Introduction: Coronavirus disease 2019 (COVID-19) vaccines protect against severe illness. However, data on post-vaccination COVID-19 breakthrough infections are limited.Methods: An analytical cross-sectional study was conducted from May 2021 to July 2021 among 2043 COVID-19-positive healthcare workers who were divided into a vaccinated group (n=1010) and an unvaccinated group (n=1033). A pre-tested questionnaire was circulated among the healthcare workers using Google Forms. Chest computed tomography (CT) severity score was the primary outcome variable analyzed using coGuide.Results: The average age of the study population was less than 45 years in both groups (43.05 ± 13.02 years). Most respondents (62%) were males. Hypertension (39%) and diabetes (33%) were the most common underlying diseases. Significant differences in age and cardiac disease were observed between the two groups (p = 0.07 and p <0.001, respectively). However, the difference was insignificant (p >0.05) for gender, hypertension, and diabetes. Most unvaccinated respondents had an increased CT severity score, and the difference between the studies groups was significant (p <0.001). Of the 1,010 vaccinated individuals, 382 (37.82%) received the only first vaccination dose, and 628 (62.18%) received both doses. The CT severity score decreased after receiving both vaccination doses, and the difference between CT severity score and vaccination status was significant (p <0.001).Conclusion: COVID-19 was mild in the vaccinated group. Chest CT severity score index can be considered an efficient tool in predicting prognosis and monitoring disease in patients with COVID-19 in India.

BackgroundCurrently, no effective and reproducible imaging method can quantitatively differentiate between benign and malignant thyroid nodules. This study aimed to assess the role of diffusion-weighted imaging (DWI) in differentiating benign from malignant thyroid nodules. MethodologyWe conducted an observational study in the Department of Radiodiagnosis at R. L. Jalappa Hospital and Research Center, Kolar, India. The study was conducted from January 2020 to June 2021, among 43 patients with thyroid swelling or nodules. We recorded patient baseline data, pertinent clinical history, and relevant laboratory investigations. Patients underwent diffusion-weighted MRI of the neck. We used receiver operator curve analysis to determine the utility of the apparent diffusion coefficient (ADC) of the thyroid nodule in predicting the histopathological diagnosis. Data were analyzed using coGuide (V1.0.3, BDSS Corp., India). ResultsA total of 43 patients were enrolled in the study (35 women, 81.4%; 8 men, 18.6%). The mean (SD) age was 49.8 (14.3) years. Nodular hyperplasia was the most common histopathologic diagnosis of the nodule (25.5%), followed by lymphocytic thyroiditis (16.2%). The MRI and histopathological findings matched: both found 35 (81.4%) nodules as benign and 8 (18.6%) as malignant. The ADC value of thyroid nodules had excellent predictive validity in predicting malignancy, as indicated by the area under the curve of 0.925 (95% confidence interval [CI] 0.804-1.000; p < 0.001). The sensitivity was 87.50% (95% CI 47.35%-99.68%), specificity was 94.29% (95% CI 80.84%-99.30%), and the total diagnostic accuracy obtained was 93.02% (95% CI 80.94%-98.54%). ConclusionsDWI with ADC measurement has the potential to differentiate between benign and malignant thyroid nodules.

Introduction: The global estimates of congenital anomalies in neonates are 6% and few of them are severe enough to cause death. According to World Health Organization (WHO), congenital anomalies attribute to 17-42% of the infant mortality. Apart from causing death, they also contribute to preterm births, childhood and adult mortality, with significant repercussions in families. With the advancement of technology, there has been a decrease in the number of deaths due to other causes and there has been an increasing concern about congenital anomalies. This calls for an inquiry into the recent burden of congenital anomalies and their associated risk factors. Hence, the study was carried out. Objectives: 1. To assess the frequency and pattern of congenital anomalies. 2. To determine the factors associated with congenital anomalies. Materials & methods: This is an observational study which included all live born neonates with congenital anomaly/ies admitted to R L Jalappa Hospital (RLJH) and still born neonates or aborti with congenital anomaly/ies delivered in RLJH during the study period. A detailed history of the study participants was taken, and all the anomalies were coded as per the ICD coding system. For still born babies, aborti and neonatal deaths, infantogram, gross autopsy and histopathological examination findings were noted. Statistical analysis: Data was analysed using “Microsoft excel sheet” and the analysis was done using Statistical Package for Social Sciences (SPSS-16) software. Significance was defined as p<0.05. Results: Our hospital had 2,400 deliveries during the study period, out of which the frequency of congenital anomalies was 1.3%. As per the associated risk factors, 66.6% of the babies had no associated risk factors while the remaining 33.4% of the babies had an associated risk factor. Most commonly seen risk factor in the study was 3rd degree consanguinity (11.1%). As per the system involved, Musculoskeletal system involvement was seen in the majority (63.9%) of the neonates, followed by Cardiovascular system in 11.1%, Central Nervous System (CNS) in 8.3%, Genital system in 8.3%, Lymphatic system in 5.6%, Gastrointestinal system in 2.8%, Cutaneous in 2.8%, Oral cavity in 2.8% and syndromic anomaly in 2.8%. Conclusion: The prevalence of congenital anomalies is considerably high and increasing the awareness to prevent them is the need of the hour. Appropriate consideration should be given to reducing the risk factors and genetic counseling should be provided to parents with high risk. Keywords: Congenital malformations, Neonates, Congenital anomalies