Predicting the Disease Severity and Mortality in COVID-19 Patients based on Disease Characteristics: An Observational Study in Indian Setting

Introduction: The emergence of newer mutated variants of COVID-19 virus has posed a significant challenge. The present study is aimed at investigating the clinical characteristics of COVID-19 and the parameters that may serve as predictors of severity and mortality related to COVID-19 in an Indian setting. Method(s): The observation study was carried-out by using the data of COVID-19 patients admitted between July 2020 to June 2021 at JLN Medical College, Ajmer, Rajasthan, India. The demographic and clinical data of clinically significant parameters were collected. The statistical difference between recovery and death and between patients who required long-term oxygen and those who did not was evaluated for various demographic and clinical variables. Chi-square and Fisher exact test were performed for categorical variables and t-test for continuous variables. Regression analyses were also carried-out for different variables with respect to survival and death, and for oxygen dependency. Result(s): Variables namely age, duration of hospital stay, overweight, breathlessness, O2 mask therapy, BiPAP support, and ventilator usage were found to be significantly different between recovered and expired subjects (P 0.00). The study has noted hypertension (25.06%) and diabetes (23.73%) as the common comorbidities noted in COVID patients, followed by coronary artery disease (2.98%) and asthma. The study has validated the role of oxygen saturation and requirement of oxygen in predicting mortality among COVID-19 patients. The study identified age as a significant predictor of mortality, obesity as a risk factor in COVID-19 patients, gender as a factor influencing the requirement of oxygen, and fever as an independent factor related to oxygen therapy. Bilevel positive airway pressure was given to majority of expired patients (83%) compared to 10% in recovered patients. Conclusion(s): Variables namely age, BMI, duration of hospital stay, breathlessness, O2 mask therapy, BiPAP support, and ventilator usage could be predictive in COVID-19 severity and mortality. The variables to be considered for predicting oxygen dependency are age, urban/rural, gender, duration of hospital stay, weight, height, BMI, fever, cough, breathlessness, diabetes, hypertension, and CAD. Copyright © 2022, Indian Academy of Clinical Medicine. All rights reserved.

TOCILIZUMAB (BIOSIMILAR) USE in CYTOKINE STORM of SEVERE COVID-19 PNEUMONIA

Background: Tocilizumab is an IgG1 class humanized monoclonal antibody targeting IL-6 receptor (IL-6R). IL-6 is a key cytokine involved in cytokine storm of severe COVID-19. Tocilizumab down-regulates IL-6 preventing fatal and permanent damage to vital organs, significantly preventing COVID-19 related mortality and morbidity. Therefore, this study aimed to compare the efficacy and safety of Tocilizumab (biosimilar) developed by Hetero Biopharma Ltd, India vs reference medicinal product (RMP)-Tocilizumab manufactured by Roche in cytokine storm of severe COVID-19 pneumonia. Methods: This multicenter, randomized, double-blind, active-controlled study enrolled patients aged 18 to 65 years, with laboratory-confirmed, hospitalized, severe COVID-19 disease with elevated inflammatory markers not on mechanical ventilation. Patients were randomized (3:1 ratio) to receive either Test-Tocilizumab (Test) 8 mg/kg or RMP-Tocilizumab 8mg/kg, maximum 800mg, administered once on day 1. The primary endpoint was the cumulative proportion of patients requiring mechanical ventilation by Day 14. Secondary endpoints included 28 day mortality rate, proportion of patients with a 2-point decrease in WHO ordinal scale, time to clinical failure (death or required mechanical ventilation or withdrawn), change in inflammatory markers (CRP, IL-6, Ferritin and D-dimer) and duration of hospital stay in days. Safety endpoints included the incidence of adverse events;the proportion of patients discontinued the study due to adverse events and the incidence of any post-treatment bacterial and/or fungal infection. Results: Out of 211 patients screened, 172 patients were randomized (131 to Test and 41 to RMP) to receive Tocilizumab 8mg/kg. Patients were similar in both groups at baseline in terms of age, gender, weight etc. Fourteen (10.69%) patients in Test and 5 (12.20%) patients in RMP progressed to mechanical ventilation by Day 14 (p=0.7789). Overall, 9 (7.83%) patients died in Test vs 5 (13.16%) in RMP during 28 days follow up (p=0.3382). Clinical improvement was seen 62.60% and 77.10% vs 53.66% and 73.17% in Test vs RMP at day 14 and 28 respectively. The time to clinical failure was 6 vs 5 days and time to clinical improvement was 11 vs 11.5 days. Hospitalization duration was 12.9 versus 13.8 days in the Test and RMP. ARDS, Insomnia and Pain were most commonly reported adverse events. Conclusion: Tocilizumab biosimilar is comparable with RMP-Tocilizumab in preventing mechanical ventilation in severe COVID19 pneumonia patients.

Frequency and Pattern of Myths and Misconception regarding Covid- 19 Vaccine in General Population

Objective: To determine the frequency and pattern of myths and misconceptions regarding COVID-19 vaccine in the general population at Isra University Hospital Hyderabad Material and Methods: This cross-sectional survey base study was conducted at the Isra University Hospital Hyderabad, during a period of six months from August 2021 to January 2022. All the patients who visited the OPD and their attendants of any age or gender, were included. All the subjects were properly counseled that their privacy was fully secured and their name and contact numbers were taken. After obtaining sociodemographic information, the participants were interviewed regarding COVID-19 infection in the past, previous vaccination history for diseases other than COVID-19, conceptions, and myths regarding COVID-19 vaccination, acceptance of COVID-19 vaccination, reasons to vaccinate for COVID-19, and reasons not to vaccinate for COVID-19. All the information was gathered via study proforma including questioner and SPSS version 26 was used for the purpose of data analysis. Results: A total of 145 individuals of either gender were studied regarding myths and misconceptions of COVID-19 vaccine, their average age was 27.71+9.86 years and females were in majority 62.1%. Among the study population, doctors, private employee and housewives were the most common as 44.1%, 11%, 11.7% and 9% respectively. Most of the cases 62.1% were unmarried. According to the myths and misconceptions, 8.3% said it can affect fertility, 23.4% had no trust on its effectiveness and safety, 14.5% said it is an artificial infection procedure, 11% were afraid from its dangerous side effects, 3.4% said the vaccine will change their DNA, 13.8% said it is a controversial substance and 6.9% afraid that they will die within 2 years. 24.1% cases heard myths from family, 24.8% heard from friends and 51% heard by social media. 17.2% had idea that it is an international conspiracy and 4.8% said this may cause sexual dysfunction and 4.8% said it is a procedure of implanting microchip to control them. Conclusion: There were several misconceptions in the general population, most myths like effects of male fertility, distrust on vaccine efficacy, they will be infected artificially, fear of dangerous side effects, controversial substances were observed to be the commonest myths and misconceptions regarding the COVID-19 vaccine in the general population. Above ideas were adopted mostly by the friends and social media.

Piloting a Novel Medical Student Virtual Discharge Counseling Process in the Time of COVID

Study Objectives: During the COVID-19 pandemic, there was a gap in adequate discharge counseling for COVID-19 patients from the emergency department due to high patient volumes and constantly changing guidelines. Medical students were also restricted from clinical areas for safety, compromising their clinical experience. We piloted a novel program in which medical students served as virtual discharge counselors for COVID-19 patients via teleconference. This program allowed patients to receive dedicated counseling on their COVID-19 diagnosis. Students had a safe clinical experience while clinical staff could simultaneously provide direct patient care and increase ED efficiency. Methods: Students were trained with a standardized protocol and a discharge script. Counseling included diagnosis, supportive care with medication dosing, quarantine instructions, return precautions, follow up, and the ability to ask questions. Counseling was provided via secure video conference integrated in the electronic health record (EHR), in the patient’s preferred language. Results: Over an 18-week period, 45 patients were counseled for a median of 20 minutes (range, 7 to 39 min). 58% of patients spoke English;35% spoke Spanish;and 7% additional languages. Median times for discharge counseling were 16 minutes, 23 minutes, and 18 minutes, respectively (p = 0.015). The 72-hour ED revisit rate was 0%, versus 4.2% in similarly-matched, not counseled COVID-19 patients. Medical students (n= 16) believed this project increased their confidence when speaking with patients (90% strongly agreed or agreed) and that it was a worthwhile experience (100% strongly agreed or agreed). Lastly, 80% strongly agreed that they would volunteer again, and similarly, 80% indicated that this was their first telemedicine experience. Conclusion: Our novel discharge program provided patients extensive counseling in that preferred language that would not otherwise be possible in an urban ED setting amidst a pandemic (or even routine ED operations). Medical students received a safe clinical experience that improved their communication skills. Due to its success, this program was scaled across three additional ED sites, and ten additional counseling diagnoses were added. The program has now accrued over 100 medical and nursing student participants. This project has proven to be sustainable and is currently on- going as part of the emergency medicine medical student curriculum.

Helping heart: Exploring the determinants of helping behavior in the time of social distancing

To reduce and control the spread of COVID-19, people are advised and even forced by law to maintain social distancing when they step out of their homes. The lockdown norms laid down by the government have impacted the nature of social interaction and various forms of behavior including participation in prosocial activities. The present study explores the determinants of helping in the context of COVID-19 pandemic and social distancing measures. The theory of planned behavior framework was taken to predict youth’s intentions and actual help for two kinds of helping behavior: donation for the people affected by the pandemic and feeding stray animals during lockdown. University students (N = 200) volunteered for the online survey, scales were used to measure their attitude, normative beliefs, perceived behavioral control, intention to help, and self-reported help during COVID-19 lockdown. The path analysis was used to test the model. Attitude and perceived behavioral control had a strong effect on the intention to help which further predicts actual self-reported help. Results also showed that since the nature of both helping behaviors was different so the relationship between the two was not strong. The results and implications are discussed in light of the present context. © 2021 Taylor & Francis Group, LLC.

EVDHM-ARIMA-Based Time Series Forecasting Model and Its Application for COVID-19 Cases

The time-series forecasting makes a substantial contribution in timely decision-making. In this article, a recently developed eigenvalue decomposition of Hankel matrix (EVDHM) along with the autoregressive integrated moving average (ARIMA) is applied to develop a forecasting model for nonstationary time series. The Phillips-Perron test (PPT) is used to define the nonstationarity of time series. EVDHM is applied over a time series to decompose it into respective subcomponents and reduce the nonstationarity. ARIMA-based model is designed to forecast the future values for each subcomponent. The forecast values of each subcomponent are added to get the final output values. The optimized value of ARIMA parameters for each subcomponent is obtained using a genetic algorithm (GA) for minimum values of Akaike information criterion (AIC). Model performance is evaluated by estimating the future values of daily new cases of the recent pandemic disease COVID-19 for India, USA, and Brazil. The high efficacy of the proposed method is convinced with the results.

Impact of COVID 19 Lockdown on the Study of Medical Students: A Cross Sectional Survey

Introduction: During the pandemic of COVID 19, the traditional teaching of MBBS students has been shifted to online teaching. We conduct an online survey to know and record the impact of COVID 19 lockdown on the study of medical students of GDMC, Dehradun. The present study aimed to investigate the MBBS student’s perception of online teaching. The results of this study may provide further inputs which might be of help to the students and faculty for further informed decisions. Materials and Methods: A cross sectional online survey during July 1–7, 2020 was applied to 334 medical students to evaluate the perception of online teaching among medical students. A questionnaire was prepared in Google form and divided into two sections. The first part covered demographics information of the respondent and the second part assessed with behavior and attitude toward online teaching. Results: The mean assessment, behavior, and attitude scores have significantly differed across age groups and previous experience. The medical students who had no exposure to online teaching their assessment score is higher than who had little exposure also found to be significant. The participants were agreed with the teaching way of the course (59.3%) and with the content of the course (56.9%). Majority of participants (58.4%) also agree that there are barriers in online learning. Most of the students agree (62.3%) and strongly agree (61%) that the course allowed them to take responsibility for their learning. Conclusions: We can conclude that the online learning program is a good alternative to classroom teaching in this era of the COVID 19 pandemic. This study can provide the basic architecture for making further strategy of course content.

COVID-19: A bibliometric analysis and insights

The current outbreak of the coronavirus disease has left the whole world traumatised. The illness triggered by the novel coronavirus is named as COVID-19. It is pre-fixed with the word "novel" because it comes under the new strain of the virus that has not been reported before. This virus outbreak has disrupted human life in the most petrifying way worldwide. The present study aims to analyse the work done in this field through a state-of-the-art review of articles based on COVID-19 and discuss the current trends in the epidemiology of this disease entity with special reference to India and the effects of this pandemic on the environment. The time frame selected for review is the beginning of this pandemic to April 10th, 2020. Scopus® database is used to carry out the analysis. Moreover, the most contributed authors, institutions, countries, etc. are showed through the analysis. The purpose of this review is to get an idea about the direction of the flow of current research, the association of various authors with each other, the role of collaboration between several institutions and the position of India in current explosive ongoing research. © 2020, International Journal of Mathematical, Engineering and Management Sciences.