Active surveillance of adverse events following COVID-19 vaccines in a tertiary care hospital.

Background: Vaccination is a safe and effective way to prevent disease and save lives, but it may also produce some undesirable adverse events (AEs)which may affect healthy individuals. Therefore, the monitoring of AE following immunization (AEFIs) is necessary. The objective of this study was to assess the AEs following COVID-19 vaccinations in a tertiary care hospital. Methodology: The study was conducted as active vaccine safety surveillance for a period of 6 months among the COVID-19 vaccine beneficiaries of the study site. Active surveillance was conducted via initiating two telephone contacts. The first surveillance was conducted in 8 days and the second surveillance after 28 days of post-vaccination. All identified AEs following immunizations (AEFIs) were reported and analysed by the AEFI investigation team at the study site. The causality assessment of each identified AEFI was performed using the World Health Organization's causality assessment algorithm. Results: A total of 2927 enrolled study population completed the study with a response rate of 80.85%. The study identified 902 AEFIs from 614 study populations with an incidence rate of 20.97%. Of which 794 and 79 AEFIs were associated with COVISHIELD™ and COVAXIN®, respectively. The majority of the events were reported among the age group of 18-29 years. Overall, only three events were serious and no deaths were reported among the study population. A total of 75.59% of events had a consistent causal association with vaccination and were categorized as vaccine product-related reactions. The study identified various factors such as gender (p = 0.019), age (p < 0.05), co-morbid status (p = 0.032) and dose number (p = 0.001) as potential predictors for development of AEFI. Conclusion: The study identified only 0.33% of events as serious, and 99.67% of the study population recovered from the AEFIs, which reveals that COVISHIELD™ and COVAXIN® have a generally favourable safety profile. However, close monitoring is required to identify the potential signals, as the safety data from the clinical trials are limited.

Comorbidities influence the predictive power of hematological markers for mortality in hospitalized COVID-19 patients.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) pandemic has caused unprecedented mortality and has stretched the health infrastructure thin worldwide, especially in low- and middle-income countries. There is a need to evaluate easily available biomarkers for their clinical relevance for poor outcomes in severe cases of COVID-19. It is also known that comorbidities affect these biomarkers with or without COVID-19. We aimed to unearth the influence of comorbidities on feasible hematological predictive markers for mortality in hospitalized severe COVID-19 patients. MATERIALS AND METHODS: This is a retrospective study done on severe COVID-19 hospitalized patients, diagnosed with RT polymerase chain reaction (n = 205), were investigated. Comorbidities associated with the patients were tracked and scored according to Charlson comorbidity index (CCI). CCI score of zero was grouped in A, those with CCI score 1-4 into group B and those with CCI scores ≥ 5 into group C. Correlation between hematological parameters and CCI scores was analyzed using Pearson correlation coefficient. Optimal cut-off and odds ratio was derived from receiver operating characteristic (ROC) curve analysis. RESULTS: Among the 205 severe COVID-19 patients age, C-reactive protein (CRP), neutrophil lymphocyte ratio (NLR), derived NLR (dNLR), absolute neutrophil count (ANC) and total leukocyte count (TLC) were found to be statistically significant independent risk factors for predicting COVID-19 mortality (p < 0.01). In group A, cut off for CRP was 51.5 mg/L (odds ratio [OR]: 26.7; area under curve [AUC]: 0.867), TLC was 11850 cells/mm³ (OR: 11.7; AUC: 0.731), NLR was 11.76 (OR: 14.3; AUC: 0.756), dNLR was 5.77 (OR: 4.89; AUC: 0.659), ANC was 13110 cells/mm³ (OR: 1.68; AUC: 0.553). In group B, cut off for CRP was 36.5 mg/L (OR: 32.1; AUC: 0.886), TLC was 11077 cells/mm³ (OR: 12.1; AUC: 0.722), NLR was 8.27 (OR: 18.9; AUC: 0.827), dNLR was 3.79 (OR: 9.26; AUC: 0.727), ANC was 11420 cells/mm³ (OR: 2.42; AUC: 0.564). In group C, cut-off for CRP was 23.7 mg/L (OR: 32.7; AUC: 0.904), TLC was 10480 cells/mm³ (OR: 21.2; AUC: 0.651), NLR was 6.29 (OR: 23.5; AUC: 0.647), dNLR was 1.93 (OR: 20.8; AUC: 0.698), ANC was 6650 cells/mm³ (OR: 2.45; AUC: 0.564). CONCLUSIONS: In severe COVID-19 patients, CRP was the most reliable biomarker to predict mortality followed by NLR. Presence, type, and number of co-morbidities influence the levels of the biomarkers and the clinically relevant cut-offs associated with mortality.

Adverse events following COVID-19 vaccination: first 90 days of experience from a tertiary care teaching hospital in South India.

BACKGROUND: The COVID-19 vaccination program was introduced in India on 16 January 2021. The Government-issued fact sheet was the only source of information regarding Adverse Events Following Immunizations (AEFIs) for these vaccines. The objective of this study was to assess the AEFIs reported following COVID-19 vaccination in a tertiary care teaching hospital. MATERIALS AND METHODS: The spontaneous reporting method was used for data collection for a period of 3 months. A data collection form was designed to collect the data from the study population who reported adverse events. Collected data were analyzed and categorized by severity and seriousness. The causality assessment team performed causality assessment of the AEFIs using the World Health Organization's causality assessment algorithm. RESULTS: A total of 11,656 doses of COVID-19 vaccine were administered at the study site during the study period, of which 9292 doses were COVISHIELD™ and 2364 doses were COVAXIN™. In all, 445 AEFIs were reported from 269 subjects with an incidence rate of 3.48%. The majority of the subjects with AEFIs belonged to the age group of 18-45 years. Out of the total 445 AEFIs, 418 AEFIs were expected as per the fact sheets, 409 with COVISHIELD™ and 9 with COVAXIN™. Most of the AEFIs [62.02% (n = 276)] were observed at the system organ class of 'General disorders and administration site conditions'. After the causality assessment, out of 433 AEFIs to COVISHIELDTM vaccine, 94.22% (n = 408) of events were categorized to have 'consistent causal association with immunization'. Out of 12 adverse events following COVAXIN™, 8 (66.66%) events were categorized as 'consistent causal association with immunization'. All of them recovered from their adverse events without any sequelae. CONCLUSION: Spontaneous reporting is one of the cheapest methods that can be used for the reporting of AEFI. This method helps health care professionals to identify rare events and potential signals.

Acute pancreatitis complicating dengue hemorrhagic fever.

Dengue infection can have spectrum of manifestations, often with an unpredictable clinical progression and outcome. There have been increasing reports of atypical manifestations. Abdominal pain or tenderness and persistent vomiting (warning signs) are present in the majority of cases with severe dengue prior to clinical deterioration. We report a 10-year-old child who presented with fever, persistent vomiting, and abdominal pain. A diagnosis of acute pancreatitis was made. This is a very infrequently reported complication of dengue hemorrhagic fever.

Acute pancreatitis complicating dengue hemorrhagic fever

Abstract Dengue infection can have spectrum of manifestations, often with an unpredictable clinical progression and outcome. There have been increasing reports of atypical manifestations. Abdominal pain or tenderness and persistent vomiting (warning signs) are present in the majority of cases with severe dengue prior to clinical deterioration. We report a 10-year-old child who presented with fever, persistent vomiting, and abdominal pain. A diagnosis of acute pancreatitis was made. This is a very infrequently reported complication of dengue hemorrhagic fever.