Yiqin Wang MD, Qiong Wen MD, Yuewen Lu BD, Jiayi Yang PhD, Naya Huang MD, Wei Chen MD
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These variables were integrated into the model-based recursive partitioning approach, yielding a visualizable tree model that depicted benefitting subgroups.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Node 4, characterized by no cardiovascular history, systolic blood pressure (SBP) ≤142.67 mm Hg, and triglycerides ≤172 mg/dL, showed significantly reduced hazards of the composite renal outcome (fully adjusted hazard ratio [HR] 0.66, 95% confidence interval [CI] 0.49–0.89; <i>p</i> = 0.006) and doubling of serum creatinine (fully adjusted HR 0.59, 95% CI 0.36–0.98; <i>p</i> = 0.041). Node 7 (no cardiovascular history and SBP 142.67–154 mm Hg) showed reduced hazards of the primary renal outcome (fully adjusted HR 0.67, 95% CI 0.49–0.93; <i>p</i> = 0.016) and ESRD (fully adjusted HR 0.35, 95% CI 0.17–0.74; <i>p</i> = 0.0057). Encouragingly, neither node 4 nor node 7 displayed elevated cardiovascular risk or hypoglycaemic events.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Through innovative machine learning, we identified ACCORD subgroups benefitting significantly from intensive glycaemic therapy for renal outcomes, without increased cardiovascular or hypoglycaemic risks.</p>\n </section>\n </div>","PeriodicalId":158,"journal":{"name":"Diabetes, Obesity & Metabolism","volume":"27 3","pages":"1198-1207"},"PeriodicalIF":5.7000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying subgroups benefiting from intensive glycaemic treatment to improve renal outcomes in type 2 diabetes: Insights from the ACCORD trial\",\"authors\":\"Yiqin Wang MD, Qiong Wen MD, Yuewen Lu BD, Jiayi Yang PhD, Naya Huang MD, Wei Chen MD\",\"doi\":\"10.1111/dom.16111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aims</h3>\\n \\n <p>The ACCORD trial showed that intensive glucose-lowering therapy has a limited impact on renal function decline. 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引用次数: 0
摘要
目的:ACCORD试验表明强化降糖治疗对肾功能下降的影响有限。我们旨在确定ACCORD人群中可能从强化降糖治疗中获得肾脏益处的亚组。材料和方法:主要肾脏结局包括肾小球滤过率基线估计下降≥50%或终末期肾病(ESRD)。使用因果树模型,我们采用内部交叉验证来确定影响强化血糖控制肾脏疗效的五个关键变量。这些变量被集成到基于模型的递归划分方法中,产生一个可视化的树模型,该模型描述了受益的子组。结果:节点4无心血管病史,收缩压(SBP)≤142.67 mm Hg,甘油三酯≤172 mg/dL,其复合肾结局的危险性显著降低(完全校正风险比[HR] 0.66, 95%可信区间[CI] 0.49-0.89;p = 0.006),血清肌酐翻倍(完全校正HR 0.59, 95% CI 0.36-0.98;p = 0.041)。节点7(无心血管病史,收缩压142.67-154 mm Hg)显示原发性肾结局的风险降低(完全校正HR 0.67, 95% CI 0.49-0.93;p = 0.016)和ESRD(完全校正HR 0.35, 95% CI 0.17-0.74;p = 0.0057)。令人鼓舞的是,4号结和7号结均未出现心血管风险升高或低血糖事件。结论:通过创新的机器学习,我们确定了ACCORD亚组从强化降糖治疗中显著受益,没有增加心血管或低血糖风险。
Identifying subgroups benefiting from intensive glycaemic treatment to improve renal outcomes in type 2 diabetes: Insights from the ACCORD trial
Aims
The ACCORD trial showed that intensive glucose-lowering therapy has a limited impact on renal function decline. We aimed to identify subgroups in the ACCORD population that might derive renal benefits from intensive glucose-lowering therapy.
Materials and Methods
The primary renal outcome included a ≥50% decline in baseline estimated glomerular filtration rate or end-stage renal disease (ESRD). Using the causal tree model, we employed internal cross-validation to identify five pivotal variables influencing the renal efficacy of intensive glycaemic control. These variables were integrated into the model-based recursive partitioning approach, yielding a visualizable tree model that depicted benefitting subgroups.
Results
Node 4, characterized by no cardiovascular history, systolic blood pressure (SBP) ≤142.67 mm Hg, and triglycerides ≤172 mg/dL, showed significantly reduced hazards of the composite renal outcome (fully adjusted hazard ratio [HR] 0.66, 95% confidence interval [CI] 0.49–0.89; p = 0.006) and doubling of serum creatinine (fully adjusted HR 0.59, 95% CI 0.36–0.98; p = 0.041). Node 7 (no cardiovascular history and SBP 142.67–154 mm Hg) showed reduced hazards of the primary renal outcome (fully adjusted HR 0.67, 95% CI 0.49–0.93; p = 0.016) and ESRD (fully adjusted HR 0.35, 95% CI 0.17–0.74; p = 0.0057). Encouragingly, neither node 4 nor node 7 displayed elevated cardiovascular risk or hypoglycaemic events.
Conclusions
Through innovative machine learning, we identified ACCORD subgroups benefitting significantly from intensive glycaemic therapy for renal outcomes, without increased cardiovascular or hypoglycaemic risks.
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.