This study assessed the risk factors driving the epidemic of COVID-19 associated mucormycosis (COVID-Mucor) in Indiathat accompanied the COVID-19 pandemic, particularly the second wave. We analysed the risk factors among 164 participants:132 COVID-Mucor(cases) and 32 non-COVID-Mucor(controls)using the data from a prospective cohort study of mucormycosis over oneyear. Diabetes mellitus remained a pivotal risk factor in both groups (97%) while uncontrolled diabetes mellitus (OR: 4.6; p=0.026)and newly detected diabetes (OR: 3.3; p=0.018), werecommoneramong the cases. Most patients with COVID-Mucor had mild COVID-19. Steroid use, often unwarranted, was highly associated with COVID-Mucorafter adjusting for other risk factors (OR 28.4; P 0.001). Serum ferritin was significantly higher(p=0.041), while C-reactive protein was not, suggesting that alterations in iron metabolism probably predispose to COVID-Mucor. Oxygen was used only in a small minority of patients with COVID-Mucor. The in-hospital mortality in both groups was low. In conclusion, the Indian COVID-Mucorepidemic was likely driven by a convergence of interlinked risk factors –uncontrolled diabetes mellitus, unwarranted steroid use, and perhapsCOVID-19 itself. Appropriate steroid use in patients with severe COVID-19 and screening and optimal control of hyperglycaemia can prevent COVID-Mucor.

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Objectives: Assess reliability of oxygen desaturation index (ODI) as an alternative parameter to apnea hypopnea index (AHI) in screening patients with severe obstructive sleep apnea (OSA). Material and Methods: Retrospectively two-year data on demography, anthropometric features, polysomnography (PSG) parameters [AHI, ODI, minimum oxygen saturation (SpO2), mean SpO2], and Epworth sleepiness score (ESS) were collected and analyzed. Results: Study showed significant correlation of ESS with AHI, ODI, apnea-hypopnea percentage of sleep period time (AH%SPT), mean SpO2 and minimum SpO2 with highest correlation being with AHI. A Cohen's weighted Kappa analysis showed good concordance of 87.32% between AHI and ODI in classifying severity of OSA, with a significant R 2 correlation of 0.84 on linear regression. An ODI>20 has a sensitivity of 96.6% and specificity of 69.6% in diagnosing severe OSA. Conclusion: Good concordance between AHI and ODI makes nocturnal oximetry a less expensive tool to confidently screen patients with severe OSA.

The eustachian tube inflation-deflation test is a sensitive test for predicting aditus patency in patients with dry ears but less so in patients with discharging ears. Hence, it could be used in the former to avoid unnecessary exploration of the mastoid.