142 research outputs found

    Terminologia Anatomica; Considered from the Perspective of Next-Generation Knowledge Sources

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    This report examines the semantic structure of Terminologia Anatomica, taking one randomly selected page as an example. The focus of analysis is the meaning imparted to an anatomical term by virtue of its location within the structured list. Terminologia’s structure expressed through hierarchies of headings, varied typographical styles, indentations and an alphanumeric code implies specific relationships between the terms embedded in the list. Together, terms and relationships can potentially capture essential elements of anatomical knowledge. The analysis focuses on these knowledge elements and evaluates the consistency and logic in their representation. Most critical of these elements are class inclusion and part-whole relationships, which are implied, rather than explicitly modeled by Terminologia. This limits the use of the term list to those who have some knowledge of anatomy and excludes computer programs from navigating through the terminology. Assuring consistency in the explicit representation of anatomical relationships would facilitate adoption of Terminologia as the anatomical standard by the various controlled medical terminology (CMT) projects. These projects are motivated by the need for computerizing the patient record, and their aim is to generate machineunderstandable representations of biomedical concepts, including anatomy. Because of the lack of a consistent and explicit representation of anatomy, each of these CMTs has generated it own anatomy model. None of these models is compatible with each other, yet each is consistent with textbook descriptions of anatomy. The analysis of the semantic structure of Terminologia Anatomica leads to some suggestions for enhancing the term list in ways that would facilitate its adoption as the standard for anatomical knowledge representation in biomedical informatics

    Artificial intelligence extension of the OSCAR-IB criteria

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    Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines

    Skills in Rheumatology

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    This Open Access book presents practical approaches to managing patients affected by various rheumatological diseases, allowing readers to gain a better understanding of the various clinical expressions and problems experienced by these patients. Discussing rheumatology from an organ systems perspective, it highlights the importance ofdetailed musculoskeletal examinations when treating patients affected by rheumatological diseases. The book first explores the latest diagnostic approaches and offers key tips for accurate musculoskeletal examinations before addressing the various treatment modalities, with a particular focus on the most common joints involved in rheumatoid arthritis: the wrists and the metacarpophalangeal joints (2nd and 3rd). Featuring easy-to-understand flow diagrams and explaining the common medical problems associated with rheumatic disease, such as shortness of breath and anemia, it is not only a valuable resource to rheumatologists, but will also appeal to medical students, junior residents, and primary healthcare physicians

    Skills in Rheumatology

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    This Open Access book presents practical approaches to managing patients affected by various rheumatological diseases, allowing readers to gain a better understanding of the various clinical expressions and problems experienced by these patients. Discussing rheumatology from an organ systems perspective, it highlights the importance ofdetailed musculoskeletal examinations when treating patients affected by rheumatological diseases. The book first explores the latest diagnostic approaches and offers key tips for accurate musculoskeletal examinations before addressing the various treatment modalities, with a particular focus on the most common joints involved in rheumatoid arthritis: the wrists and the metacarpophalangeal joints (2nd and 3rd). Featuring easy-to-understand flow diagrams and explaining the common medical problems associated with rheumatic disease, such as shortness of breath and anemia, it is not only a valuable resource to rheumatologists, but will also appeal to medical students, junior residents, and primary healthcare physicians

    Contextual factors, placebo and nocebo effects in physical therapy: clinical relevance and impact on research

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    A brief overview on placebo and nocebo effects Placebo and nocebo effects represent one of the most fascinating topics in the healthcare field. They represent complex and distinct psychoneurobiological phenomena where behavioural and neurophysiological changes occur during an interaction between the patient and the healthcare context (1). Placebo effects (Latin \u201cI shall please\u201d) are produced by a psychosocial context that is capable of positively affecting the patient's brain and therapeutic outcomes (2-4). On the contrary, nocebo effects (Latin \u201cI shall harm\u201d) are consequences of the negative perception of the ritual and therapeutic act on the patient's mind and body, so much so that it generates unwanted effects and side effects (5-7). Throughout the history of medicine, placebo and nocebo have been traditionally viewed as bothersome variables to check for in a clinical trial. In the last four decades, in light of some significant clinical and laboratory findings, they have become a source of research interest. Indeed, placebo and nocebo have been adopted as a conceptual model to examine the body-mind interaction and the human body systems, exploring their connection with different systems, mechanisms, diseases and therapeutic interventions (8, 9). In particular, placebo and nocebo effects have been studied in mood (10), cardiovascular, respiratory (11), gastrointestinal (12, 13), motor (14), immune and endocrine (15), and pain systems (16-18). Clinically, not all improvement or aggravation of patients\u2019 symptoms is due to placebo and nocebo effects. It is necessary to rule out the patients\u2019 modifications created by placebo and nocebo effects from the changes of outcomes related to other confounding elements. The elements which could create misinterpretations of the patients\u2019 clinical picture are: the spontaneous remission of the disease and symptom fluctuation (also called the natural history), the regression to the mean (a statistical phenomenon caused by selection biases), the patient\u2019s and clinician\u2019s biases during the reports of clinical conditions, and unidentified effects of concomitant co-interventions (8, 9). Different psychoneurobiological findings allowed the scientific community to begin to understand the underlying mechanisms of placebo and nocebo effects. From a theoretical perspective, two main psychological subjective constructs have been suggested to explain how placebo or nocebo effects act: the expectation and the conditioning. The social learning, reward, anxiety reduction, desire, motivation, memory, somatic focus, genetic and personality traits also represent alternative theories (19-25). \u201cAlternative\u201d however does not mean that these psychological mechanisms are mutually exclusive: they can interact simultaneously (26). Regarding the actual findings, placebo and nocebo interact with the brain modulatory systems at a neurochemical level, through the release of specific neurotransmitters. For instance, considering pain outcome as a model, the endogenous opioids, dopamine, cannabinoids, oxytocin and vasopressin are involved in placebo analgesia, while cholecystokinin, dopamine, opioid deactivation and cyclooxygenaseprostaglandins activation are implicated in nocebo hyperalgesia (27-29). Furthermore, recent advances in neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), suggest an involvement of specific neural correlates during placebo and nocebo effects, mainly the pain one. In fact, placebo and nocebo are able to activate or deactivate the four key brain regions commonly associated with the descending pain processing pathway: the dorsolateral prefrontal cortex, the rostral anterior cingulate cortex, the periaqueductal gray and the dorsal horn of spine (16). Nevertheless, they represent only a part of brain areas showing a change in their activity during placebo or nocebo (30-32). Therefore, the previously described evidence suggests that placebo and nocebo effects are concrete and genuine phenomena, triggered by different contexts, and capable of impacting the patients\u2019 brain. It is necessary to define what the context is, and why its parts are important from a clinical perspective (33). The healthcare context as a trigger of placebo and nocebo effects In 1955 Balint described the context as the \u201cwhole atmosphere around the therapy\u201d (34). The context is not a vacuum, but it embodies a healing space composed by internal, external and relational elements capable of interacting with the patient\u2019s disease (35). The internal elements consist of memories, emotions, expectations and psychological characteristics of the patient. The external elements include the physical aspects of therapy, such as the kind of treatment (pharmacological or manual) and the place in which the treatment is delivered. Relational elements are represented by all the social cues that characterize the patient-clinician relationship, such as the verbal information that the clinicians give to the patient, the communication style or the body language (36). In 2001, Di Blasi et al. defined these elements as \u201ccontextual factors\u201d. These factors have been grouped, from a clinical practice point of view, in five categories: a) clinician features, b) patient features, c) patient-clinician relationship, d) intervention features, and e) healthcare setting features (37). As a whole, contextual factors constitute the therapeutic ritual and healing symbols surrounding the patient-clinician encounter, capable of producing changes in the patient at perceptual, neurophysiological and cognitive levels (38). Indeed, contextual factors convey a hidden meaning, actively detected and analysed by the patient, which is essential for the perception of care and the interpretation of the therapeutic intervention (39, 40). When these contextual stimuli and cues are filtered by the patient\u2019s perspective and mind-set (41), they are translated into a complex cascade of psycho-neuroimmunoendocrine events, thus triggering placebo and nocebo effects and influencing the course of illness (42, 43). From a clinical perspective, the contextual factors pervade every healthcare action (history taking, physical examination, therapy and prognosis) and directly affect the quality of the health-related outcome (44-46). A positive context, that is characterized by the presence of positive contextual factors, can improve therapeutic outcome by producing placebo effects, while a negative context, characterized by the presence of negative contextual factors, can aggravate therapeutic outcome by creating nocebo effects(47, 48). For example, during the same treatment delivery (e.g. painkillers), the use of positive verbal suggestion (e.g. \u201cThis therapy will help you and it will decrease pain\u201d) can improve musculoskeletal pain, while the adoption of verbal suggestion of uncertainty (e.g. \u201cThis therapy could help you and sometimes it decrease pain\u201d) can aggravate patient\u2019s pain (49). The presented studies offer a starting point for reflection about the role of the contextual factors surrounding the administration of a healthcare treatment: they can be a source of improvement of the efficacy of the therapy or implicated in the manifestation of adverse effects. The logical consequence is to wonder whether context, placebo and nocebo effects have been taken into consideration in a specific healthcare field, such as physical therapy. The link between placebo, nocebo effects and physical therapy Throughout the history of physical therapy and rehabilitation, placebo and nocebo effects have been considered as problematic phenomena for two main reasons. From a research point of view, they have represented confounding factors capable of limiting the internal validity of the study design and reducing the external validity of the findings (50). From a clinical point of view, they have embodied troublesome and nonspecific variables able to attenuate the therapeutic role of specific therapies such as massage, joint mobilization and therapeutic exercise (51, 52). As a consequence, for many years the role of placebo and nocebo effects was debated worldwide by clinicians and researchers (53-55). At the end of the first decade of the twenty-first century the scientific community began to investigate the mechanisms of action of joint, soft tissue and neural therapeutic intervention, consequently revaluing the role of placebo and nocebo effects in physiotherapy (56). Recent studies have suggested a mechanical and neurophysiological mechanism (peripheral, spinal and supraspinal) linked to the therapeutic strategies adopted by physical therapists (57). Among the supraspinal mechanisms, the placebo and nocebo effects have assumed an important top-down role in inducing changes in patient\u2019s symptoms (58), thus becoming elements that clinicians should adopt in clinical practice (59). Recently, also the context in which interventions are delivered has been suggested as a moderator of clinical effects (60). A new line of research has indicated the context as responsible for a larger non-specific component of treatment efficacy in physical therapy (61). Despite these promising advances, the following issues remain unexplored: 1) What are the contextual factors? 2) How can the contextual factors trigger placebo and nocebo effects? 3) Which therapeutic outcomes can be influenced by the contextual factors? 4) Are the physical therapists aware of the use of contextual factors in clinical practice? 5) What is the role of contextual factors in research? General organization of the research project The main goal of this PhD research project is to investigate the relevance of the contextual factors as triggers of placebo/nocebo effects and their impact on therapeutic outcomes in physiotherapy. Different studies were conducted during the 3-year period of PhD training (2015-2018). The results, relative discussions and implications are reported in the chapters of the present dissertation as follows: \u2022 Chapter I: a conceptual model regarding the role of the contextual factors as triggers of placebo, nocebo responses and influencers of physical therapy outcomes; \u2022 Chapter II: the model of contextual factors regarding musculoskeletal pain, which is a common outcome encountered by physical therapists; \u2022 Chapter III: the link between the determinants of patient satisfaction in outpatient musculoskeletal physiotherapy clinics and the contextual factors; \u2022 Chapter IV: the knowledge, attitude and behaviour of Italian physiotherapists specialized in manual therapy towards contextual factors; \u2022 Chapter V: the translational value of contextual factors and their relevance for physical therapy research

    Washington University Record, November 13, 1997

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    https://digitalcommons.wustl.edu/record/1775/thumbnail.jp

    Unveiling healthcare data archiving: Exploring the role of artificial intelligence in medical image analysis

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    Gli archivi sanitari digitali possono essere considerati dei moderni database progettati per immagazzinare e gestire ingenti quantità di informazioni mediche, dalle cartelle cliniche dei pazienti, a studi clinici fino alle immagini mediche e a dati genomici. I dati strutturati e non strutturati che compongono gli archivi sanitari sono oggetto di scrupolose e rigorose procedure di validazione per garantire accuratezza, affidabilità e standardizzazione a fini clinici e di ricerca. Nel contesto di un settore sanitario in continua e rapida evoluzione, l’intelligenza artificiale (IA) si propone come una forza trasformativa, capace di riformare gli archivi sanitari digitali migliorando la gestione, l’analisi e il recupero di vasti set di dati clinici, al fine di ottenere decisioni cliniche più informate e ripetibili, interventi tempestivi e risultati migliorati per i pazienti. Tra i diversi dati archiviati, la gestione e l’analisi delle immagini mediche in archivi digitali presentano numerose sfide dovute all’eterogeneità dei dati, alla variabilità della qualità delle immagini, nonché alla mancanza di annotazioni. L’impiego di soluzioni basate sull’IA può aiutare a risolvere efficacemente queste problematiche, migliorando l’accuratezza dell’analisi delle immagini, standardizzando la qualità dei dati e facilitando la generazione di annotazioni dettagliate. Questa tesi ha lo scopo di utilizzare algoritmi di IA per l’analisi di immagini mediche depositate in archivi sanitari digitali. Il presente lavoro propone di indagare varie tecniche di imaging medico, ognuna delle quali è caratterizzata da uno specifico dominio di applicazione e presenta quindi un insieme unico di sfide, requisiti e potenziali esiti. In particolare, in questo lavoro di tesi sarà oggetto di approfondimento l’assistenza diagnostica degli algoritmi di IA per tre diverse tecniche di imaging, in specifici scenari clinici: i) Immagini endoscopiche ottenute durante esami di laringoscopia; ciò include un’esplorazione approfondita di tecniche come la detection di keypoints per la stima della motilità delle corde vocali e la segmentazione di tumori del tratto aerodigestivo superiore; ii) Immagini di risonanza magnetica per la segmentazione dei dischi intervertebrali, per la diagnosi e il trattamento di malattie spinali, così come per lo svolgimento di interventi chirurgici guidati da immagini; iii) Immagini ecografiche in ambito reumatologico, per la valutazione della sindrome del tunnel carpale attraverso la segmentazione del nervo mediano. Le metodologie esposte in questo lavoro evidenziano l’efficacia degli algoritmi di IA nell’analizzare immagini mediche archiviate. I progressi metodologici ottenuti sottolineano il notevole potenziale dell’IA nel rivelare informazioni implicitamente presenti negli archivi sanitari digitali

    Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

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    Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia Âź; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-ÎșB localization and IÎșB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-ÎșB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-ÎșB and degradation of IÎșB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-ÎșB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes
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