Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Jinny G. Park"'
Autor:
Keren Ladin, John Cuddeback, O. Kenrik Duru, Sharad Goel, William Harvey, Jinny G. Park, Jessica K. Paulus, Joyce Sackey, Richard Sharp, Ewout Steyerberg, Berk Ustun, David van Klaveren, Saul N. Weingart, David M. Kent
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope ha
Externí odkaz:
https://doaj.org/article/8225c57a8b2d4aebbf837ef224076579
Autor:
David van Klaveren, Theodoros P. Zanos, Jason Nelson, Todd J. Levy, Jinny G. Park, Isabel R. A. Retel Helmrich, Judith A. C. Rietjens, Melissa J. Basile, Negin Hajizadeh, Hester F. Lingsma, David M. Kent
Publikováno v:
BMC Medicine, Vol 20, Iss 1, Pp 1-11 (2022)
Abstract Background Supporting decisions for patients who present to the emergency department (ED) with COVID-19 requires accurate prognostication. We aimed to evaluate prognostic models for predicting outcomes in hospitalized patients with COVID-19,
Externí odkaz:
https://doaj.org/article/f30773149fa242248f07768295a85140
Autor:
Richard T. Carrick, Jinny G. Park, Hannah L. McGinnes, Christine Lundquist, Kristen D. Brown, W. Adam Janes, Benjamin S. Wessler, David M. Kent
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 9, Iss 16 (2020)
Background More than 500 000 sudden cardiac arrests (SCAs) occur annually in the United States. Clinical predictive models (CPMs) may be helpful tools to differentiate between patients who are likely to survive or have good neurologic recovery and th
Externí odkaz:
https://doaj.org/article/ce3917920c2847d68a3ff18ea47c1e33
Autor:
Benjamin S. Wessler, Christine M. Lundquist, Benjamin Koethe, Jinny G. Park, Kristen Brown, Tatum Williamson, Muhammad Ajlan, Zuhair Natto, Jennifer S. Lutz, Jessica K. Paulus, David M. Kent
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 8, Iss 20 (2019)
Background While many clinical prediction models (CPMs) exist to guide valvular heart disease treatment decisions, the relative performance of these CPMs is largely unknown. We systematically describe the CPMs available for patients with valvular hea
Externí odkaz:
https://doaj.org/article/4a5af5fc0afd43ea8838a701682f2455
Autor:
Melissa J. Basile, I. R. A. Retel Helmrich, Jinny G. Park, Jennifer Polo, Judith A.C. Rietjens, David van Klaveren, Theodoros P. Zanos, Jason Nelson, Hester F. Lingsma, David M. Kent, Jelmer Alsma, R. J. C. G. Verdonschot, Negin Hajizadeh
Publikováno v:
Medical Decision Making, 43(4):272989X231152852, 445-460. SAGE Publishing
Introduction Clinical prediction models (CPMs) for coronavirus disease 2019 (COVID-19) may support clinical decision making, treatment, and communication. However, attitudes about using CPMs for COVID-19 decision making are unknown. Methods Online fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2564643dd34e5cd1c31ed81dbcf0990e
https://doi.org/10.1177/0272989x231152852
https://doi.org/10.1177/0272989x231152852
Autor:
Gaurav Gulati, Jenica Upshaw, Benjamin S. Wessler, Riley J. Brazil, Jason Nelson, David van Klaveren, Christine M. Lundquist, Jinny G. Park, Hannah McGinnes, Ewout W. Steyerberg, Ben Van Calster, David M. Kent
Publikováno v:
Circulation. Cardiovascular quality and outcomes, 15(4). Lippincott Williams & Wilkins
Circulation: Cardiovascular Quality and Outcomes, 15(4), 248-260. LIPPINCOTT WILLIAMS & WILKINS
Circulation: Cardiovascular Quality and Outcomes, 15(4), 248-260. LIPPINCOTT WILLIAMS & WILKINS
Background: While clinical prediction models (CPMs) are used increasingly commonly to guide patient care, the performance and clinical utility of these CPMs in new patient cohorts is poorly understood. Methods: We performed 158 external validations o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8e94d7c7354ce59209287e283a8fd5f
https://doi.org/10.1161/circoutcomes.121.008487
https://doi.org/10.1161/circoutcomes.121.008487
Autor:
David van Klaveren, Gowri Raman, Benjamin S. Wessler, David M. Kent, Ewout W. Steyerberg, Lester Y. Leung, Rehab Salah, Jason Nelson, Benjamin Koethe, Jinny G. Park, Esmee Venema, Jessica K. Paulus
Publikováno v:
Journal of Clinical Epidemiology, 138, 32-39. ELSEVIER SCIENCE INC
Journal of Clinical Epidemiology, 138, 32-39. Elsevier Inc.
Journal of Clinical Epidemiology, 138, 32-39. Elsevier Inc.
Objective: To assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation. Study Design and Setting: We evalua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55afcfc18abbb85b9c884bb4a25abb9e
http://hdl.handle.net/1887/3277513
http://hdl.handle.net/1887/3277513
Autor:
Esmee Venema, Christine Lundquist, Ben Van Calster, David van Klaveren, Gaurav Gulati, Rebecca E.H. Maunder, Jinny G. Park, Jason Nelson, Ewout S. Steyerberg, Riley Brazil, David M. Kent, Benjamin S. Wessler, Hannah L. McGinnes, Jenica N. Upshaw, Jessica K. Paulus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::905cac68451aa34cdc0db86a9e73580e
https://doi.org/10.25302/09.2021.me.160635555
https://doi.org/10.25302/09.2021.me.160635555
Autor:
Jason Nelson, Hannah L. McGinnes, Benjamin S. Wessler, D. van Klaveren, Esmee Venema, Gaurav Gulati, David M. Kent, Jessica K. Paulus, Jinny G. Park, Riley Brazil, Ben Van Calster, Ewout W. Steyerberg
Publikováno v:
Circulation: Cardiovascular Quality and Outcomes, 14(8). LIPPINCOTT WILLIAMS & WILKINS
Circulation. Cardiovascular Quality and Outcomes
Circulation. Cardiovascular Quality and Outcomes
Supplemental Digital Content is available in the text.
Background: There are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been ext
Background: There are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been ext
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a0a680c39cae170a23b09b09ba72981
http://hdl.handle.net/1887/3277507
http://hdl.handle.net/1887/3277507
Autor:
Hannah L. McGinnes, Benjamin S. Wessler, Ewout W. Steyerberg, Jenica N. Upshaw, James E. Udelson, Jinny G. Park, Jason Nelson, van Klaveren D, Benjamin Koethe, Van Calster B, Marvin A. Konstam, David M. Kent
BackgroundMost heart failure (HF) clinical prediction models (CPMs) have not been externally validated.MethodsWe performed a systematic review to identify CPMs predicting outcomes in HF, stratified by acute and chronic HF CPMs. External validations w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31ea160cea6fb6ffca11a9902c97190a
https://doi.org/10.1101/2021.01.31.21250875
https://doi.org/10.1101/2021.01.31.21250875