RESUMO
Objectives: The Omicron variant-mediated COVID-19 wave is responsible for a global tsunami of cases. There is scarce data about the clinical and epidemiological characteristic analyses of the third wave. We present the data of COVID-19 patients from Mumbai region during the early third wave by taking S-gene target failure (SGTF) as a proxy for probable Omicron cases. Methods: We collected retrospective data of RT-PCR-confirmed (COVID-19) patients, and measured the proportion of possible Omicron cases by SGTF. We segregated and analyzed the clinical and lab data of patients with outcomes such as differing symptoms, vaccination coverage, previous infection, and travel history. We also performed a trend analysis of Mumbai's COVID-19 data before and during the third wave. Results: All patients had mild clinical symptoms while few were asymptomatic. Myalgia was more significantly present in SGTF/Omicron cases compared to non-SGTF/Delta patients. Out of the total 101 COVID-positive individuals, 94 individuals (93%) had taken two doses of COVID vaccine. Among these 94 individuals, 9 (8.9%) had been previously infected with COVID 19 in the first or second waves. 77.7% of the previously infected were now infected with Omicron variant and only 22.3% by a non-Omicron variant. Conclusion: Rapid rise and fall during the third wave in Mumbai was due to Omicron cases gradually replacing Delta. The overall milder clinical spectrum in both Omicron and Delta cases imply that vaccines might not be effective against re-infection but can attenuate disease severity and mortality, as evident by high coverage of vaccination in the country.
RESUMO
Diabetic foot ulcer (DFU) is a major complication of diabetes with high morbidity and mortality rates. The pathogenesis of DFUs is governed by a complex milieu of environmental and host factors. The empirical treatment is initially based on wound severity since culturing and profiling the antibiotic sensitivity of wound-associated microbes is time-consuming. Hence, a thorough and rapid analysis of the microbial landscape is a major requirement toward devising evidence-based interventions. Toward this, 122 wound (100 diabetic and 22 nondiabetic) samples were sampled for their bacterial community structure using both culture-based and next-generation 16S rRNA-based metagenomics approach. Both the approaches showed that the Gram-negative microbes were more abundant in the wound microbiome. The core microbiome consisted of bacterial genera, including Alcaligenes, Pseudomonas, Burkholderia, and Corynebacterium in decreasing order of average relative abundance. Despite the heterogenous nature and extensive sharing of microbes, an inherent community structure was apparent, as revealed by a cluster analysis based on Euclidean distances. Facultative anaerobes (26.5%) were predominant in Wagner grade 5, while strict anaerobes were abundant in Wagner grade 1 (26%). A nonmetric dimensional scaling analysis could not clearly discriminate samples based on HbA1c levels. Sequencing approach revealed the presence of major culturable species even in samples with no bacterial growth in culture-based approach. Our study indicates that (i) the composition of core microbial community varies with wound severity, (ii) polymicrobial species distribution is individual specific, and (iii) antibiotic susceptibility varies with individuals. Our study suggests the need to evolve better-personalized care for better wound management therapies.IMPORTANCE Chronic nonhealing diabetic foot ulcers (DFUs) are a serious complication of diabetes and are further exacerbated by bacterial colonization. The microbial burden in the wound of each individual displays diverse morphological and physiological characteristics with unique patterns of host-pathogen interactions, antibiotic resistance, and virulence. Treatment involves empirical decisions until definitive results on the causative wound pathogens and their antibiotic susceptibility profiles are available. Hence, there is a need for rapid and accurate detection of these polymicrobial communities for effective wound management. Deciphering microbial communities will aid clinicians to tailor their treatment specifically to the microbes prevalent in the DFU at the time of assessment. This may reduce DFUs associated morbidity and mortality while impeding the rise of multidrug-resistant microbes.
