinal injuries.

During the last decades, spine surgery has grown exponentially. In spite of that, it remains a surgical specialty without a well-defined own certification. It is usually carried out, separately, by neurosurgeons and orthopedic surgeons, even if there is an overlapping of competence and skills. In our hospital, from January 2019, a systematic protocol called integrated spine trauma team protocol (ISTTP) was implemented to improve the management of traumatic spinal injuries in a multidisciplinary way. It is characterized by a specific algorithm from diagnosis to postoperative care. According to the new protocol, orthopedic spinal surgeons and neurosurgeons work together as an integrated spine trauma team. The authors analyzed, retrospectively, the results obtained by comparing patients treated before and after the application of the ISTTP. The new protocol allowed a statistically significant reduction in waiting time before surgery and complication rate. Moreover, early discharge of patients was recorded. To the best of our knowledge, this is the first study that described a specific algorithm for a standardized multidisciplinary management of the spinal trauma with combined orthopedic and neurosurgeon expertise. Our preliminary results suggest that the application of our ISTTP leads to better results for treating traumatic spinal injury (TSI).

ACL surgery: reasons for failure and management.

Despite the general success of anterior cruciate ligament reconstructions (ACL-R), there are still studies reporting a high failure rate. Orthopedic surgeons are therefore increasingly confronted with the treatment of ACL retears, which are often accompanied by other lesions, such as meniscus tears and cartilage damage and which, if overlooked, can lead to poor postoperative clinical outcomes. The literature shows a wide variety of causes for ACL-R failure. Main causes are further trauma and possible technical errors during surgery, among which the position of the femoral tunnel is thought to be one of the most important. A successful postoperative outcome after ACL-revision surgery requires good preoperative planning, including a thorough evaluation of patient's medical history, e.g. instability during daily or sports activity, increased general joint laxity, and hints for a low-grade infection. A careful clinical examination should be performed. Additionally, comprehensive imaging is necessary. Besides a magnetic resonance imaging, a CT scan is helpful to determine location of tunnel apertures and to analyze for tunnel enlargement. A lateral knee radiograph is helpful to determine the tibial slope. The range of surgical options for the treatment of ACL-R failure is broad today. Orthopedic surgeons and experts in Sports Medicine must deal with various possible associated injuries of the knee or unfavorable anatomical conditions for ACL-R. The aim of this review was to highlight predictors and reasons of failures of ACL-R as well as describe diagnostic procedures to individualize treatment strategies for improved outcome after revision ACL-R.

The Importance of Acetabular Morphometry in Determining Hip Dysplasia

The aim of this study was to evaluate the relation between acetabulum morphological measurements and present the reference values of the acetabulum. The study had a retrospective design and was conducted with 234 healthy subjects (108 females; 126 males) aged 18-53 years over a period of 4 years from 2018 to 2022. Eleven measurements including the center- edge angle (CEA), acetabular angle (AA), acetabular depth (AD), acetabular width (AW), dept to width ratio (ADWR), Extrusion A (EA)-B (EB), Extrusion index (EI), the lateral subluxation (LS), peak to edge distance (PED), and roof obliquity (RO) were taken. The p<0.05 value was considered significant. A significant difference was found in CEA, AA, EB, LS, and RO values, while there was no significance in the AD, AW, ADWR, EI, and PED measurements in comparison with acetabular morphometry according to gender. Also, in the evaluation of acetabulum to age-related changes, there was a significant difference in values of the CEA, AA, AD, AW, ADWR, LS, and PED from decades 1 to 5. The knowledge of radiological acetabulum findings is paramount for the diagnosis of hip dysplasia and may be useful for prosthesis, orthopedic and forensic experts. Also, the most interesting finding was that ADWR increased based on age in a directly proportional trend. The most apparent change based on age was seen in CEA (between decades 3-4), LS (decades 1-5), PED (decades 2-4), AD, and AW (decades 2-5).

Do symptoms of anxiety and/or depression and pain intensity before primary Total knee arthroplasty influence reason for revision? Results of an observational study from the Dutch arthroplasty register in 56,233 patients

ObjectiveAnxiety, depression and greater pain intensity before total knee arthroplasty (TKA) may increase the probability of revision surgery for remaining symptoms even without clear pathology or technical issues. We aimed to assess whether preoperative anxiety/depression and pain intensity are associated with revision TKA for less clear indications. MethodsLess clear indications for revision were defined after a Delphi process in which consensus was reached among 59 orthopaedic knee experts. We performed a cox regression analyses on primary TKA patients registered in the Dutch Arthroplasty Registry (LROI) who completed the EuroQol 5D 3 L (EQ5D-3 L) anxiety/depression score to examine associations between preoperative anxiety/depression and pain (Numeric Rating Scale (NRS)) with TKA revision for less clear reasons. These analyses were adjusted for age, BMI, sex, smoking, ASA score, EQ5D-3 L thermometer and OKS score. ResultsIn total, 25.9% patients of the 56,233 included patients reported moderate or severe symptoms of anxiety/depression on the EQ5D-3 L anxiety/depression score. Of those, 615 revisions (45.5%) were performed for less clear reasons for revision (patellar pain, malalignment, instability, progression of osteoarthritis or arthrofibrosis). Not EQ5D-3 L anxiety/depression score, but higher NRS pain at rest and EQ5D-3 L pain score were associated with revision for less clear reason (HR: 1.058, 95% CI 1.019–1.099 & HR: 1.241, 95% CI 1.044–1.476, respectively). ConclusionOur findings suggest that pain intensity is a risk factor for TKA revision for a less clear reason. The finding that preoperative pain intensity was associated with reason for revision confirms a likely influence of subjective, personal factors on offer and acceptance of TKA revision. The association between anxiety/depression and reason for revision after TKA may also be found when including more specific outcome measures to assess anxiety/depression and we therefore hope to encourage further research on this topic with our study, ideally in a prospective setting. Study designLongitudinal Cohort Study Level III, Delphi Consensus

Whole body vibration versus balance training in patients with chronic ankle instability

Background: The ankle is the most often injured joint in athletics. The most frequent kind of ankle injury is a lateral ankle sprain. Whole Body Vibration (WBV) is a unique biophysical technique that generates whole-body vibration impulses for mechanical stimulation. It has been demonstrated in recent years to improve the neurological, muscular, and skeletal systems. Objective: The goal of this study is to assess the effect of systemic vibration and balance training on pain intensity and balance, in CAI patients. Methods: 45 female patients will be enrolled in the research after being recommended by an orthopedic expert for recurrent ankle instability. They will be divided into three equal-sized groups. Group (A) comprises of fifteen patients who will get a six-week exercise program designed specifically for CAI and Whole-Body–Vibration Training (three sessions per week). Group (B) comprises of fifteen patients who will get a six-week, three-session-per-week, conventional exercise program for CAI and balance training. Group (C) consists of fifteen patients who will get a standard exercise plan for CAI. pain; balance and function status of the patients were examined before and after the treatment.

Enhancing Orthopedic Surgery and Treatment Using Artificial Intelligence and Its Application in Health and Dietary Welfare

The current decade has seen an increased usage of high-end digital technologies like machine learning in the field of health care services which enable in supporting and performing different functions with less or no human interventions. The application of machine learning tools in the orthopedic area is gaining more popularity as it can support in analyzing the issues in a more comprehensive manner, provide accurate data, support in forecasting the pattern. It enables offering critical information for taking quick decisions by the medical practitioners in order to enhance the health and dietary care service delivery. The ML tools can support in collecting patient centric data related to orthopedic surgery and also estimate the postoperative complications, level of treatment modalities to be provided, and guide the medical practitioners in taking effective clinical device decisions. The ML approach also supports in providing prediction methods of implementing the ortho surgical outcomes. Furthermore, it can also guide in making better treatment procedures, forecast the patterns, and stream the health care management services for better patient recovery. This study implements a quantitative research approach which will support in sourcing the data from the respondents who are currently working as medical practitioners, orthopedic experts, and radiologists who use ML-based models in making critical decisions related to orthopedic surgery. The researchers chose nearly 149 respondents, and the information was analysed using the IBM SPSS package for gaining critical interpretation. The major analyses cover descriptive analysis, regression analysis, and analysis of variances.