No abstract

No abstract

Clinicians around the world are experiencing skin breakdown due to the prolonged usage of masks while working long hours to treat patients with COVID-19. The skin damage is a result of the increased friction and pressure at the mask-skin barrier. Throughout the COVID-19 pandemic, clinicians have been applying various skin barriers to prevent and ameliorate skin breakdown. However, there are no studies to our knowledge that assess the safety and efficacy of using these skin barriers without compromising a sufficient mask-face seal. We report the largest study to date of various skin barriers and seal integrity with quantitative fit testing (QNFT). Our pilot study explores whether the placement of a silicone scar sheet (ScarAway®), Cavilon™, or Tegaderm™ affects 3M™ half-face mask respirator barrier integrity when compared to no barrier using QNFT. We collected data from nine clinicians at an academic Level 1 trauma center in New Jersey. We found that the silicone scar sheet resulted in the lowest adequate fit while Cavilon™ provided the highest fit factor when compared to other interventions (p<0.05). Our findings help inform clinicians considering barriers for comfort when wearing facemasks during the COVID-19 pandemic and for future pandemics.

No abstract

No abstract

Central nervous system infections in immunosuppressed patients are rare but potentially lethal complications that require swift diagnoses and intervention. While the differential diagnosis for new lesions on neuroradiological imaging of immunosuppressed patients typically includes infections and neoplasms, image-based heuristics to differentiate the two has been shown to have variable reliability.The authors describe 2 rare CNS infections in immunocompromised patients with atypical physical and radiological presentations. In the first case, a 59-year-old man, who had recently undergone a renal transplantation, was found to have multifocal Nocardia amikacinitolerans abscesses masquerading as neoplasms on diffusion-weighted imaging (DWI); in the second case, a 33-year-old man with suspected recurrent Hodgkin’s lymphoma was found to have a nonpyogenic abscess with cytomegalovirus (CMV) encephalitis.As per review of the literature, this appears to be the first case of brain abscess caused by N. amikacinitolerans, a recently isolated superbug. Despite confirmation through brain biopsy later on in case 1, the initial radiological appearance was atypical, showing subtle diffusion restriction on DWI. Similarly, the authors present a case of CMV encephalitis that presented as a ring-enhancing lesion, which is extremely rare. Both cases draw attention to the reliability of neuroimaging in differentiating an abscess from a neoplasm.

No abstract

BackgroundFollowing mild traumatic brain injury (mTBI) compromised white matter structural integrity can result in alterations in functional connectivity of large-scale brain networks and may manifest in functional deficit including cognitive dysfunction. Advanced magnetic resonance neuroimaging techniques, specifically diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI), have demonstrated an increased sensitivity for detecting microstructural changes associated with mTBI. Identification of novel imaging biomarkers can facilitate early detection of these changes for effective treatment. In this study, we hypothesize that feature selection combining both structural and functional connectivity increases classification accuracy.Methods16 subjects with mTBI and 20 healthy controls underwent both DTI and resting state functional imaging. Structural connectivity matrices were generated from white matter tractography from DTI sequences. Functional connectivity was measured through pairwise correlations of rs-fMRI between brain regions. Features from both DTI and rs-fMRI were selected by identifying five brain regions with the largest group differences and were used to classify the generated functional and structural connectivity matrices, respectively. Classification was performed using linear support vector machines and validated with leave-one-out cross validation.ResultsGroup comparisons revealed increased functional connectivity in the temporal lobe and cerebellum as well as decreased structural connectivity in the temporal lobe. After training on structural connections only, a maximum classification accuracy of 78% was achieved when structural connections were selected based on their corresponding functional connectivity group differences. After training on functional connections only, a maximum classification accuracy of 69% was achieved when functional connections were selected based on their structural connectivity group differences. After training on both structural and functional connections, a maximum classification accuracy of 69% was achieved when connections were selected based on their structural connectivity.ConclusionsOur multimodal approach to ROI selection achieves at highest, a classification accuracy of 78%. Our results also implicate the temporal lobe in the pathophysiology of mTBI. Our findings suggest that white matter tractography can serve as a robust biomarker for mTBI when used in tandem with resting state functional connectivity.