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

YeunYi Lin, Damien Leith, Michael Abbott, Rachael Barrett, Samira Bell, Tim J Croudace, Scott G Cunningham, John F Dillon, Peter T Donnan, Albert Farre, Rodolfo Hernandez, Chim C Lang, Stephanie McKenzie, Ify R Mordi, Susan Morrow, H Cameron Munro, Mandy Ryan, Huan Wang, Mya Win, Ewan R. Pearson
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Abstract

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. Ethics and Dissemination This study was reviewed by the NHS HRA and given a favourable opinion by a Research Ethics Committee (reference:23/ES/0008). Study findings will be disseminated via publications and presented at scientific conferences. Findings will be shared with patients and the public on the study website and social media. Study registration ISRCTN18000901 Study Sponsor University of Dundee, no. 2-026-22. Contact: tascgovernance@dundee.ac.uk Protocol version: V3.0, 22/09/2023
iDiabetes 平台:加强糖尿病患者表型分析,促进精准诊断、预后和治疗--分组随机对照研究的研究方案
导言和目的 糖尿病是一种全球性的紧急健康问题,发病率和与糖尿病相关的发病率和死亡率都在不断上升。优化糖尿病护理所面临的挑战之一是将这一异质性疾病的研究进展转化为常规临床护理。一个潜在的解决方案是在糖尿病护理中引入精准医疗方法。我们旨在开发一个名为智能糖尿病(iDiabetes)的数字平台,以支持苏格兰的糖尿病精准治疗模式,并评估其对全因死亡率、住院率、肾功能下降和血糖控制等主要综合结果的影响。方法与分析 iDiabetes 的影响将通过群组随机对照研究进行评估,最多将招募 22500 名糖尿病患者。苏格兰国家卫生服务局泰赛德卫生委员会的初级保健全科医生(GP)是随机分组的单位(群组)。每个初级保健全科医生将组成一个群组(每个群组约有 400 名患者),最多招募 60 个群组。随机分组为 iDiabetes(指南支持)、iDiabetesPlus 或常规糖尿病护理(对照组)。参与研究的全科医生的患者在接受年度糖尿病筛查或新诊断出糖尿病时,将自动加入研究。采用 Win-Ratio 统计方法评估的复合分层主要结果包括:(I)全因死亡率;(II)全因住院率;(III)eGFR 比基线降低 40% 或新出现终末期肾病的比例;(IV)HbA1C 绝对值降低 0.5% 的比例。将进行全面的定性和健康经济分析,评估 iDiabetes 平台的成本效益、预算影响和用户接受度。伦理与传播 本研究已通过英国国家医疗服务系统 HRA 审查,并获得研究伦理委员会的赞成意见(参考文献:23/ES/0008)。研究结果将通过出版物和科学会议进行传播。研究结果将在研究网站和社交媒体上与患者和公众分享。研究注册号:ISRCTN18000901研究主办方:邓迪大学,编号:2-026-22。联系方式:tascgovernance@dundee.ac.ukProtocol 版本:V3.0, 22/09/2023
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