TY - JOUR
T1 - iDiabetes platform - enhanced phenotyping of patients with diabetes for precision diagnosis, prognosis and treatment
T2 - study protocol for a cluster-randomised controlled study in Tayside, Scotland
AU - Lin, Yeun Yi
AU - Leith, Damien
AU - Abbott, Michael
AU - Barrett, Rachael
AU - Bell, Samira
AU - Croudace, Tim J.
AU - Cunningham, Scott
AU - Dillon, John
AU - Donnan, Peter
AU - Farre, Albert
AU - Hernández, Rodolfo
AU - Lang, Chim
AU - Mckenzie, Stephanie
AU - Mordi, Ify
AU - Morrow, Susan
AU - Munro, Cameron
AU - Philip, Sam
AU - Ryan, Mandy
AU - Wake, Deborah
AU - Wang, Huan
AU - Win, Mya
AU - Pearson, Ewan
AU - iDiabetes Study Team
AU - Doney, Alex
AU - Taylor, Andrew
AU - Barnett, Anna
AU - Allardice, Brian
AU - Schofield, Christopher
AU - Andrews, Claire
AU - Palmer, Colin
AU - Baty, David
AU - Kidd, Doug
AU - Dow, Ellie
AU - Riches, Emma
AU - Middleton, Erin
AU - Anyebe, Evelyn
AU - Francis, Jacob
AU - Digby, Jayne
AU - McLean, Joanne
AU - Wilson, Karen
AU - Moonie, Lewis
AU - Tosh, Gerry
AU - Bremner, Louise
AU - Donnelly, Louise
AU - Andrew, Nicola
AU - Brennan, Paul
AU - McCrimmon, Rory
AU - Petty, Russell
AU - Boyd, Simon
AU - Srinivasan, Sundar
AU - O'Rourke, Tegwen
N1 - Funding: This work was supported by Chief Scientist Office, Scotland (grant number: PMAS-21-01).Published by BMJ.
PY - 2024/11/28
Y1 - 2024/11/28
N2 - Introduction and aim Diabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care. We aim to develop a digital platform called 'intelligent Diabetes' (iDiabetes) to support a precision diabetes care model in Scotland and assess its impact on the primary composite outcome of all-cause mortality, hospitalisation rate, renal function decline and glycaemic control.
Methods and analysis The impact of iDiabetes will be evaluated through a cluster-randomised controlled study, recruiting up to 22 500 patients with diabetes. Primary care general practices (GPs) in the National Health Service (NHS) Scotland Tayside Health Board are the units (clusters) of randomisation. Each primary care GP will form one cluster (approximately 400 patients per cluster), with up to 60 clusters recruited. Randomisation will be to iDiabetes (guideline support), iDiabetesPlus or usual diabetes care (control arm). Patients of participating primary care GPs are automatically enrolled on the study when they attend for their annual diabetes screening or are newly diagnosed with diabetes. A composite hierarchical primary outcome, evaluated using Win-Ratio statistical methodology, will consist of (1) all-cause mortality, (2) all-cause hospitalisation rate, (3) proportion with >40% estimated glomerular filtration rate [eGFR] reduction from baseline or new development of end-stage renal disease, (4) proportion with absolute HbA1C reduction >0.5%. Outcomes will be evaluated after a 2-year median follow-up period. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform.
Ethics and dissemination This study was reviewed by the NHS Health Research Authority and approved by the East of Scotland Research Ethics Committee (reference: 23/ES/0008). Study findings will be disseminated via publications, presented at scientific conferences and shared with patients and the public on the study website and social media.
AB - Introduction and aim Diabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care. We aim to develop a digital platform called 'intelligent Diabetes' (iDiabetes) to support a precision diabetes care model in Scotland and assess its impact on the primary composite outcome of all-cause mortality, hospitalisation rate, renal function decline and glycaemic control.
Methods and analysis The impact of iDiabetes will be evaluated through a cluster-randomised controlled study, recruiting up to 22 500 patients with diabetes. Primary care general practices (GPs) in the National Health Service (NHS) Scotland Tayside Health Board are the units (clusters) of randomisation. Each primary care GP will form one cluster (approximately 400 patients per cluster), with up to 60 clusters recruited. Randomisation will be to iDiabetes (guideline support), iDiabetesPlus or usual diabetes care (control arm). Patients of participating primary care GPs are automatically enrolled on the study when they attend for their annual diabetes screening or are newly diagnosed with diabetes. A composite hierarchical primary outcome, evaluated using Win-Ratio statistical methodology, will consist of (1) all-cause mortality, (2) all-cause hospitalisation rate, (3) proportion with >40% estimated glomerular filtration rate [eGFR] reduction from baseline or new development of end-stage renal disease, (4) proportion with absolute HbA1C reduction >0.5%. Outcomes will be evaluated after a 2-year median follow-up period. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform.
Ethics and dissemination This study was reviewed by the NHS Health Research Authority and approved by the East of Scotland Research Ethics Committee (reference: 23/ES/0008). Study findings will be disseminated via publications, presented at scientific conferences and shared with patients and the public on the study website and social media.
KW - Cardiovascular Disease
KW - Chronic renal failure
KW - General diabetes
KW - Hepatobiliary disease
KW - Primary Care
UR - https://www.scopus.com/pages/publications/85211232209
U2 - 10.1136/bmjopen-2024-086594
DO - 10.1136/bmjopen-2024-086594
M3 - Article
C2 - 39613429
AN - SCOPUS:85211232209
SN - 2044-6055
VL - 14
SP - 1
EP - 13
JO - BMJ Open
JF - BMJ Open
IS - 11
M1 - e086594
ER -