Improving Nursing Students' COVID-19 Knowledge Using a Serious Game.

Improving nursing students' understanding of the novel COVID-19 is an essential component of their education. We designed and developed a serious game-based computer learning application that requires nursing students to solve problems through simulated cases. This study aimed to compare knowledge mastery among nursing students who used this teaching method versus those who received online lectures. A retrospective observational study was conducted using preclass, postclass, and final test scores of 130 students retrieved from the university's database of test scores. Both teaching methods produced significant increases in short-term knowledge of COVID-19. There was no statistical difference between the two methods in pre- and postclass scores; however, the serious game group scored higher than the online lecture group in knowledge retention. In summary, the serious game application is a potentially effective method for COVID-19 education among nursing students, particularly in terms of its capacity for improved knowledge retention.

Treatment strategies for gastric cancer during the COVID-19 pandemic.

The coronavirus disease 2019 pandemic has become a major global public health problem. Governments are taking the necessary steps to reduce the movement of people to contain the spread of the virus. However, these measures have caused considerable distress to patients with gastric cancer who are newly diagnosed or are undergoing treatment. In addition to the cancer, they must deal with longer waiting times for surgery and poor communication with doctors. Furthermore, gastric cancer patients generally have low immunity and a poor nutritional status, so they are a high-risk group for infection with the novel coronavirus. Therefore, it is necessary to formulate reasonable outpatient management strategies to reduce the adverse effects of the pandemic on their treatment. We summarize the management strategies for patients with gastric cancer during the pandemic.

Health Workforce Development in Health Emergency and Disaster Risk Management: The Need for Evidence-Based Recommendations.

The Sendai Framework for Disaster Risk Reduction 2015-2030 placed human health at the centre of disaster risk reduction, calling for the global community to enhance local and national health emergency and disaster risk management (Health EDRM). The Health EDRM Framework, published in 2019, describes the functions required for comprehensive disaster risk management across prevention, preparedness, readiness, response, and recovery to improve the resilience and health security of communities, countries, and health systems. Evidence-based Health EDRM workforce development is vital. However, there are still significant gaps in the evidence identifying common competencies for training and education programmes, and the clarification of strategies for workforce retention, motivation, deployment, and coordination. Initiated in June 2020, this project includes literature reviews, case studies, and an expert consensus (modified Delphi) study. Literature reviews in English, Japanese, and Chinese aim to identify research gaps and explore core competencies for Health EDRM workforce training. Thirteen Health EDRM related case studies from six WHO regions will illustrate best practices (and pitfalls) and inform the consensus study. Consensus will be sought from global experts in emergency and disaster medicine, nursing, public health and related disciplines. Recommendations for developing effective health workforce strategies for low- and middle-income countries and high-income countries will then be disseminated.

Prognostic value of three rapid scoring scales and combined predictors for the assessment of patients with coronavirus disease 2019.

AIM: To explore the factors affecting mortality in patients with COVID-19 and to verify the predictive value of the three rapid scoring scales MEWS, RAPS and REMS. DESIGN: Cross-sectional observational study. METHODS: Kaplan-Meier and Cox survival analyses were performed to identify the risk factors associated with COVID-19-related death. A ROC curve analysis was used to evaluate the abilities of the three scoring scales to predict the prognosis of COVID-19 patients. RESULTS: Age, low blood oxygen saturation level and decreased lymphocyte count were the high risk factors for COVID-19-related mortality. The analysis of the abilities of the three scales to predict the prognosis of COVID-19 patients: The AUC of 0.641 for the RAPS (p = .065). The MEWS (AUC = 0.705, p = .007), compared with RAPS, the NRI was 0.371(p = .03), and the IDI = 0.092 (p = .046); The REMS (AUC = 0.841, p < .001), compared with MEWS, the NRI was 0.227(p = .12), and the IDI=0.09(p = .047); The Combining Predictor (AUC = 0.878, p < .001), compared with REMS, the NRI was 0.25(p = .113), and the IDI=0.02(p = .598). CONCLUSION: Patients with an old age, low blood oxygen saturation level and decreased lymphocyte count were at a high risk of COVID-19-related mortality. Moreover, our analysis revealed that the REMS had a better prognostic ability than the MEWS and RAPS when applied to COVID-19 patients. Our findings suggest that the REMS can be used as a rapid scoring tool for the early assessment of COVID-19 severity.

The Effectiveness of a Serious Game Versus Online Lectures for Improving Medical Students' Coronavirus Disease 2019 Knowledge.

Objective: The sudden disruption of university teaching caused by the coronavirus disease 2019 (COVID-19) pandemic has forced universities to switch to online teaching. It is vital for graduating medical students to learn about COVID-19 because they are likely to treat COVID-19 patients after graduation. We developed a COVID-19 lesson for medical students that used either an online lecture or a serious game that we designed. The aim of this study is to explore the effectiveness of a serious game versus online lectures for improving medical students' COVID-19 knowledge. Materials and Methods: From our university's database of knowledge scores, we collected the prelesson, postlesson, and final test knowledge scores of the students who participated in the lesson and conducted a retrospective comparative analysis. Results: An analysis of scores concerning knowledge of COVID-19 from prelesson and postlesson tests shows that both teaching methods produce significant increases in short-term knowledge, with no statistical difference between the two methods (P > 0.05). The final test scores, however, show that the group of students who used the game-based computer application scored significantly higher in knowledge retention than did the online lecture group (P = 0.001). Conclusion: In the context of the disruption of traditional university teaching caused by the COVID-19 pandemic, the serious game we designed is potentially an effective option for online medical education about COVID-19, particularly in terms of its capacity for improved knowledge retention.

Predictive Value of 5 Early Warning Scores for Critical COVID-19 Patients.

OBJECTIVES: A simple evaluation tool for patients with novel coronavirus disease 2019 (COVID-19) could assist the physicians to triage COVID-19 patients effectively and rapidly. This study aimed to evaluate the predictive value of 5 early warning scores based on the admission data of critical COVID-19 patients. METHODS: Overall, medical records of 319 COVID-19 patients were included in the study. Demographic and clinical characteristics on admission were used for calculating the Standardized Early Warning Score (SEWS), National Early Warning Score (NEWS), National Early Warning Score2 (NEWS2), Hamilton Early Warning Score (HEWS), and Modified Early Warning Score (MEWS). Data on the outcomes (survival or death) were collected for each case and extracted for overall and subgroup analysis. Receiver operating characteristic curve analyses were performed. RESULTS: The area under the receiver operating characteristic curve for the SEWS, NEWS, NEWS2, HEWS, and MEWS in predicting mortality were 0.841 (95% CI: 0.765-0.916), 0.809 (95% CI: 0.727-0.891), 0.809 (95% CI: 0.727-0.891), 0.821 (95% CI: 0.748-0.895), and 0.670 (95% CI: 0.573-0.767), respectively. CONCLUSIONS: SEWS, NEWS, NEWS2, and HEWS demonstrated moderate discriminatory power and, therefore, offer potential utility as prognostic tools for screening severely ill COVID-19 patients. However, MEWS is not a good prognostic predictor for COVID-19.

Comparing Rapid Scoring Systems in Mortality Prediction of Critically Ill Patients With Novel Coronavirus Disease.

OBJECTIVES: Rapid and early severity-of-illness assessment appears to be important for critically ill patients with novel coronavirus disease (COVID-19). This study aimed to evaluate the performance of the rapid scoring system on admission of these patients. METHODS: A total of 138 medical records of critically ill patients with COVID-19 were included in the study. Demographic and clinical characteristics on admission used for calculating Modified Early Warning Score (MEWS) and Rapid Emergency Medicine Score (REMS) and outcomes (survival or death) were collected for each case and extracted for analysis. All patients were divided into two age subgroups (<65 years and ≥65 years). The receiver operating characteristic (ROC) curve analyses were performed for overall patients and both subgroups. RESULTS: The median [25th quartile, 75th quartile] of MEWS of survivors versus nonsurvivors were 1 [1, 2] and 2 [1, 3] and those of REMS were 5 [2, 6] and 7 [6, 10], respectively. In overall analysis, the area under the ROC curve for the REMS in predicting mortality was 0.833 (95% confidence interval [CI] = 0.737 to 0.928), higher than that of MEWS (0.677, 95% CI = 0.541 to 0.813). An optimal cutoff of REMS (≥6) had a sensitivity of 89.5%, a specificity of 69.8%, a positive predictive value of 39.5%, and a negative predictive value of 96.8%. In the analysis of subgroup of patients aged <65 years, the area under the ROC curve for the REMS in predicting mortality was 0.863 (95% CI = 0.743 to 0.941), higher than that of MEWS (0.603, 95% CI = 0.462 to 0.732). CONCLUSION: To our knowledge, this study was the first exploration on rapid scoring systems for critically ill patients with COVID-19. The REMS could provide emergency clinicians with an effective adjunct risk stratification tool for critically ill patients with COVID-19, especially for the patients aged <65 years. The effectiveness of REMS for screening these patients is attributed to its high negative predictive value.