Clinical profile of COVID-19 infection in postvaccination individuals.

OBJECTIVES: Covishield and Covaxin vaccines have been introduced after rapid approval in India, the nation that has the second most COVID-19 cases globally. These vaccines have been administered in a 2-dose schedule since January 16, 2021. This study deals with the clinical profile of individuals who developed COVID-19 infection post COVID-19 vaccination. This is the first study of its kind in India. STUDY DESIGN: Descriptive cross-sectional study. METHODS: The study population was composed of individuals who were COVID-19 positive more than 4 weeks post vaccination and were compared with individuals who were COVID-19 positive within the first 4 weeks of vaccination. Data were collected in a digital questionnaire format and analyzed with SPSS version 23 software. Clinical features were profiled in detail. Chi-square analysis was done to find out the association of various demographic features with the severity of the disease. RESULTS: In the study population, fever was the most common symptom (75.1%), followed by anosmia (72.1%) and shortness of breath (16.3%). There was a lower incidence of fever, cough, dyspnea, and requirement of hospitalization in the study population compared with the control group and previous epidemiological data. The time required for complete recovery and disease severity was favorable in our study population. There was a significant correlation in the rate of hospitalization among the study group and the comparative group (P = .0001) and between the number of doses of COVID-19 vaccine and the lowest oxygen saturation recorded (P = .001). CONCLUSIONS: The findings of this study should boost the ongoing initiative of maximizing the vaccinated population countrywide and emphasize the need for 2 doses of vaccination.

Covishield India: demystifying myths through an early multicenter study.

OBJECTIVES: Nationwide COVID-19 vaccination was initiated in India on January 16, 2021, in a phased manner with vaccines including Covishield. This vaccine was indigenously prepared by Serum Institute of India in line with the Oxford-AstraZeneca ChAdOx1 vaccine developed at the University of Oxford. This is the first multicenter study to assess the safety of the indigenously prepared Covishield vaccine in India. STUDY DESIGN: Multicenter observational descriptive study. METHODS: This was a multicenter study carried out in northern and eastern India. Individuals who received the first dose of the Covishield vaccine were followed up for 7 days to check for any adverse effects or systemic effects post vaccination. The data were collected by the authors with a participant-administered questionnaire. The primary end point was the incidence of adverse or systemic effects within 7 days post vaccination. RESULTS: No serious adverse or systemic effects were noted in 7 days of follow-up. Nonserious systemic effects were seen in 42.0% of individuals post vaccination. Myalgia and/or fatigue was the most common effect of vaccination in 25.7%, followed by fever in 22.0% of individuals. In most individuals, the systemic effects started 6 to 12 hours post vaccination. There were no reports of fresh onset of systemic effects of any kind beyond 48 hours of vaccination. Women and older adults tolerated the vaccination better. CONCLUSIONS: The absence of serious adverse effects in our study will help allay fears around vaccine acceptance and give a boost to the vaccination campaign worldwide.

Covishield India: Demystifying Myths Through an Early Multicenter Safety Study

Objectives: Nationwide COVID-19 vaccination was initiated in India on January 16, 2021, in a phased manner with vaccines including Covishield. This vaccine was indigenously prepared by Serum Institute of India in line with the Oxford-AstraZeneca ChAdOx1 vaccine developed at the University of Oxford. This is the first multicenter study to assess the safety of the indigenously prepared Covishield vaccine in India. Study Design: Multicenter observational descriptive study. Methods: This was a multicenter study carried out in northern and eastern India. Individuals who received the first dose of the Covishield vaccine were followed up for 7 days to check for any adverse effects or systemic effects post vaccination. The data were collected by the authors with a participant-administered questionnaire. The primary end point was the incidence of adverse or systemic effects within 7 days post vaccination. Results: No serious adverse or systemic effects were noted in 7 days of follow-up. Nonserious systemic effects were seen in 42.0% of individuals post vaccination. Myalgia and/or fatigue was the most common effect of vaccination in 25.7%, followed by fever in 22.0% of individuals. In most individuals, the systemic effects started 6 to 12 hours post vaccination. There were no reports of fresh onset of systemic effects of any kind beyond 48 hours of vaccination. Women and older adults tolerated the vaccination better. Conclusions: The absence of serious adverse effects in our study will help allay fears around vaccine acceptance and give a boost to the vaccination campaign worldwide.

Systematic review of predictive mathematical models of COVID-19 epidemic.

BACKGROUND: Various mathematical models were published to predict the epidemiological consequences of the COVID-19 pandemic. This systematic review has studied the initial epidemiological models. METHODS: Articles published from January to June 2020 were extracted from databases using search strings and those peer-reviewed with full text in English were included in the study. They were analysed as to whether they made definite predictions in terms of time and numbers, or contained only mathematical assumptions and open-ended predictions. Factors such as early vs. late prediction models, long-term vs. curve-fitting models and comparisons based on modelling techniques were analysed in detail. RESULTS: Among 56,922 hits in 05 databases, screening yielded 434 abstracts, of which 72 articles were included. Predictive models comprised over 70% (51/72) of the articles, with susceptible, exposed, infectious and recovered (SEIR) being the commonest type (mean duration of prediction being 3 months). Common predictions were regarding cumulative cases (44/72, 61.1%), time to reach total numbers (41/72, 56.9%), peak numbers (22/72, 30.5%), time to peak (24/72, 33.3%), hospital utilisation (7/72, 9.7%) and effect of lockdown and NPIs (50/72, 69.4%). The commonest countries for which models were predicted were China followed by USA, South Korea, Japan and India. Models were published by various professionals including Engineers (12.5%), Mathematicians (9.7%), Epidemiologists (11.1%) and Physicians (9.7%) with a third (32.9%) being the result of collaborative efforts between two or more professions. CONCLUSION: There was a wide diversity in the type of models, duration of prediction and the variable that they predicted, with SEIR model being the commonest type.

"The Janus Face" of Thrombocytes in COVID-19.

A 55 year old patient of COVID-19, with no known comorbidities presented with fever, myalgia and headache and at presentation had leukopenia and thrombocytopenia, however did not have any bleeding manifestations. The patient's inflammatory markers including ferritin and C-reactive protein were elevated at admission. Later in the course of illness went on to develop severe thrombocytosis and leukocytosis. We discuss the course and outcome of illness in an unusual case of COVID-19 with severe and diametrically opposite haematological abnormalities.

Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio and Their Role as Predictors of Disease Severity of Coronavirus Disease 2019 (COVID-19).

Context Due to the wide spectrum of clinical illness in coronavirus disease 2019 (COVID-19) patients, it is important to stratify patients into severe and nonsevere categories. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been evaluated rapidly by a few studies worldwide for its association with severe disease, but practically none have been conducted in the Indian population. This study was undertaken to examine the role of NLR and PLR in predicting severe disease in Indian patients. Objectives The objective was to study the association of NLR and PLR observed at the time of admission with maximum disease severity during hospitalization and to study their role in predicting disease severity. Material and Methods A total of 229 COVID-19 patients were admitted at the center during the study period. After applying inclusion and exclusion criteria, 191 patients were included in the study. The demographic, clinical, and laboratory (complete blood count, NLR, and PLR) data of all patients were obtained at the time of admission. Maximum disease severity of all patients was assessed during hospitalization. Statistical Analysis Chi-square and Mann-Whitney U tests were used to assess statistical significance. Receiver operating characteristic curve (ROC) was plotted for NLR and PLR to estimate the cutoff values and sensitivity and specificity using Youden's index for predicting severe disease. Logistic regression analysis was used to estimate the odds ratios (OR) and 95% confidence intervals. Results Mean NLR and PLR were significantly higher in severe patients (NLR = 7.41; PLR = 204) compared with nonsevere patients (NLR = 3.30; PLR = 121). ROC analysis showed that NLR, in comparison to PLR, had a higher area under the curve (AUC) of 0.779, with a larger OR of 1.237 and cutoff of 4.1, and showed 69% sensitivity and 78% specificity in predicting severe disease. Cut off for PLR was 115.3, which showed 79% sensitivity and 62% specificity in predicting severe disease. Conclusion NLR and PLR, both showing acceptable AUCs, can be used as screening tools to predict disease severity. However, NLR was a better predictor of disease severity.

Relation of D-dimer levels of COVID-19 patients with diabetes mellitus.

BACKGROUND AND AIMS: Diabetes is a frequent comorbidity in patients with Severe COVID-19 infection associated with a worse prognosis. Hypercoagulability with elevation in D-dimer levels has been demonstrated in patients with COVID-19. This study aims to study D-dimer levels in people with diabetes compared to those without diabetes among patients with COVID-19 infection. METHODS: In this observational study 98 moderate and severely ill patients with COVID-19 infection were included at a dedicated COVID hospital. The study group was divided into patients with diabetes and without diabetes. Peak D-dimer was measured in both the groups and compared using appropriate statistical tests. RESULTS: In our study peak D-dimer levels were 1509 ± 2420 ng/mL (Mean ± SD) in people with diabetes and 515 ± 624 ng/mL (Mean ± SD) in patients without diabetes. Patients with diabetes had higher D-dimer levels which were statistically significant. CONCLUSIONS: This study shows COVID-19 patients with diabetes had significantly higher D-dimer levels. Therefore, it is possible that COVID-19 infection with diabetes is more likely to cause hypercoagulable state with a worse prognosis. However clinical implications of these findings will need to be seen in further studies.