Splenium of the Corpus Callosum Infarct Associated With COVID-19: Case Report.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has been recently associated with infarction of the central splenium of the corpus callosum. These are described as cytotoxic lesions, and imaging rarely reveals enhancement. They have not been described in the body or head of the corpus callosum. Few diseases affect the corpus callosum, but the most common include multiple sclerosis, aquaporin-4 disease, and Susac syndrome. There is also emerging literature on Mild Encephalopathy with Reversible Splenial lesions associated with central and not basal lesions. The reason for the location of these lesions in acute COVID-19 infection is unknown. CASE REPORT: A 22-year-old female presented to the ED for altered mental status after being found down. A brief history review indicated that the patient had been altered for 2-3 days before being found naked and covered in her own feces and urine by her family after they had not heard from her. As she lived alone, a clear history of the events preceding her admission remains unclear. On initial assessment, the patient was found to be somnolent and nonverbal, though she could follow simple commands. On admission, testing for SARS CoV-2 RNA PCR was positive. Patient was admitted to the hospital for further work up to determine the cause of the altered mental status. CONCLUSION: We present a new case of a young woman who developed a central splenium lesion during acute COVID-19 infection and explain the predilection for the callosum in these patients, as well as literature to show that COVID-19 was most likely the cause.

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning.

SIGNIFICANCE: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. AIM: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. APPROACH: We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection. RESULTS: We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. CONCLUSION: These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.