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Background: Advances in computational methodologies have enabled processing of large datasets originating from imaging studies. However, most imaging biomarkers suffer from a lack of direct links with underlying biology, as they are only observationally correlated with pathophysiology. Purpose(s): To develop and validate a novel AI-assisted image analysis platform, by applying quantitative radiotranscriptomics that quantifies cytokinedriven vascular inflammation from routine CT angiograms (CTA) performed as part of clinical care in COVID-19. Method(s): We used this platform to train the radiotranscriptomic signature C19-RS, derived from the perivascular space around the aorta and the internal mammary artery in routine chest CTAs, to best describe cytokinedriven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies (A). This signature was validated externally in 358 clinically indicated CT pulmonary angiograms from patients with or without COVID-19 from 3 different geographical regions. Result(s): First, 22 patients who had a CTA before the pandemic underwent repeat CTA <6 months post COVID-19 infection (B). Compared with 22 controls (matched for age, gender, and BMI) C19-RS was increased only in the COVID-19 group (C). Next, C19-RS was calculated in a cohort of 331 patients hospitalised during the pandemic, and was higher in COVID-19 positives (adjusted OR=2.97 [95% CI: 1.43-6.27], p=0.004, D). C19-RS had prognostic value for in-hospital mortality in COVID-19, with HR=3.31 ([95% CI: 1.49-7.33], p=0.003) and 2.58 ([95% CI: 1.10-6.05], p=0.028) in two testing cohorts respectively (E, F), adjusted for clinical factors and biochemical biomarkers of inflammation and myocardial injury. The corrected HR for in-hospital mortality was 8.24 [95% CI: 2.16-31.36], p=0.002 for those who received no treatment with dexamethasone, but only 2.27 [95% CI: 0.69-7.55], p=0.18 in those who received dexamethasone subsequently to the C19-RS based image analysis, suggesting that vascular inflammation may have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0.61, p=0.0003) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. Conclusion(s): We present the first proof of concept study that combines transcriptomics with radiomics to provide a platform for the development of machine learning derived radiotranscriptomics analysis of routine clinical CT scans for the development of non-invasive imaging biomarkers. Application in COVID-19 produced C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation, that predicts inhospital mortality and identifies people who will have better response to anti-inflammatory treatments, allowing targeted therapy. This AI-assisted image analysis platform may have applications across a wide range of vascular diseases, from infections to autoimmune diseases.
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Methods: A survey was designed using Survey Monkey to query faculty regarding measures of stress and burnout related to both remote teaching and on campus teaching. A fivepoint Likert scale was used to garner respondents' reactions to 21 closed ended questions. The anonymous, confidential survey link was sent by email to faculty at three chiropractic programs. Respondents were instructed to reflect on March 2020 to March 2021 when completing the survey. Results: The survey request yielded 36 respondents. The majority of respondents, 66%, worked partially at home and partially on campus, while 26% worked entirely from home and 8% entirely on campus. In addition to work responsibilities, 31% of respondents were educating children at home. Nearly 2/3 of respondents (61%), indicated that they did not stop working at the end of the workday and 47% indicated that they felt stressed at work. However, 72% of respondents indicated that they were able to create a productive learning environment for students. While only 17% of respondents agreed that working with students remotely was energizing, most (70%) did not feel students blamed them for issues experienced during remote learning. Background: The purpose of this study was to examine the effect of moving to emergency remote teaching due to the COVID-19 pandemic on chiropractic college faculty. The job of a faculty member has always included demands. Stress can lead to occupational burnout, defined by the World Health Organization (WHO) in 2019 as “a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed.” Conclusion: Chiropractic faculty variably experienced stress during the height of the COVID-19 pandemic. This may be due to working remotely and an absence of separation of home and work life. Despite the stressors felt surrounding teaching and work, faculty created a positive learning environment for students.
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This study details research currently underway exploring the perceived roles that higher education instructors embody during the COVID-19 pandemic. Of interest to this study-up research, are the ways that instructors evaluate themselves as they pivot from previous modalities into emergency remote instruction and how their response provides insights into emergency continuity strategies. Through teleconferenced interviews, perspectives are transcribed, qualitatively coded through two coding cycles, culminating in an inductively derived insights that provide guidance to instructors and institutions. © 2020 Owner/Author.