Hasil untuk "Medicine"

N. Watson, M. Badr, G. Belenky et al.

Jonathan H. Chen, S. Asch

C. Krittanawong, Hongju Zhang, Zhen Wang et al.

K. Harmon, J. Drezner, Matthew R. Gammons et al.

Purpose of the statement ▸ To provide an evidence-based, best practises summary to assist physicians with the evaluation and management of sports concussion. ▸ To establish the level of evidence, knowledge gaps and areas requiring additional research. Importance of an AMSSM statement ▸ Sports medicine physicians are frequently involved in the care of patients with sports concussion. ▸ Sports medicine physicians are specifically trained to provide care along the continuum of sports concussion from the acute injury to return-to-play (RTP) decisions. ▸ The care of athletes with sports concussion is ideally performed by healthcare professionals with specific training and experience in the assessment and management of concussion. Competence should be determined by training and experience, not dictated by specialty. ▸ While this statement is directed towards sports medicine physicians, it may also assist other physicians and healthcare professionals in the care of patients with sports concussion. Definition ▸ Concussion is defined as a traumatically induced transient disturbance of brain function and involves a complex pathophysiological process. Concussion is a subset of mild traumatic brain injury (MTBI) which is generally self-limited and at the less-severe end of the brain injury spectrum. Pathophysiology ▸ Animal and human studies support the concept of postconcussive vulnerability, showing that a second blow before the brain has recovered results in worsening metabolic changes within the cell. ▸ Experimental evidence suggests the concussed brain is less responsive to usual neural activation and when premature cognitive or physical activity occurs before complete recovery the brain may be vulnerable to prolonged dysfunction. Incidence ▸ It is estimated that as many as 3.8 million concussions occur in the USA per year during competitive sports and recreational activities; however, as many as 50% of the concussions may go unreported. ▸ Concussions occur in all sports with the highest incidence in football, hockey, rugby, soccer and basketball. Risk factors for sport-related concussion ▸ A history of concussion is associated with a higher risk of sustaining another concussion. ▸ A greater number, severity and duration of symptoms after a concussion are predictors of a prolonged recovery. ▸ In sports with similar playing rules, the reported incidence of concussion is higher in female athletes than in male athletes. ▸ Certain sports, positions and individual playing styles have a greater risk of concussion. ▸ Youth athletes may have a more prolonged recovery and are more susceptible to a concussion accompanied by a catastrophic injury. ▸ Preinjury mood disorders, learning disorders, attention-deficit disorders (ADD/ADHD) and migraine headaches complicate diagnosis and management of a concussion. Diagnosis of concussion ▸ Concussion remains a clinical diagnosis ideally made by a healthcare provider familiar with the athlete and knowledgeable in the recognition and evaluation of concussion. ▸ Graded symptom checklists provide an objective tool for assessing a variety of symptoms related to concussions, while also tracking the severity of those symptoms over serial evaluations. ▸ Standardised assessment tools provide a helpful structure for the evaluation of concussion, although limited validation of these assessment tools is available. ‘Sideline’ evaluation and management ▸ Any athlete suspected of having a concussion should be stopped from playing and assessed by a licenced healthcare provider trained in the evaluation and management of concussions. ▸ Recognition and initial assessment of a concussion should be guided by a symptoms checklist, cognitive evaluation (including orientation, past and immediate memory, new learning and concentration), balance tests and further neurological physical examination. ▸ While standardised sideline tests are a useful framework for examination, the sensitivity, specificity, validity and reliability of these tests among different age groups, cultural groups and settings is largely undefined. Their practical usefulness with or without an individual baseline test is also largely unknown. ▸ Balance disturbance is a specific indicator of a concussion, but not very sensitive. Balance testing on the sideline may be substantially different than baseline tests because of differences in shoe/cleat-type or surface, use of ankle tape or braces, or the presence of other lower extremity injury. ▸ Imaging is reserved for athletes where intracerebral bleeding is suspected. ▸ There is no same day RTP for an athlete diagnosed with a concussion. ▸ Athletes suspected or diagnosed with a concussion should be monitored for deteriorating physical or mental status. Neuropsychological testing ▸ Neuropsychological (NP) tests are an objective measure of brain–behaviour relationships and are more sensitive for subtle cognitive impairment than clinical exam. ▸ Most concussions can be managed appropriately without the use of NP testing. ▸ Computerised neuropsychological (CNP) testing should be interpreted by healthcare professionals trained and familiar with the type of test and the individual test limitations, including a knowledgeable assessment of the reliable change index, baseline variability and false-positive and false-negative rates. ▸ Paper and pencil NP tests can be more comprehensive, test different domains and assess for other conditions which may masquerade as or complicate assessment of concussion. ▸ NP testing should be used only as part of a comprehensive concussion management strategy and should not be used in isolation. ▸ The ideal timing, frequency and type of NP testing have not been determined. ▸ In some cases, properly administered and interpreted NP testing provides an added value to assess cognitive function and recovery in the management of sports concussions. ▸ It is unknown if use of NP testing in the management of sports concussion helps prevent recurrent concussion, catastrophic injury or long-term complications. ▸ Comprehensive NP evaluation is helpful in the post-concussion management of athletes with persistent symptoms or complicated courses. Return to class ▸ Students will require cognitive rest and may require academic accommodations such as reduced workload and extended time for tests while recovering from a concussion. Return to play ▸ Concussion symptoms should be resolved before returning to exercise. ▸ A RTP progression involves a gradual, step-wise increase in physical demands, sports-specific activities and the risk for contact. ▸ If symptoms occur with activity, the progression should be halted and restarted at the preceding symptom-free step. ▸ RTP after concussion should occur only with medical clearance from a licenced healthcare provider trained in the evaluation and management of concussions. Short-term risks of premature RTP ▸ The primary concern with early RTP is decreased reaction time leading to an increased risk of a repeat concussion or other injury and prolongation of symptoms. Long-term effects ▸ There is an increasing concern that head impact exposure and recurrent concussions contribute to long-term neurological sequelae. ▸ Some studies have suggested an association between prior concussions and chronic cognitive dysfunction. Large-scale epidemiological studies are needed to more clearly define risk factors and causation of any long-term neurological impairment. Disqualification from sport ▸ There are no evidence-based guidelines for disqualifying/retiring an athlete from a sport after a concussion. Each case should be carefully deliberated and an individualised approach to determining disqualification taken. Education ▸ Greater efforts are needed to educate involved parties, including athletes, parents, coaches, officials, school administrators and healthcare providers to improve concussion recognition, management and prevention. ▸ Physicians should be prepared to provide counselling regarding potential long-term consequences of a concussion and recurrent concussions. Prevention ▸ Primary prevention of some injuries may be possible with modification and enforcement of the rules and fair play. ▸ Helmets, both hard (football, lacrosse and hockey) and soft (soccer, rugby) are best suited to prevent impact injuries (fracture, bleeding, laceration, etc.) but have not been shown to reduce the incidence and severity of concussions. ▸ There is no current evidence that mouth guards can reduce the severity of or prevent concussions. ▸ Secondary prevention may be possible by appropriate RTP management. Legislation ▸ Legislative efforts provide a uniform standard for scholastic and non-scholastic sports organisations regarding concussion safety and management. Future directions ▸ Additional research is needed to validate current assessment tools, delineate the role of NP testing and improve identification of those at risk of prolonged post-concussive symptoms or other long-term complications. ▸ Evolving technologies for the diagnosis of concussion, such as newer neuroimaging techniques or biological markers, may provide new insights into the evaluation and management of sports concussion.

G. Handelman, H. Kok, R. Chandra et al.

Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer‐aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML, explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.

B. Djulbegovic, G. Guyatt

L. Zhang, F. Gu, Juliana M. Chan et al.

L. Goetz, N. Schork

There is a great deal of hype surrounding the concept of personalized medicine. Personalized medicine is rooted in the belief that since individuals possess nuanced and unique characteristics at the molecular, physiological, environmental exposure, and behavioral levels, they may need to have interventions provided to them for diseases they possess that are tailored to these nuanced and unique characteristics. This belief has been verified to some degree through the application of emerging technologies such as DNA sequencing, proteomics, imaging protocols, and wireless health monitoring devices, which have revealed great inter-individual variation in disease processes. In this review, we consider the motivation for personalized medicine, its historical precedents, the emerging technologies that are enabling it, some recent experiences including successes and setbacks, ways of vetting and deploying personalized medicines, and future directions, including potential ways of treating individuals with fertility and sterility issues. We also consider current limitations of personalized medicine. We ultimately argue that since aspects of personalized medicine are rooted in biological realities, personalized medicine practices in certain contexts are likely to be inevitable, especially as relevant assays and deployment strategies become more efficient and cost-effective.

E. Vayena, A. Blasimme, I. Cohen

Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.

J. Gimble, A. Katz, B. Bunnell

A. Davis, J. Carcillo, R. Aneja et al.

T. Horlocker, E. Vandermeuelen, S. Kopp et al.

(Reg Anesth Pain Med. 2018;43:263–309)The American Society of Regional Anesthesia and Pain Medicine (ASRA) convened its Fourth Consensus Conference on Regional Anesthesia and Anticoagulation in conjunction with the European Society of Anesthesiology (ESA) in response to emerging patient safety issue

Eric J. Cassell

M. Weinstein, J. Siegel, M. Gold et al.

R. Samsonraj, M. Raghunath, V. Nurcombe et al.

Mesenchymal stem cells (MSC) hold great potential for regenerative medicine because of their ability for self‐renewal and differentiation into tissue‐specific cells such as osteoblasts, chondrocytes, and adipocytes. MSCs orchestrate tissue development, maintenance and repair, and are useful for musculoskeletal regenerative therapies to treat age‐related orthopedic degenerative diseases and other clinical conditions. Importantly, MSCs produce secretory factors that play critical roles in tissue repair that support both engraftment and trophic functions (autocrine and paracrine). The development of uniform protocols for both preparation and characterization of MSCs, including standardized functional assays for evaluation of their biological potential, are critical factors contributing to their clinical utility. Quality control and release criteria for MSCs should include cell surface markers, differentiation potential, and other essential cell parameters. For example, cell surface marker profiles (surfactome), bone‐forming capacities in ectopic and orthotopic models, as well as cell size and granularity, telomere length, senescence status, trophic factor secretion (secretome), and immunomodulation, should be thoroughly assessed to predict MSC utility for regenerative medicine. We propose that these and other functionalities of MSCs should be characterized prior to use in clinical applications as part of comprehensive and uniform guidelines and release criteria for their clinical‐grade production to achieve predictably favorable treatment outcomes for stem cell therapy. Stem Cells Translational Medicine 2017;6:2173–2185

G. Ginsburg, K. Phillips

Bowen Yang, Yu Chen, Jianlin Shi

Catalysis and medicine are often considered as two independent research fields with their own respective scientific phenomena. Promoted by recent advances in nanochemistry, large numbers of nanocatalysts, such as nanozymes, photocatalysts, and electrocatalysts, have been applied in vivo to initiate catalytic reactions and modulate biological microenvironments for generating therapeutic effects. The rapid growth of research in biomedical applications of nanocatalysts has led to the concept of “nanocatalytic medicine,” which is expected to promote the further advance of such a subdiscipline in nanomedicine. The high efficiency and selectivity of catalysis that chemists strived to achieve in the past century can be ingeniously translated into high efficacy and mitigated side effects in theranostics by using “nanocatalytic medicine” to steer catalytic reactions for optimized therapeutic outcomes. Here, the rationale behind the construction of nanocatalytic medicine is eludicated based on the essential reaction factors of catalytic reactions (catalysts, energy input, and reactant). Recent advances in this burgeoning field are then comprehensively presented and the mechanisms by which catalytic nanosystems are conferred with theranostic functions are discussed in detail. It is believed that such an emerging catalytic therapeutic modality will play a more important role in the field of nanomedicine.

S. MacEachern, N. Forkert

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multimodal or 'multi-omics' data from an individual to make patient-tailored decisions. With the large and complex datasets generated using precision medicine diagnostic approaches, novel techniques to process and understand these complex data were needed. At the same time, computer science has progressed rapidly to develop techniques that enable the storage, processing, and analysis of these complex datasets, a feat that traditional statistics and early computing technologies could not accomplish. Machine learning, a branch of artificial intelligence, is a computer science methodology that aims to identify complex patterns in data that can be used to make predictions or classifications on new unseen data or for advanced exploratory data analysis. Machine learning analysis of precision medicine's multimodal data allows for broad analysis of large datasets and ultimately a greater understanding of human health and disease. This review focuses on machine learning utilization for precision medicine's "big data", in the context of genetics, genomics, and beyond.

Jennifer E. Rood, Aidan Maartens, A. Hupalowska et al.

M. A. Alghamdi, A. N. Fallica, N. Virzì et al.

Both personalized medicine and nanomedicine are new to medical practice. Nanomedicine is an application of the advances of nanotechnology in medicine and is being integrated into diagnostic and therapeutic tools to manage an array of medical conditions. On the other hand, personalized medicine, which is also referred to as precision medicine, is a novel concept that aims to individualize/customize therapeutic management based on the personal attributes of the patient to overcome blanket treatment that is only efficient in a subset of patients, leaving others with either ineffective treatment or treatment that results in significant toxicity. Novel nanomedicines have been employed in the treatment of several diseases, which can be adapted to each patient-specific case according to their genetic profiles. In this review, we discuss both areas and the intersection between the two emerging scientific domains. The review focuses on the current situation in personalized medicine, the advantages that can be offered by nanomedicine to personalized medicine, and the application of nanoconstructs in the diagnosis of genetic variability that can identify the right drug for the right patient. Finally, we touch upon the challenges in both fields towards the translation of nano-personalized medicine.