Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Matthew, Churpek"'
Autor:
Preeti Gupta, Anoop Mayampurath, Tim Gruenloh, Madeline Oguss, Askar Safipour Afshar, Michael Spigner, Megan Gussick, Matthew Churpek, Todd Lee, Majid Afshar
Publikováno v:
BMC Emergency Medicine, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Substance misuse poses a significant public health challenge, characterized by premature morbidity and mortality, and heightened healthcare utilization. While studies have demonstrated that previous hospitalizations and emergency
Externí odkaz:
https://doaj.org/article/e8dce0e9a8f34160ba9c071bc1df6f8e
Autor:
Preeti Gupta, Anoop Mayampurath, Tim Gruenloh, Madeline Oguss, Askar Safipour Afshar, Michael Spigner, Megan Gussick, Matthew Churpek, Todd Lee, Majid Afshar
Publikováno v:
BMC Emergency Medicine, Vol 24, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/d5b8e62215724a6c8f0fc3ddb03a0a5b
Autor:
David E. Arnolds, Kyle A. Carey, Lena Braginsky, Roxane Holt, Dana P. Edelson, Barbara M. Scavone, Matthew Churpek
Publikováno v:
BMC Pregnancy and Childbirth, Vol 22, Iss 1, Pp 1-9 (2022)
Abstract Background Early warning scores are designed to identify hospitalized patients who are at high risk of clinical deterioration. Although many general scores have been developed for the medical-surgical wards, specific scores have also been de
Externí odkaz:
https://doaj.org/article/78c5200b683449fea37694f64e5c2380
Autor:
Ahmed Arshad, MD, Catherine Blandon, MS, Kyle Carey, MPH, Philip Verhoef, MD, PhD, Priti Jani, MD, MPH, Samuel Volchenboum, MD, PhD, Matthew Churpek, MD, MPH, PhD, Anoop Mayampurath, PhD
Publikováno v:
Critical Care Explorations, Vol 4, Iss 10, p e0765 (2022)
OBJECTIVE:. PICU patients who experience critical illness events, such as intubation, are at high risk for morbidity and mortality. Little is known about the impact of these events, which require significant resources, on outcomes in other patients.
Externí odkaz:
https://doaj.org/article/a58943d4c4ed4d66a4069eccc3a4df83
Autor:
Mejalli Al-Kofahi, Alexandra Spicer, Richard S. Schaefer, Andrea Uhl, Matthew Churpek, Sushant Govindan
Publikováno v:
American Journal of Medical Quality. 38:147-153
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe3888f4de3795058b0c9c6ec02e5e34
https://doi.org/10.1097/jmq.0000000000000123
https://doi.org/10.1097/jmq.0000000000000123
Autor:
Oguzhan Alagoz, Ajay K Sethi, Brian W Patterson, Matthew Churpek, Ghalib Alhanaee, Elizabeth Scaria, Nasia Safdar
Publikováno v:
PLoS ONE, Vol 16, Iss 7, p e0254456 (2021)
IntroductionVaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the sp
Externí odkaz:
https://doaj.org/article/af9194e01d444ec3bfc614ce5d7675bc
Autor:
Saket Girotra, Philip G. Jones, Mary Ann Peberdy, Mary S. Vaughan-Sarrazin, Paul S. Chan, Paul Chan, Anne Grossestreuer, Ari Moskowitz, Dana Edelson, Joseph Ornato, Matthew Churpek, Michael Kurz, Monique Anderson Starks, Sarah Perman, Zachary Goldberger
Publikováno v:
Circulation. Cardiovascular quality and outcomes. 15(9)
Background: Although rapid response teams have been widely promoted as a strategy to reduce unexpected hospital deaths, most studies of rapid response teams have not adjusted for secular trends in mortality before their implementation. We examined wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b03ea5b007ba2ae065ce1acd3cbe577
https://pubmed.ncbi.nlm.nih.gov/36065818
https://pubmed.ncbi.nlm.nih.gov/36065818
Autor:
Anoop, Mayampurath, Fereshteh, Bashiri, Raffi, Hagopian, Laura, Venable, Kyle, Carey, Dana, Edelson, Matthew, Churpek
Publikováno v:
Resuscitation. 178:55-62
Machine learning models are more accurate than standard tools for predicting neurological outcomes in patients resuscitated after cardiac arrest. However, their accuracy in patients with Coronavirus Disease 2019 (COVID-19) is unknown. Therefore, we c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4bb0a67901a992c7f0f77f4d973f682
https://doi.org/10.1016/j.resuscitation.2022.07.018
https://doi.org/10.1016/j.resuscitation.2022.07.018
Autor:
Lara L. Roessler, Mathias J. Holmberg, Rahul D. Pawar, Annmarie T. Lassen, Ari Moskowitz, Anne Grossestreuer, Dana Edelson, Joseph Ornato, Mary Ann Peberdy, Matthew Churpek, Michael Kurz, Monique Anderson Starks, Paul Chan, Saket Girotra, Sarah Perman, Zachary Goldberger
Publikováno v:
Chest. 162:569-577
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9605a99d1dfd6d251c84f0b6352e6770
https://doi.org/10.1016/j.chest.2022.03.015
https://doi.org/10.1016/j.chest.2022.03.015
Publikováno v:
PLoS ONE, Vol 14, Iss 7, p e0220640 (2019)
BackgroundDeep learning algorithms have achieved human-equivalent performance in image recognition. However, the majority of clinical data within electronic health records is inherently in a non-image format. Therefore, creating visual representation
Externí odkaz:
https://doaj.org/article/9944bc58f8634e699bf88445f8969942