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Your search keyword '"Melissa Haendel"' showing total 5 results
Start Over Author "Melissa Haendel" Publisher springer science and business media llc
5 results on '"Melissa Haendel"'

1. Biomonitoring and precision health in deep space supported by artificial intelligence

Author

Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Hector Garcia Martin, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers, Charlotte Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, and Sylvain V. Costes

Subjects
Human-Computer Interaction, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Software
Published
2023
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2. Biological research and self-driving labs in deep space supported by artificial intelligence

Author

Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Hector Garcia Martin, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers, Charlotte Nelson, Jonathan Oribello, Seung-min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, and Sylvain V. Costes

Subjects
Human-Computer Interaction, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Software
Published
2023
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3. NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study

Author

Ben Coleman, Peter N. Robinson, Emily Pfaff, Rachel Deer, Katie Rebecca Bradwell, Andrew E. Williams, Nomi L. Harris, Tommaso Fontana, Heidi Spratt, Giorgio Valentini, Melissa Haendel, Luca Cappelletti, Jasvinder Singh, Richard A. Moffitt, Christopher J. Mungall, Lauren Chan, Justin T. Reese, Elena Casiraghi, Christopher G. Chute, Tiffany J. Callahan, Julie A McMurry, and Guy Karlebach

Subjects
medicine.medical_specialty, Kidney Disease, NSAIDs, Anti-Inflammatory Agents, Microbiology, Cyclooxygenase inhibitors, Cohort Studies, COVID-19 Testing, Community-acquired pneumonia, Clinical Research, Internal medicine, Observational study, Virology, medicine, Humans, Adverse effect, Pandemics, Retrospective Studies, Aspirin, Respiratory tract infections, Proportional hazards model, business.industry, Prevention, Anti-Inflammatory Agents, Non-Steroidal, COVID-19, Odds ratio, Acute Kidney Injury, medicine.disease, Acetaminophen, Good Health and Well Being, Infectious Diseases, Medical Microbiology, Cohort, business, Non-Steroidal, medicine.drug
Abstract

Background Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. Methods A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. Results Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53–0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47–0.56), invasive ventilation (OR: 0.59 95% CI: 0.55–0.64), AKI (OR: 0.67 95% CI: 0.63–0.72), or ECMO (OR: 0.51 95% CI: 0.36–0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. Conclusions Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

Published
2022
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4. Modularization for the Cell Ontology

Author

Christopher Mungall, Carlo Torniai, Alexander Diehl, Melissa Haendel, Amelia Ireland, Shahid Manzoor, Terry Meehan, and David Osumi-Sutherland

Subjects
General Materials Science
Published
2011
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