Výsledky vyhledávání - "Deborah E Malden"

Akademický článek

Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System

Autor: Deborah E Malden, Sara Y Tartof, Bradley K Ackerson, Vennis Hong, Jacek Skarbinski, Vincent Yau, Lei Qian, Heidi Fischer, Sally F Shaw, Susan Caparosa, Fagen Xie

Publikováno v: JMIR Public Health and Surveillance, Vol 8, Iss 12, p e41529 (2022)

BackgroundNatural language processing (NLP) of unstructured text from electronic medical records (EMR) can improve the characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation of

Externí odkaz: https://doaj.org/article/624f73ba47a9409681536ec2d6c428fa

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Akademický článek

Predictors of nirmatrelvir–ritonavir receipt among COVID-19 patients in a large US health system

Autor: Deborah E. Malden, John M. McLaughlin, Vennis Hong, Joseph Lewnard, Bradley K. Ackerson, Laura Puzniak, Jeniffer S. Kim, Harpreet Takhar, Timothy B. Frankland, Jeff M. Slezak, Sara Y. Tartof

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)

Abstract A clear understanding of real-world uptake of nirmatrelvir–ritonavir for treatment of SARS-CoV-2 can inform treatment allocation strategies and improve interpretation of effectiveness studies. We used data from a large US healthcare system

Externí odkaz: https://doaj.org/article/d3fe580778384714bf7e778dfa12f3e1

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Reactions following Pfizer-BioNTech COVID-19 mRNA vaccination and related healthcare encounters among 7,077 children aged 5-11 years within an integrated healthcare system

Autor: Deborah E. Malden, Julianne Gee, Sungching Glenn, Zhuoxin Li, Cheryl Mercado, Oluwaseye A. Ogun, Sunhea Kim, Bruno J. Lewin, Bradley K. Ackerson, Amelia Jazwa, Eric S. Weintraub, Michael M. McNeil, Sara Y. Tartof

Publikováno v: Vaccine. 41:315-322

Studies combining data from digital surveys and electronic health records (EHR) can be used to conduct comprehensive assessments on COVID-19 vaccine safety.We conducted an observational study using data from a digital survey and EHR of children aged

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9080ebe13775d9e32c6513516c509dc5
https://doi.org/10.1016/j.vaccine.2022.10.079

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Hospitalization and Emergency Department Encounters for COVID-19 After Paxlovid Treatment — California, December 2021–May 2022

Autor: Deborah E. Malden, Vennis Hong, Bruno J. Lewin, Bradley K. Ackerson, Marc Lipsitch, Joseph A. Lewnard, Sara Y. Tartof

Publikováno v: MMWR. Morbidity and Mortality Weekly Report. 71:830-833

Nirmatrelvir/ritonavir (Paxlovid) is a combination protease inhibitor that blocks replication of SARS-CoV-2 (the virus that causes COVID-19) and has been shown to reduce the risk for hospitalization and death among patients with mild to moderate COVI

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d9d4a68b8e4cb1ad61b32fede2321b6
https://doi.org/10.15585/mmwr.mm7125e2

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Distribution of SARS-CoV-2 Variants in a Large Integrated Health Care System — California, March–July 2021

Autor: Sara Y. Tartof, Lei Qian, Julia E. Tubert, Michael Aragones, Katia Bruxvoort, Deborah E. Malden, Harpreet S. Takhar, Carla A. Talarico, Hung Fu Tseng, Soon Kyu Choi, Vennis Hong, Ana Florea, John M McLaughlin, Bradley Ackerson

Publikováno v: Morbidity and Mortality Weekly Report

Data from observational studies demonstrate that variants of SARS-CoV-2, the virus that causes COVID-19, have evolved rapidly across many countries (1,2). The SARS-CoV-2 B.1.617.2 (Delta) variant of concern is more transmissible than previously ident

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::beb7b7e47bb2327fdcbaf7a25191f850
https://doi.org/10.15585/mmwr.mm7040a4

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Natural Language Processing for Improved Characterization of COVID-19 Symptoms: An Observational Study of 350,000 Patients in a Large Integrated Healthcare System

Autor: Deborah E Malden, Sara Y Tartof, Bradley K Ackerson, Vennis Hong, Jacek Skarbinski, Vincent Yau, Lei Qian, Heidi Fischer, Sally F Shaw, Susan Caparosa, Fagen Xie

Publikováno v: JMIR public health and surveillance.

Background Natural language processing (NLP) of unstructured text from electronic medical records (EMR) can improve the characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::852a9564e04608784d9e19b62381c7ff
https://pubmed.ncbi.nlm.nih.gov/36446133

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Health Care Utilization in the 6 Months Following SARS-CoV-2 Infection

Autor: Sara Y. Tartof, Deborah E. Malden, In-Lu Amy Liu, Lina S. Sy, Bruno J. Lewin, Joshua T. B. Williams, Simon J. Hambidge, Jonathan D. Alpern, Matthew F. Daley, Jennifer C. Nelson, David McClure, Ousseny Zerbo, Michelle L. Henninger, Candace Fuller, Eric Weintraub, Sharon Saydah, Lei Qian

Publikováno v: JAMA Network Open. 5:e2225657

After SARS-CoV-2 infection, many patients present with persistent symptoms for at least 6 months, collectively termed post-COVID conditions (PCC). However, the impact of PCC on health care utilization has not been well described.To estimate COVID-19-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81c7db77fc6d45737eb142cdf738f52c
https://doi.org/10.1001/jamanetworkopen.2022.25657

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Body fat distribution and systolic blood pressure in 10,000 adults with whole‐body imaging: UK Biobank and Oxford BioBank

Autor: Derrick A Bennett, Ben Lacey, Jonathan Emberson, Fredrik Karpe, Naomi E. Allen, Deborah E. Malden, Sarah Lewington

Publikováno v: Obesity (Silver Spring, Md.)

Objective This study aimed to quantify the associations of regional fat mass and fat‐free mass with systolic blood pressure. Methods This analysis combined individual participant data from two large‐scale imaging studies: UK Biobank and Oxford Bi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ecb87cac21815fc220927d563a9c767
http://ora.ox.ac.uk/objects/uuid:

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