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Neuro-mucormycosis: Lessons from COVID-19-associated cases
Nahad Sedaghat1, Masoud Etemadifar2, Pouria Ghasemi1
1Alzahra Research Institute, Alzahra University Hospital, Isfahan University of Medical Sciences, Isfahan, Iran.
Abstract:
Background: Scarce data are available on the neurological presentations of coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) and COVID-19-unrelated rhino-orbito-cerebral mucormycosis (ROCM). This study aimed to compare the neurological presentations and their associated outcomes in patients with CAM and COVID-19-unrelated ROCM. Methods: In December 2021, a case-control analysis was conducted on the CAM (case group) and COVID-19-unrelated ROCM (control group) referrals of one center in Isfahan, Iran. Confirmed CAM patients from January 2020 to December 2021 constituted the case group, and patients with COVID-19-unrelated ROCM from 2016-2019 constituted the control group. Their data were then analyzed using proper (non) parametric tests and generalized linear models (GLM), therein P-value below 0.05 was considered as the criterion of statistical significance, and the SPSS software was used. Results: After retrieving data on 177 patients with mucormycosis, 78 patients with CAM were included as the case group and 72 patients with COVID-19-unrelated ROCM were included as the control group. Neurological presentations suggestive of second, third, and eighth cranial nerve involvement were more prevalent in the CAM group (all with P < 0.05). The mortality rate in the CAM group was 1.9 times that of the controls (P = 0.01), being explained by higher extent of corticosteroid administration among them. Higher age and presentation with gait ataxia, ptosis, and mydriasis were considered to be predictive of poor prognosis in patients with CAM (all with P < 0.05). Conclusion: The neurological manifestations of CAM differ from COVID-19-unrelated ROCM based on the presented results, some of which are associated with poor prognosis. Further replication is warranted to confirm our retrospective analyses.
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