Cardiovascular Risk Assessment after COVID-19 Infection before Resuming Sports Activities - Practical Flowchart and Meta-Analysis

Abstract Background: The risk of sports-related sudden cardiac arrest after COVID-19 infection can be a serious problem. There is an urgent need for evidence-based criteria to ensure patient safety before resuming exercise. Objective: To estimate the pooled prevalence of acute myocardial injury caused by COVID-19 and to provide an easy-to-use cardiovascular risk assessment toolkit prior to resuming sports activities after COVID-19 infection. Methods: We searched the Medline and Cochrane databases for articles on the prevalence of acute myocardial injury associated with COVID-19 infection. The pooled prevalence of acute myocardial injury was calculated for hospitalized patients treated in different settings (non-intensive care unit [ICU], ICU, overall hospitalization, and non-survivors). Statistical significance was accepted for p values <0.05. We propose a practical flowchart to assess the cardiovascular risk of individuals who recovered from COVID-19 before resuming sports activities. Results: A total of 20 studies (6,573 patients) were included. The overall pooled prevalence of acute myocardial injury in hospitalized patients was 21.7% (95% CI 17.3-26.5%). The non-ICU setting had the lowest prevalence (9.5%, 95% CI 1.5-23.4%), followed by the ICU setting (44.9%, 95% CI 27.7-62.8%), and the cohort of non-survivors (57.7% with 95% CI 38.5-75.7%). We provide an approach to assess cardiovascular risk based on the prevalence of acute myocardial injury in each setting. Conclusions: Acute myocardial injury is frequent and associated with more severe disease and hospital admissions. Cardiac involvement could be a potential trigger for exercise-induced clinical complications after COVID-19 infection. We created a toolkit to assist with clinical decision-making prior to resuming sports activities after COVID-19 infection.

Detecting wildlife trafficking in images from online platforms: A test case using deep learning with pangolin images

E-commerce has become a booming market for wildlife trafficking, as online platforms are increasingly more accessible and easier to navigate by sellers, while still lacking adequate supervision. Artificial intelligence models, and specifically deep learning, have been emerging as promising tools for the automated analysis and monitoring of digital online content pertaining to wildlife trade. Here, we used and fine-tuned freely available artificial intelligence models (i.e., convolutional neural networks) to understand the potential of these models to identify instances of wildlife trade. We specifically focused on pangolin species, which are among the most trafficked mammals globally and receiving increasing trade attention since the COVID-19 pandemic. Our convolutional neural networks were trained using online images (available from iNaturalist, Flickr and Google) displaying both traded and non-traded pangolin settings. The trained models showed great performances, being able to identify over 90 % of potential instances of pangolin trade in the considered imagery dataset. These instances included the showcasing of pangolins in popular marketplaces (e.g., wet markets and cages), and the displaying of commonly traded pangolin parts and derivates (e.g., scales) online. Nevertheless, not all instances of pangolin trade could be identified by our models (e.g., in images with dark colours and shaded areas), leaving space for further research developments. The methodological developments and results from this exploratory study represent an advancement in the monitoring of online wildlife trade. Complementing our approach with other forms of online data, such as text, would be a way forward to deliver more robust monitoring tools for online trafficking.

Flexibility of Ballet Dancers in COVID-19 Pandemic: A Prospective Observational Study in Portugal.

The aim of this study was to verify how dancers' flexibility work has developed during confinement through four assessment moments: before, during (two times), and after the lockdown period. The sample was formed by 18 dancers from the Porto Dance Conservatory (Portugal) with an average age of 11.4 ± 1.4 years and 1.4 ± 0.7 years of experience. To assess the passive and active flexibility level, we used seven of the International Gymnastics Federation's recommended tests using main joints (i.e., hips and spine). The first evaluation was performed before the pandemic situation began in a training environment, and the second and third evaluation were performed during the lockdown, in home environment, and in virtual trainings. Finally, the last evaluation was carried out in a training environment after returning to face-to-face activities and with several rules such a social distancing and mask use. The results showed that significant improvements were verified in the flexibility level of the dancers from the first to the fourth moment of evaluation. In the current study, no statistical significance was noted for the decreased values of functional asymmetry between the preferred and non-preferred lower limbs. These differences may have substantial relevance for dancers' harmonious body development.

Impacts of the SARS-CoV-2 pandemic on the global demand for exotic pets: An expert elicitation approach.

The SARS-CoV-2 pandemic has caused immense social and economic costs worldwide. Most experts endorse the view that the virus has a zoonotic origin with the final spillover being associated with wildlife trade. Besides human consumption, wild animals are also extensively traded as pets. Information on zoonotic diseases has been reported to reduce consumer demand for exotic pets. We conducted a global survey and collected 162 responses from international experts on exotic pet trade (traders, academics, NGOs, enforcement entities) to understand how the legal and illegal trade of exotic pets is expected to be affected by the ongoing coronavirus pandemic. Our results suggest that legal purchase of exotic pets is perceived as decreasing during the first pandemic wave due to: lower availability of animals for trade, suppliers' inability to reach consumers and social distancing measures. The general perception is that in the future (i.e., next five years), both demand and supply of legally traded exotic pets are expected to either remain unchanged or decrease only temporarily. The consumer demand for illegal exotic pets is also expected to remain unchanged following the outbreak. The top two challenges reported by respondents, when considering the consequences of the pandemic for the exotic pet trade, are inadequate enforcement of national regulations and increased illegal trade. Our results suggest that the negative consequences of a zoonotic outbreak may not dissuade consumers of exotic pets. Worldwide, the transit/storing conditions and lack of health screenings of traded live animals are conducive to spreading diseases. Consumer demand is a key driver of trade, and enforcement of trade regulations will remain challenging, unless factors driving consumer demand are adequately incorporated in problem-solving frameworks. We emphasize the complexity of trade dynamics and the need to go beyond bans on wildlife trade. Stronger law enforcement, implemented along with initiatives dissuading consumption of wild exotic pets, are essential to sustainably satisfy the market demand.