Behavior, in its broadest definition, can be defined as the motor manifestation of physiologic processes. As such, all behaviors manifest through the motor system. In the fields of neuroscience and orthopedics, locomotion is a commonly evaluated behavior for a variety of disease models. For example, locomotor recovery after traumatic injury to the nervous system is one of the most commonly evaluated behaviors [1][2][3] . Though locomotion can be evaluated using a variety of endpoint measurements (e.g. time taken to complete a locomotor task, etc), semiquantitative kinematic measures (e.g. ordinal rating scales (e.g. Basso Beattie and Bresnahan locomotor (BBB) rating scale, etc)) and surrogate measures of behaviour (e.g. muscle force, nerve conduction velocity, etc), only kinetics (force measurements) and kinematics (measurements of body segments in space) provide a detailed description of the strategy by which an animal is able to locomote 1 . Though not new, kinematic and kinetic measurements of locomoting rodents is now more readily accessible due to the availability of commercially available equipment designed for this purpose. Importantly, however, experimenters need to be very familiar with theory of biomechanical analyses and understand the benefits and limitations of these forms of analyses prior to embarking on what will become a relatively labor-intensive study. The present paper aims to describe a method for collecting kinematic and ground reaction force data using commercially available equipment. Details of equipment and apparatus set-up, pre-training of animals, inclusion and exclusion criteria of acceptable runs, and methods for collecting the data are described. We illustrate the utility of this behavioral analysis technique by describing the kinematics and kinetics of strain-matched young adult, middleaged, and geriatric rats.
IntroductionAlthough simulation-based training is increasingly used for medical education, its benefits in continuing medical education (CME) are less established. This study seeks to evaluate the feasibility of incorporating simulation-based training into a CME conference and compare its effectiveness with the traditional workshop in improving knowledge and self-reported confidence.MethodsParticipants (N=27) were group randomized to either a simulation-based workshop or a traditional case-based workshop.ResultsPost-training, knowledge assessment score neither did increase significantly in the traditional group (d=0.13; p=0.76) nor did significantly decrease in the simulation group (d= − 0.44; p=0.19). Self-reported comfort in patient assessment parameters increased in both groups (p<0.05 in all). However, only the simulation group reported an increase in comfort in patient management (d=1.1, p=0.051 for the traditional group and d=1.3; p= 0.0003 for the simulation group). At 1 month, comfort measures in the traditional group increased consistently over time while these measures in the simulation group increased post-workshop but decreased by 1 month, suggesting that some of the effects of training with simulation may be short lived.DiscussionThe use of simulation-based training was not associated with benefits in knowledge acquisition, knowledge retention, or comfort in patient assessment. It was associated with superior outcomes in comfort in patient management, but this benefit may be short-lived. Further studies are required to better define the conditions under which simulation-based training is beneficial.
Background The evolving COVID-19 pandemic has and continues to present a threat to health system capacity. Rapidly expanding an existing acute care physician workforce is critical to pandemic response planning in large urban academic health systems. Intervention The Medical Emergency-Pandemic Operations Command (MEOC)—a multi-specialty team of physicians, operational leaders, and support staff within an academic Department of Medicine in Calgary, Canada—partnered with its provincial health system to rapidly develop a comprehensive, scalable pandemic physician workforce plan for non-ventilated inpatients with COVID-19 across multiple hospitals. The MEOC Pandemic Plan comprised seven components, each with unique structure and processes. Methods In this manuscript, we describe MEOC’s Pandemic Plan that was designed and implemented from March to May 2020 and re-escalated in October 2020. We report on the plan’s structure and process, early implementation outcomes, and unforeseen challenges. Data sources included MEOC documents, health system, public health, and physician engagement implementation data. Key Results From March 5 to October 26, 2020, 427 patients were admitted to COVID-19 units in Calgary hospitals. In the initial implementation period (March–May 2020), MEOC communications reached over 2500 physicians, leading to 1446 physicians volunteering to provide care on COVID-19 units. Of these, 234 physicians signed up for hospital shifts, and 227 physicians received in-person personal protective equipment simulation training. Ninety-three physicians were deployed on COVID-19 units at four large acute care hospitals. The resurgence of cases in September 2020 has prompted re-escalation including re-activation of COVID-19 units. Conclusions MEOC leveraged an academic health system partnership to rapidly design, implement, and refine a comprehensive, scalable COVID-19 acute care physician workforce plan whose components are readily applicable across jurisdictions or healthcare crises. This description may guide other institutions responding to COVID-19 and future health emergencies.
Pleural effusions are a common finding in many clinical settings and have important diagnostic and therapeutic implications. They may be identified by physical exam, chest radiography, chest computerized tomography (CT) scans or point of care ultrasonography (POCUS). The use of POCUS for the diagnosis and management of pleural effusions offers several advantages relevant to the practice of the general internist. For the diagnosis of pleural effusion, POCUS has superior sensitivity and specificity when compared to chest radiography and physical exam. Abnormal sonographic features of the pleural fluid and the adjacent pleura may suggest the presence of an exudative or malignant effusion. POCUS can be used to quickly estimate the size of a pleural effusion. Lastly, the use of ultrasound guidance when performing a thoracentesis reduces the risk of pneumothorax and hemorrhage.
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