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The supraspinatus tendon is one of the most involved tendons in the development of shoulder pain. Extracorporeal shockwave therapy (ESWT) has been recognized as a valid and safe treatment. Sometimes the symptoms cannot be relieved, or a relapse develops, affecting the patient's quality of life. Therefore, a prediction protocol could be a powerful tool aiding our clinical decisions. An artificial neural network was run, in particular a multilayer perceptron model incorporating input information such as the VAS and Constant-Murley score, administered at T0 and at T1 after six months. It showed a model sensitivity of 80.7%, and the area under the ROC curve was 0.701, which demonstrates good discrimination. The aim of our study was to identify predictive factors for minimal clinically successful therapy (MCST), defined as a reduction of ≥40% in VAS score at T1 following ESWT for chronic non-calcific supraspinatus tendinopathy (SNCCT). From the male gender, we expect greater and more frequent clinical success. The more severe the patient's initial condition, the greater the possibility that clinical success will decrease. The Constant and Murley score, Roles and Maudsley score, and VAS are not just evaluation tools to verify an improvement; they are also prognostic factors to be taken into consideration in the assessment of achieving clinical success. Due to the lower clinical improvement observed in older patients and those with worse clinical and functional scales, it would be preferable to also provide these patients with the possibility of combined treatments. The ANN predictive model is reasonable and accurate in studying the influence of prognostic factors and achieving clinical success in patients with chronic non-calcific tendinopathy of the supraspinatus treated with ESWT.
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Pain represents a common symptom of several diseases and is often associated with a reduction in rehabilitation outcomes and recovery. The effectiveness of pain alleviation by botulinum toxin has been recently demonstrated. We searched in PubMed the papers about this topic published in the last ten years, and we selected clinical trials, guidelines, meta-analyses, reviews, and systematic reviews. We used different approaches: multiperspective presentation, lexical evaluation, and systematic review. The systematic review was only performed for the randomized controlled trials. We predominantly found reviews and trials about the rehabilitation of stroke/brain injury and epicondylitis. The most common outcome measures were pain, function, and spasticity. Among the common words, pain was the most frequent and the terms were grouped into different families, especially concerning the outcomes. Rehabilitation showed a relatively low frequency. Finally, the systematic review showed moderate-low levels of bias which confirms the effectiveness of botulinum toxin for pain treatment. The current literature about botulinum toxin is wide and globally diffuse but with some limitations in study strategies and clearness in the formal presentation. The evidence justifies the use of botulinum toxin in treating pain in different diseases.
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Rehabilitation after rotator cuff repair is crucial for functional recovery and for minimizing the risk of retear. There are two rehabilitation protocols (early and traditional) and the debate about which is the best is open. This umbrella review aimed to compare the effect of these rehabilitation protocols in terms of reduction in pain, functional recovery, and retear risk. We selected systematic reviews and meta-analyses published between 2012 and 2022 dealing with the aim. Nineteen systematic reviews were included. No significant differences were found between early and traditional protocols in terms of pain reduction. Early rehabilitation provided better short-term results regarding Range of Motion improvement, but long-term functional outcomes were similar. Retear risk remains a significant concern for the early protocol. We found major differences between the analyzed protocols. This review suggests that both protocols are useful to recover global shoulder function, but the standard protocol has a greater safety profile for larger tears. On the other hand, the early protocol may be preferable for smaller lesions, allowing a faster recovery and having less impact on medical costs. Further research is needed to identify optimal rehabilitation strategies tailored to the individual patient's needs and characteristics.
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The knee is an essential part of our body, and identifying its injuries is crucial since it can significantly affect quality of life. To date, the preferred way of evaluating knee injuries is through magnetic resonance imaging (MRI), which is an effective imaging technique that accurately identifies injuries. The issue with this method is that the high amount of detail that comes with MRIs is challenging to interpret and time consuming for radiologists to analyze. The issue becomes even more concerning when radiologists are required to analyze a significant number of MRIs in a short period. For this purpose, automated tools may become helpful to radiologists assisting them in the evaluation of these images. Machine learning methods, in being able to extract meaningful information from data, such as images or any other type of data, are promising for modeling the complex patterns of knee MRI and relating it to its interpretation. In this study, using a real-life imaging protocol, a machine-learning model based on convolutional neural networks used for detecting medial meniscus tears, bone marrow edema, and general abnormalities on knee MRI exams is presented. Furthermore, the model's effectiveness in terms of accuracy, sensitivity, and specificity is evaluated. Based on this evaluation protocol, the explored models reach a maximum accuracy of 83.7%, a maximum sensitivity of 82.2%, and a maximum specificity of 87.99% for meniscus tears. For bone marrow edema, a maximum accuracy of 81.3%, a maximum sensitivity of 93.3%, and a maximum specificity of 78.6% is reached. Finally, for general abnormalities, the explored models reach 83.7%, 90.0% and 84.2% of maximum accuracy, sensitivity and specificity, respectively.
Asunto(s)
Traumatismos de la Rodilla , Calidad de Vida , Humanos , Traumatismos de la Rodilla/diagnóstico por imagen , Traumatismos de la Rodilla/patología , Imagen por Resonancia Magnética/métodos , Articulación de la Rodilla/diagnóstico por imagen , Articulación de la Rodilla/patología , Sensibilidad y Especificidad , Aprendizaje AutomáticoRESUMEN
BACKGROUND: Magnetic Resonance Imaging (MRI) and Ultrasound (US) in combination with clinical data could contribute to the diagnosis, staging and follow-up of Patello-Femoral Syndrome (PFS), which often overlaps with other pathologies of the knee. PURPOSE OF THE STUDY: To evaluate the diagnostic role of MRI and US findings associated with PFS and define the range values of instrumental measurements obtained in pathological cases and healthy controls, the performance of the two methods in comparison, and the correlation with clinical data. MATERIALS AND METHODS: 100 subjects were examined: 60 patients with a high suspicion of PFS at the clinical evaluation and 40 healthy controls. All measurements obtained by MRI and US examination were correlated with clinical data. A descriptive analysis of all measurements was stratified for pathological cases and healthy controls. A Student's t-test for continuous variables was used to compare patients to controls and US to MRI. Logistic regression analysis was applied to test the correlation between MRI and US measurements with clinical data. RESULTS: Statistical descriptive analysis determined the MRI and US range values of medial patello-femoral distance and the thickness of retinacles and cartilages in pathological cases and healthy controls. In pathological cases, the retinacle results of both increased; the medial appeared to be slightly more increased than the lateral. Furthermore, in some cases, the thickness of the cartilage decreased in both techniques; the medial cartilage was more thinned than the lateral. According to logistic regression analyses, the best diagnostic parameter was the medial patello-femoral distance due to the overlapping results of the US and MRI. Furthermore, all clinical data obtained by different tests showed a good correlation with patello-femoral distance. In particular, the correlation between medial patello-femoral distance and the VAS score is direct and equal to 97-99%, which is statistically significant (p < 0.001), and the correlation with the KOOS score is inverse and equal to 96-98%, which is statistically significant. CONCLUSIONS: MRI and Ultrasound examination in combination with clinical data demonstrated high-value results in the diagnosis of PFS.
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BACKGROUND: Cervical spine manipulations (CSM) have been performed for centuries and are a widely practiced intervention to manage cervical spine musculoskeletal disorders. We aimed to perform an overview of the literature concerning the effects and the adverse events of CSM in the Physical and Rehabilitation Medicine (PRM) field with a forensic medicine perspective. METHODS: A search in the scientific literature (PubMed, Google Scholar, PEDro and Cochrane) was carried out from inception until October 2020. RESULTS: Fourteen articles were included in this narrative summary. The possible development of side effects requires a careful mandatory balance of benefits and risks even when there is an indication for this approach. Moreover, a qualified professional is essential to perform CSM-a non-invasive therapeutic procedure that can be potentially harmful. CONCLUSIONS: In conclusion, it is essential to perform the diagnosis, to treat, and to manage complications within the PRM field, both for the reduction of malpractice claims and, most importantly, for the safety of the patient.
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Knee osteoarthritis is one of the leading causes of chronic disability worldwide and is a significant social and economic burden on healthcare systems; hence it has become essential to develop methods to identify patients at risk for developing knee osteoarthritis at an early stage. Standard morphological MRI sequences are focused mostly on alterations seen in advanced stages of osteoarthritis. However, they possess low sensitivity for early, subtle, and potentially reversible changes of the degenerative process. In this review, we have summarized the state of the art with regard to innovative quantitative MRI techniques that exploit objective and quantifiable biomarkers to identify subtle alterations that occur in early stages of osteoarthritis in knee cartilage before any morphological alteration occurs and to capture potential effects on the brain. These novel MRI imaging tools are believed to have great potential for improving the current standard of care, but further research is needed to address limitations before these compositional techniques can be robustly applied in research and clinical settings.