2型糖尿病患者多成分风险评估和数据驱动护理持续获益的7年前瞻性分析:马来西亚JADE项目

IF 5.7 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Jia-Xin Hoo, Ya-Feng Yang, Eric S H Lau, Luqman Ibrahim, Shireene R Vethakkan, Jeyakantha Ratnasingam, Siew-Pheng Chan, Sharmila S Paramasivam, Yook-Chin Chia, Alexander T B Tan, Andrea O Y Luk, Sanjay Rampal, Juliana C N Chan, Lee-Ling Lim
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引用次数: 0

摘要

目的:我们评估了基于网络的亚洲糖尿病联合评估(JADE)平台增强的多成分风险评估和数据驱动护理的持续效果,该平台具有内置模板,可指导马来西亚2型糖尿病(T2D)患者在常规护理基础上进行风险分层的综合评估(CA)。方法:2012-2015年,1196例T2D患者参加了为期1年的JADE计划,随机分为(1)仅CA,(2)接受JADE个性化报告(CA + R)以增强自我护理能力,或(3)通过护士电话参与(CA + R + T)。在2020-2022年期间,患者接受了重复CA以评估≥2个ABC目标的实现情况(HbA1c结果:7.5±0.5 (mean±SD)年后,138例(11.5%)患者死亡,232例(19.4%)患者违约,826例(69.1%)患者复发。死者有更多的并发症,而非海归更年轻,并发症更少,但风险因素控制在基线时比海归更差。通过逆概率加权和逻辑回归,获得≥2个ABC目标与CA + R + T相关(与仅CA相关),比值比(OR, 95%置信区间)为1.57 (1.02-2.41,p = 0.041)。其他预测因素包括年龄[1.05 (1.04-1.07,p)]。结论:技术辅助的多成分风险评估和数据驱动的1年护理确定了高危患者,并改善了7年后的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 7-year prospective analysis of sustained benefits of multicomponent risk assessment and data-driven care in patients with type 2 diabetes: The Malaysian JADE Program.

Aim: We evaluated the sustained effects of multicomponent risk assessment and data-driven care augmented by the web-based Joint Asia Diabetes Evaluation (JADE) Platform with a built-in template to guide comprehensive assessment (CA) for risk stratification on top of usual care in patients with type 2 diabetes (T2D) from Malaysia.

Methods: In 2012-2015, 1196 T2D patients participated in a 1-year JADE Program randomised to (1) CA-only, (2) receipt of a JADE personalised report (CA + R) to empower self-care, or (3) engagement by nurse phone calls (CA + R + T). In 2020-2022, patients underwent repeat CA for evaluation of attainment of ≥2 ABC targets (HbA1c <7%, Blood pressure <130/80 mmHg, low-density lipoprotein Cholesterol [LDL-C] <2.6 mmol/L) and diabetes-related endpoints.

Results: After 7.5 ± 0.5 (mean ± SD) years, 138 (11.5%) patients had died, 232 (19.4%) defaulted, and 826 (69.1%) patients returned. The deceased had more complications, while non-returnees were younger, with fewer complications but worse risk factor control than returnees at baseline. Using inverse probability weighting and logistic regression, attaining ≥2 ABC targets was associated with CA + R + T (vs. CA-only) with an odds ratio (OR, 95% confidence interval) of 1.57 (1.02-2.41, p = 0.041). Other predictors included age [1.05 (1.04-1.07, p < 0.001)], diabetes duration [0.97 (0.95-0.99, p = 0.003)], JADE risk category 3 [0.41 (0.26-0.66), p < 0.001] and risk category 4 (vs. category 1 and 2) [0.22 (0.12-0.38), p < 0.001]. Amongst participants without complications at baseline, CA + R + T was associated with an incidence rate ratio of 0.89 (0.78-1.00, p = 0.043) for any diabetes-related endpoints.

Conclusions: Technology-assisted multicomponent risk assessment and data-driven care for 1-year identified high-risk patients and improved outcomes after 7 years.

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来源期刊
Diabetes, Obesity & Metabolism
Diabetes, Obesity & Metabolism 医学-内分泌学与代谢
CiteScore
10.90
自引率
6.90%
发文量
319
审稿时长
3-8 weeks
期刊介绍: Diabetes, Obesity and Metabolism is primarily a journal of clinical and experimental pharmacology and therapeutics covering the interrelated areas of diabetes, obesity and metabolism. The journal prioritises high-quality original research that reports on the effects of new or existing therapies, including dietary, exercise and lifestyle (non-pharmacological) interventions, in any aspect of metabolic and endocrine disease, either in humans or animal and cellular systems. ‘Metabolism’ may relate to lipids, bone and drug metabolism, or broader aspects of endocrine dysfunction. Preclinical pharmacology, pharmacokinetic studies, meta-analyses and those addressing drug safety and tolerability are also highly suitable for publication in this journal. Original research may be published as a main paper or as a research letter.
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