The iDiabetes Platform: Enhanced Phenotyping of Patients with Diabetes for Precision Diagnosis, Prognosis and Treatment- study protocol for a cluster-randomised controlled study

TY - UNPB

T1 - The iDiabetes Platform

T2 - Enhanced Phenotyping of Patients with Diabetes for Precision Diagnosis, Prognosis and Treatment- study protocol for a cluster-randomised controlled study

AU - Lin, Yeun Yi

AU - Leith, Damien

AU - Abbott, Michael

AU - Barrett, Rachael

AU - Bell, Samira

AU - Croudace, Tim

AU - Cunningham, Scot G

AU - Dillon, John F

AU - Donnan, Peter T

AU - Farre, Albert

AU - Hernández, Rodolfo

AU - Lang, Chim

AU - McKenzie, Stephanie

AU - Mordi, Ify R

AU - Morrow, Susan

AU - Munro, H Cameron

AU - Ryan, Mandy

AU - Wake, Deborah J.

AU - Wang, H

AU - Win, Mya

AU - Pearson, Ewan R

PY - 2024/3/21

Y1 - 2024/3/21

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 heterogenous disease into routine 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 (GP) in the National Health Service 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 to 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 consists of (I) all-cause mortality, (II) all-cause hospitalisation rate, (III) proportion with >40% eGFR reduction from baseline or new development of end-stage renal disease, (IV) proportion with absolute HbA1C reduction >0.5%. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform.

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 heterogenous disease into routine 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 (GP) in the National Health Service 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 to 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 consists of (I) all-cause mortality, (II) all-cause hospitalisation rate, (III) proportion with >40% eGFR reduction from baseline or new development of end-stage renal disease, (IV) proportion with absolute HbA1C reduction >0.5%. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform.

KW - Precision medicine

KW - Diabetes mellitus

KW - Diabetes complications

KW - Cardiovascular diseases

KW - Heart failure

KW - Kidney failure, chronic

KW - Non-alcoholic fatty liver disease

KW - Glycemic control

KW - Genetic risk score

KW - Biological variation, population

KW - Primary health care

KW - Delivery of health care

KW - Health care economics and organizations

KW - Qualitative research

UR - http://europepmc.org/abstract/PPR/PPR824813

U2 - 10.1101/2024.03.19.24304468

DO - 10.1101/2024.03.19.24304468

M3 - Preprint

BT - The iDiabetes Platform

PB - medRxiv

ER -