Antarctic representation in print media during the emergence of COVID-19

Like every other continent in the world, Antarctica has been affected by the COVID-19 pandemic, in an imagined as well as a practical sense. Antarctica is a mediated experience;that is, most of us experience the place through films, novels, music, visual arts and the media. We present an analysis of media articles from eight countries over three time periods - pre-COVID-19 outbreak (October-December 2019), shortly after the pandemic hit the headlines (March-May 2020) and when the virus was established (October-December 2020) - to discover how COVID-19 may have changed Antarctic discourse. Our study shows that representations of Antarctica have been affected by the pandemic, in some instances reinforcing existing ideas and in other cases bringing new ideas to the fore. Based on our findings, we believe that COVID-19 has begun to change representations of Antarctica, stepping us away from the prevailing Antarctic hero narrative and providing a more contemporary understanding of the Antarctic experience. We argue that this may increase our motivation to engage with Antarctic issues, with associated implications for future global stewardship of the region.

Negative pressure drainage relieves respiratory discomfort for patients with medical face masks under ocular surgeries during COVID-19

AIM: To report our precaution practices for ocular surgeries under local anesthesia during COVID-19 outbreak and evaluate the respiration situation among the patients with medical face masks under ocular surgeries. METHODS: Sixty Chinese patients needed eye surgery treatment were recruited and given medical face masks as one of the COVID-19 precaution practices during eye surgery with local anesthesia. Oxygen supplementation and negative pressure drainage were applied to relieve the potential respiratory discomfort, and the respiratory comfort score was evaluated. RESULTS: Patients with medical face masks experienced mild to moderate respiratory discomfort with an overall mean score of 2.34±0.73. Supplementation of oxygen together with negative pressure drainage relieved this discomfort (overall mean score of 0.15±0.75;P<0.001). There is no gender and operation time difference on respiratory discomfort or discomfort relieve. Failure in negative pressure drainage led to severe respiratory discomfort. CONCLUSION: Negative pressure drainage could maintain the respiratory circulation in patients with medical face mask under eye surgery with local anesthesia. Application of medical face masks in patients under surgeries is recommended to protect the medical practitioners during the operations within COVID-19 outbreak. Copyright 2021 by the IJO Press.

[Prediction of severe outcomes of patients with COVID-19].

Objective: To establish a new model for the prediction of severe outcomes of COVID-19 patients and provide more comprehensive, accurate and timely indicators for the early identification of severe COVID-19 patients. Methods: Based on the patients' admission detection indicators, mild or severe status of COVID-19, and dynamic changes in admission indicators (the differences between indicators of two measurements) and other input variables, XGBoost method was applied to establish a prediction model to evaluate the risk of severe outcomes of the COVID-19 patients after admission. Follow up was done for the selected patients from admission to discharge, and their outcomes were observed to evaluate the predicted results of this model. Results: In the training set of 100 COVID-19 patients, six predictors with higher scores were screened and a prediction model was established. The high-risk range of the predictor variables was calculated as: blood oxygen saturation <94%, peripheral white blood cells count >8.0×10(9), change in systolic blood pressure <-2.5 mmHg, heart rate >90 beats/min, multiple small patchy shadows, age >30 years, and change in heart rate <12.5 beats/min. The prediction sensitivity of the model based on the training set was 61.7%, and the missed diagnosis rate was 38.3%. The prediction sensitivity of the model based on the test set was 75.0%, and the missed diagnosis rate was 25.0%. Conclusions: Compared with the traditional prediction (i.e. using indicators from the first test at admission and the critical admission conditions to assess whether patients are in mild or severe status), the new model's prediction additionally takes into account of the baseline physiological indicators and dynamic changes of COVID-19 patients, so it can predict the risk of severe outcomes in COVID-19 patients more comprehensively and accurately to reduce the missed diagnosis of severe COVID-19.