Výsledky vyhledávání - "John M Dennis"

Akademický článek

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study

Autor: Beverley M Shields, Bilal A Mateen, Andrew P McGovern, John M Dennis, Sebastian J Vollmer, Daniyal Raja, Rhian Hopkins, Katherine G Young, Nicholas J Thomas, James Godwin, Robert J Challen

Publikováno v: BMJ Open, Vol 14, Iss 1 (2024)

Objective This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.Design Population-based cohort study.Setting UK primary care records (Clinical Practice Research Da

Externí odkaz: https://doaj.org/article/d449e1a95edf4edf9c07de8a333b2eb9

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Akademický článek

Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis

Autor: Sebastian Vollmer, John M Dennis, Spiros Denaxas, Andrew McGovern, Nick Thomas, Bilal Akhter Mateen, Harrison Wilde, Andrew Duncan, Matt Keeling

Publikováno v: BMJ Open, Vol 11, Iss 1 (2021)

Objective In this study, we describe the pattern of bed occupancy across England during the peak of the first wave of the COVID-19 pandemic.Design Descriptive survey.Setting All non-specialist secondary care providers in England from 27 March27to 5 J

Externí odkaz: https://doaj.org/article/367213de27a640f1b9b2219a0fdb13d2

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Akademický článek

A national retrospective study of the association between serious operational problems and COVID-19 specific intensive care mortality risk.

Autor: Harrison Wilde, John M Dennis, Andrew P McGovern, Sebastian J Vollmer, Bilal A Mateen

Publikováno v: PLoS ONE, Vol 16, Iss 7, p e0255377 (2021)

ObjectivesTo describe the relationship between reported serious operational problems (SOPs), and mortality for patients with COVID-19 admitted to intensive care units (ICUs).DesignEnglish national retrospective cohort study.Setting89 English hospital

Externí odkaz: https://doaj.org/article/1760cc10cf1348c9860265654ab8a939

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Akademický článek

Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

Autor: Anita L. Lynam, John M. Dennis, Katharine R. Owen, Richard A. Oram, Angus G. Jones, Beverley M. Shields, Lauric A. Ferrat

Publikováno v: Diagnostic and Prognostic Research, Vol 4, Iss 1, Pp 1-10 (2020)

Abstract Background There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the

Externí odkaz: https://doaj.org/article/7d83a1a064234f99b9609f39f40f094e

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Akademický článek

What to do with diabetes therapies when HbA1c lowering is inadequate: add, switch, or continue? A MASTERMIND study

Autor: Andrew P. McGovern, John M. Dennis, Beverley M. Shields, Andrew T. Hattersley, Ewan R. Pearson, Angus G. Jones, On behalf of the MASTERMIND Consortium

Publikováno v: BMC Medicine, Vol 17, Iss 1, Pp 1-9 (2019)

Abstract Background It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stoppi

Externí odkaz: https://doaj.org/article/be42b9e5c5d54271b11f5eb5adf7a41a

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Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study

Autor: John M Dennis, Katherine G Young, Andrew P McGovern, Bilal A Mateen, Sebastian J Vollmer, Michael D Simpson, William E Henley, Rury R Holman, Naveed Sattar, Ewan R Pearson, Andrew T Hattersley, Angus G Jones, Beverley M Shields

Publikováno v: The Lancet Digital Health. 4:e873-e883

Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c23450a52259cbabfdfe145aed3163d8
https://doi.org/10.1016/s2589-7500(22)00174-1

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