Zobrazeno 1 - 10
of 21
pro vyhledávání: '"JASON E. BLACK"'
Publikováno v:
Endocrinology, Diabetes & Metabolism, Vol 5, Iss 4, Pp n/a-n/a (2022)
Abstract Introduction Americans with diabetes are clinically vulnerable to worse COVID‐19 outcomes; thus, insight into how to prevent infection is imperative. Using longitudinal, prospective data from the real‐world iNPHORM study, we identify the
Externí odkaz:
https://doaj.org/article/1060c1c586014df7aeb31ea61f8a8d6d
Publikováno v:
International Journal of Population Data Science, Vol 6, Iss 1 (2021)
Introduction The ability to estimate risk of multimorbidity will provide valuable information to patients and primary care practitioners in their preventative efforts. Current methods for prognostic prediction modelling are insufficient for the estim
Externí odkaz:
https://doaj.org/article/9118e974e06940c8ab1c0509bbc84042
Autor:
Alexandria Ratzki-Leewing, Bridget L Ryan, Guangyong Zou, Susan Webster-Bogaert, Jason E Black, Kathryn Stirling, Kristina Timcevska, Nadia Khan, John D Buchenberger, Stewart B Harris
Publikováno v:
JMIR Research Protocols, Vol 11, Iss 2, p e33726 (2022)
BackgroundHypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. ObjectiveThis protocol describes the design and impleme
Externí odkaz:
https://doaj.org/article/86ae8926752a431a8dc37cb73853d35a
Publikováno v:
Family practice.
Classification and prediction tasks are common in health research. With the increasing availability of vast health data repositories (e.g. electronic medical record databases) and advances in computing power, traditional statistical approaches are be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e598abee063bfd28290e2dc550758e1
https://pubmed.ncbi.nlm.nih.gov/36181463
https://pubmed.ncbi.nlm.nih.gov/36181463
Autor:
ALEXANDRIA RATZKI-LEEWING, STEWART B. HARRIS, JASON E. BLACK, GUANGYONG ZOU, SUSAN WEBSTER-BOGAERT, BRIDGET L. RYAN
Publikováno v:
Diabetes. 71
Most prediction models for diabetes-related iatrogenic severe hypoglycemia (SH) have derived from trial/administrative records subject to poor generalizability, ascertainment bias, and incomplete data capture. Redressing this gap, iNPHORM leveraged t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b941dec832235ae5e0ee27072288e22
https://doi.org/10.2337/db22-372-p
https://doi.org/10.2337/db22-372-p
Autor:
ALEXANDRIA RATZKI-LEEWING, STEWART B. HARRIS, JASON E. BLACK, GUANGYONG ZOU, SUSAN WEBSTER-BOGAERT, BRIDGET L. RYAN
Publikováno v:
Diabetes. 71
Iatrogenic non-severe hypoglycemia (NSH) is a common and known precursor of severe hypoglycemia. Still, virtually no valid risk estimators exist to predict daytime and nocturnal NSH (NSDH, NSNH) in the general US population with diabetes. To redress
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ca84d7ba0a6d1e2e3e20d1f757d3142
https://doi.org/10.2337/db22-371-p
https://doi.org/10.2337/db22-371-p
Autor:
Alexandria Ratzki-Leewing, Bridget L Ryan, Guangyong Zou, Susan Webster-Bogaert, Jason E Black, Kathryn Stirling, Kristina Timcevska, Nadia Khan, John D Buchenberger, Stewart B Harris
Publikováno v:
JMIR research protocols. 11(2)
BACKGROUND Hypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. OBJECTIVE This protocol describes the design and implem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1425800c7215ee0994b4ea4538344f62
https://pubmed.ncbi.nlm.nih.gov/35025756
https://pubmed.ncbi.nlm.nih.gov/35025756
Autor:
John D Buchenberger, Jason E. Black, Bridget L. Ryan, Joseph W Dickens, Stewart B. Harris, Alexandria Ratzki-Leewing
Publikováno v:
BMJ Open
BMJ Open, Vol 11, Iss 9 (2021)
Family Medicine Publications
BMJ Open, Vol 11, Iss 9 (2021)
Family Medicine Publications
Main objectiveTo determine how and to what extent COVID-19 has affected real-world, self-reported glycaemic management in Americans with type 1 or type 2 diabetes taking insulin and/or secretagogues, with or without infection.DesignA cross-sectional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f2da14e13fb47b8d1f508066ad4c67c
http://europepmc.org/articles/PMC8413474
http://europepmc.org/articles/PMC8413474
Publikováno v:
Diabetes. 70
Background: Individual and societal determinants can affect the need and propensity for healthcare utilization (HCU) following diabetes-related severe hypoglycemia (SH). This is the first US study to explore the real-world risk factors of HCU- versus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed0805e38ced2bc83f104aebbc84407d
https://doi.org/10.2337/db21-347-p
https://doi.org/10.2337/db21-347-p
Publikováno v:
International journal of medical informatics. 141
Background We developed and evaluated a prognostic prediction model that estimates osteoarthritis risk for use by patients and practitioners that is designed to be appropriate for integration into primary care health information technology systems. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2db1694bf51d40d119a71d27ee48360d
https://pubmed.ncbi.nlm.nih.gov/32593009
https://pubmed.ncbi.nlm.nih.gov/32593009