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result(s) for
"Gautam, Bhaswati"
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COVID-19-associated rhino-orbital-cerebral mucormycosis: A systematic review, meta-analysis, and meta-regression analysis
by
Sarma, Phulen
,
Prajapat, Manisha
,
Sharma, Saurabh
in
Amphotericin B - therapeutic use
,
Analysis
,
Antifungal agents
2021
BACKGROUND: Till now, no meta-analysis is available to address the clinical profile, risk factors, different interventions, and outcomes among COVID-19-associated rhino-orbito-cerebral mucormycosis (C-ROCM) cases.
MATERIALS AND METHODS: Eight literature databases were screened using appropriate keywords from November 1, 2019, to June 30, 2021. The objectives were to analyze the clinical and microbiological profile, risk factor/comorbidity, intervention, and outcome. \"R-metafor package\" was used for analysis.
RESULTS: A total of 23 studies were included. The mean age of presentation of C-ROCM was 54.6 years. The most common presentation was ptosis (72.7%), lid edema (60.6%), proptosis (60.6%), ophthalmoplegia (57.3%), loss of vision (53.7%), facial edema (34.7%), and nasal-blockage (11.8%). Evidence of intracranial spread was seen in 42.8% of cases. Rhizopus was the most common fungus (57.1%) isolated in fungal culture. Among C-ROCM patients, diabetes was the commonest comorbid condition, and the use of corticosteroids related to COVID-19 treatment was the most common risk factor (85.75%). Compared to controlled diabetics, C-ROCM was significantly higher among uncontrolled diabetics (odds ratio [OR] 0.15, 95% confidence interval [C.I.] 0.041-0.544, P = 0.0010). However, no significant association was seen between C-ROCM and COVID-19 severity (OR 0.930, 95% C.I. 0.212-4.087, P = 0.923). For treatment, amphotericin-B was the most common antifungal drug used which was followed by surgical options. However, mortality was high (prevalence 0.344, 95% C.I. 0.205-0.403) despite treatment.
CONCLUSION: Although local rhino-orbito symptoms were the first to appear, rapid intracranial extension was seen in a significant number of C-ROCM cases. Uncontrolled diabetes and excessive use of corticosteroid were the most common risk factors present among the C-ROCM cases. High index clinical suspicion is imperative (specifically among COVID-19 patients with diabetes), and routine screening may be helpful.
Journal Article
Rhino-orbital-cerebral-mucormycosis in COVID-19: A systematic review
2021
Since the onset of COVID-19 pandemic, parallel opportunistic infections have also been emerging as another disease spectrum. Among all these opportunistic infection, mucormycosis has become a matter of concern with its rapid increase of cases with rapid spread as compared to pre-COVID-19 era. Cases have been reported in post-COVID-19-related immune suppression along with the presence of comorbidity which adds on the deadly outcome. There is no systematic review addressing the issue of COVID-19-associated mucormycosis. This is the first systematic review of published studies of mucormycosis associated with COVID-19. The aim was to analyze the real scenario of the disease statement including all the published studies from first November 2019 to 30th June to analyze the contemporary epidemiology, clinical manifestations, risk factor, prognosis, and treatment outcome of COVID-19 associated rhino-orbito-cerebral-mucormycosis. A comprehensive literature search was done in following databases, namely, PubMed, Google Scholar, Scopus, and EMBASE using keywords mucormycosis, rhino orbital cerebral mucormycosis, COVID-19, and SARS-CoV-2 (from November 01, 2019 to June 30, 2021). Our study shows that, while corticosteroids have proved to be lifesaving in severe to critical COVID-19 patients, its indiscriminate use has come with its price of rhino-orbito-cerebral mucormycosis epidemic, especially in India especially in patients with preexisting diabetes mellitus with higher mortality. Corticosteroid use should be monitored and all COVID-19 patients should be closely evaluated/monitored for sequelae of immunosuppression following treatment.
Journal Article
Major Contribution of Myeloid Cells In TB specific Host Gene Signature: Revelations from Re-Analysis of Publicly Available Datasets
by
Gautam, Anuradha
,
Mohapatra, Saroj Kant
,
Pandit, Bhaswati
in
Antigens
,
Cell differentiation
,
Datasets
2022
Introduction: Interaction of human host and its pathogen M.tuberculosis drives tuberculosis disease, resulting in dysregulation of host gene expression. We re-analyzed host gene expression datasets of TB to identify and validate a cellular circuit by interlinking the DEGs with their target miRNAs, GWAS hits associated with immunological phenotypes mapping to the DEGs and associated cellular subtypes through bioinformatic and experimental approaches. Methodology: DEGs were identified systematically through re-analysis of whole blood host transcriptomic datasets of treatment-naive TB patients, obtained from public repositories having at least 1.2 fold change of expression and FDR corrected p-value <0.05. Using well characterized M.tb antigens: Ag85 complex, LAM, CFP10 and ESAT6, we evaluated their effect on the expression of a subset of the top DEGs with at least two fold change of expression in a monocytic cell line THP1 with or without differentiation into a macrophage-like state with PMA and a T cell line Jurkat E6-1. Results: We discovered 305 DEGs (236 up and 69 down-regulated genes) out of which 23 (21 up and 2 down-regulated genes) were top DEGs. Overall, innate immune and myeloid cell associated pathways were enriched for up-regulated genes while T cell associated pathways were enriched for down-regulated genes. Among top DEGs, EPSTI1 was predominantly up-regulated in macrophages while SERPING1 was universally upregulated in the monocyte model by all antigens. The down-regulation of gene expression was replicated by ESAT6 in T cell line by significantly down-regulating a top down-regulated gene LRRN3. Competing Interest Statement The authors have declared no competing interest. Footnotes * Main figures moved to supplemental figures, Supplemental figures updated, The Rcode used for analysis along with the dataset has been to uploaded to Figshare and the link is provided (10.6084/m9.figshare.21215363) * https://figshare.com/articles/software/TB_host_response_zip/21215363