Development and validation of prognostic scoring system for COVID-19 severity in South India.

BACKGROUND: Development of a prediction model using baseline characteristics of COVID-19 patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring system for predicting the COVID-19 severity in South India. METHODS: We undertook this retrospective cohort study among COVID-19 patients reporting to Hindu Mission Hospital, India. Multivariable logistic regression using the LASSO procedure was used to select variables for the model building, and the nomogram scoring system was developed with the final selected model. Model discrimination, calibration, and decision curve analysis (DCA) was performed. RESULTS: In total, 35.1% of the patients in the training set developed severe COVID-19 during their follow-up period. In the basic model, nine variables (age group, sex, education, chronic kidney disease, tobacco, cough, dyspnea, olfactory-gustatory dysfunction [OGD], and gastrointestinal symptoms) were selected and a nomogram was built using these variables. In the advanced model, in addition to these variables (except OGD), C-reactive protein, lactate dehydrogenase, ferritin, D-dimer, and CT severity score were selected. The discriminatory power (c-index) for basic model was 0.78 (95%CI: 0.74-0.82) and advanced model was 0.83 (95%CI: 0.79-0.87). DCA showed that both the models are beneficial at a threshold probability around 10-95% than treat-none or treat-all strategies. CONCLUSION: The present study has developed two separate prognostic-scoring systems to predict the COVID-19 severity. This scoring system could help the clinicians and policymakers to devise targeted interventions and in turn reduce the COVID-19 mortality in India.

Can mRNA Vaccines Turn the Tables During the COVID-19 Pandemic? Current Status and Challenges.

The COVID-19 pandemic continues to affect millions of people across the world. The current global statistics for the disease are 111 million cases and 2.45 million deaths, with new cases emerging each day. Although several drugs including remdesivir have been approved for emergency use, they remain ineffective in bringing the infection under control. Therefore, there is a need for highly effective and safe vaccines against COVID-19. The recent advancements in mRNA vaccines have catapulted them to be forefront in the race to develop vaccines for COVID-19. Two mRNA vaccines, BNT162b2 and mRNA-1273, developed by Pfizer-BioNTech and Moderna Therapeutics, respectively, have been granted authorization for emergency use by the US Food and Drug Administration. Interim analysis of the clinical trials for BNT162b2 and mRNA-1273 vaccines reported an efficacy of 95% and 94.1%, respectively, after the second dose. The adverse events for both the vaccines have been found to be mild to moderate, with mostly injection-site reactions and fatigue. No serious adverse events have been reported. Moreover, Pfizer-BioNTech and Moderna Therapeutics have announced that their vaccines are effective even against the new strains (B.1.17 and B.1.351) of the virus. Both companies are now scaling up the production of the vaccines to meet the global demand. Although the long-term efficacy, safety, and immunogenicity of these vaccines is uncertain, there is hope that they can turn the tables against COVID-19 in this current pandemic situation.