Stuart J McGurnaghan
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Explore the profile of Stuart J McGurnaghan including associated specialties, affiliations and a list of published articles.
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38
Citations
681
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Recent Articles
1.
Roshandel D, Spiliopoulou A, McGurnaghan S, Iakovliev A, Lipschutz D, Hayward C, et al.
Diabetes
. 2024 Nov;
74(2):223-233.
PMID: 39556808
Identified genetic loci for C-peptide and type 1 diabetes (T1D) age at diagnosis (AAD) explain only a small proportion of their variation. We aimed to identify additional genetic loci associated...
2.
Magliano D, Chen L, Morton J, Salim A, Carstensen B, Gregg E, et al.
Lancet Diabetes Endocrinol
. 2024 Nov;
12(12):915-923.
PMID: 39541997
Background: Population-based incidence data on young-adult-onset type 1 diabetes and type 2 diabetes are limited. We aimed to examine secular trends in the incidence of diagnosed type 1 diabetes and...
3.
Greene C, Blackbourn L, McGurnaghan S, Mercer S, Smith D, Wild S, et al.
Br J Clin Pharmacol
. 2024 Jul;
90(11):2802-2810.
PMID: 38981672
Aims: Prescribing of antidepressant and antipsychotic drugs in general populations has increased in the United Kingdom, but prescribing trends in people with type 2 diabetes (T2D) have not previously been...
4.
McGurnaghan S, McKeigue P, Blackbourn L, Mellor J, Caparrotta T, Sattar N, et al.
Diabetes Care
. 2024 Jun;
47(8):1342-1349.
PMID: 38889071
Objective: In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim...
5.
Berthon W, McGurnaghan S, Blackbourn L, Mellor J, Gibb F, Heller S, et al.
Diabetes Res Clin Pract
. 2024 Mar;
210:111642.
PMID: 38548109
Aims: We examined severe hospitalised hypoglycaemia (SHH) rates in people with type 1 and type 2 diabetes in Scotland during 2016-2022, stratifying by sociodemographics. Methods: Using the Scottish National diabetes...
6.
Ter Braake J, Fleetwood K, Vos R, Blackbourn L, McGurnaghan S, Wild S, et al.
Diabetologia
. 2024 Feb;
67(6):1029-1039.
PMID: 38409440
Aims/hypothesis: The aim of this study was to compare cardiovascular risk management among people with type 2 diabetes according to severe mental illness (SMI) status. Methods: We used linked electronic...
7.
Mellor J, Jiang W, Fleming A, McGurnaghan S, Blackbourn L, Styles C, et al.
Br J Ophthalmol
. 2024 Feb;
108(6):833-839.
PMID: 38316534
Background/aims: National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL)...
8.
Berthon W, McGurnaghan S, Blackbourn L, Bath L, McAllister D, Stockton D, et al.
Diabetes Care
. 2023 Dec;
47(3):e26-e28.
PMID: 38113438
No abstract available.
9.
Fleming A, Mellor J, McGurnaghan S, Blackbourn L, Goatman K, Styles C, et al.
Br J Ophthalmol
. 2023 Sep;
108(7):984-988.
PMID: 37704266
Background/aims: Support vector machine-based automated grading (known as iGradingM) has been shown to be safe, cost-effective and robust in the diabetic retinopathy (DR) screening (DES) programme in Scotland. It triages...
10.
Mellor J, Jiang W, Fleming A, McGurnaghan S, Blackbourn L, Styles C, et al.
Int J Med Inform
. 2023 May;
175:105072.
PMID: 37167840
Aims: This study's objective was to evaluate whether deep learning (DL) on retinal photographs from a diabetic retinopathy screening programme improve prediction of incident cardiovascular disease (CVD). Methods: DL models...