Suppr超能文献

慢性心力衰竭患者的动态个体化风险预测:92 种生物标志物的纵向临床研究(Bio-SHiFT 研究)。

Dynamic personalized risk prediction in chronic heart failure patients: a longitudinal, clinical investigation of 92 biomarkers (Bio-SHiFT study).

机构信息

Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Room NA-316, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.

Department of Cardiology, Hypertension and Internal Medicine, Medical University of Warsaw, Warsaw, Poland.

出版信息

Sci Rep. 2022 Feb 18;12(1):2795. doi: 10.1038/s41598-022-06698-3.

Abstract

The aim of our observational study was to derive a small set out of 92 repeatedly measured biomarkers with optimal predictive capacity for adverse clinical events in heart failure, which could be used for dynamic, individual risk assessment in clinical practice. In 250 chronic HFrEF (CHF) patients, we collected trimonthly blood samples during a median of 2.2 years. We selected 537 samples for repeated measurement of 92 biomarkers with the Cardiovascular Panel III (Olink Proteomics AB). We applied Least Absolute Shrinkage and Selection Operator (LASSO) penalization to select the optimal set of predictors of the primary endpoint (PE). The association between repeatedly measured levels of selected biomarkers and the PE was evaluated by multivariable joint models (mvJM) with stratified fivefold cross validation of the area under the curve (cvAUC). The PE occurred in 66(27%) patients. The optimal set of biomarkers selected by LASSO included 9 proteins: NT-proBNP, ST2, vWF, FABP4, IGFBP-1, PAI-1, PON-3, transferrin receptor protein-1, and chitotriosidase-1, that yielded a cvAUC of 0.88, outperforming the discriminative ability of models consisting of standard biomarkers (NT-proBNP, hs-TnT, eGFR clinically adjusted) - 0.82 and performing equally well as an extended literature-based set of acknowledged biomarkers (NT-proBNP, hs-TnT, hs-CRP, GDF-15, ST2, PAI-1, Galectin 3) - 0.88. Nine out of 92 serially measured circulating proteins provided a multivariable model for adverse clinical events in CHF patients with high discriminative ability. These proteins reflect wall stress, remodelling, endothelial dysfunction, iron deficiency, haemostasis/fibrinolysis and innate immunity activation. A panel containing these proteins could contribute to dynamic, personalized risk assessment.Clinical Trial Registration: 10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 .

摘要

我们的观察性研究旨在从心力衰竭不良临床事件具有最佳预测能力的 92 个反复测量的生物标志物中得出一个小的集合,以便在临床实践中用于动态、个体化风险评估。在 250 名慢性射血分数降低心衰(HFrEF)患者中,我们在中位数 2.2 年的时间内每三个月采集一次血液样本。我们使用心血管面板 III(Olink Proteomics AB)对 92 种生物标志物的 537 个样本进行了重复测量。我们应用最小绝对收缩和选择算子(LASSO)惩罚来选择主要终点(PE)的最佳预测因子集。通过具有曲线下面积(cvAUC)分层五倍交叉验证的多变量联合模型(mvJM)评估选定生物标志物的反复测量水平与 PE 的相关性。PE 在 66 名(27%)患者中发生。LASSO 选择的最佳生物标志物集包括 9 种蛋白:NT-proBNP、ST2、vWF、FABP4、IGFBP-1、PAI-1、PON-3、转铁蛋白受体蛋白-1 和几丁质酶-1,其 cvAUC 为 0.88,优于由标准生物标志物(NT-proBNP、hs-TnT、临床调整后的 eGFR)组成的模型的区分能力 -0.82 并且与基于文献的公认生物标志物(NT-proBNP、hs-TnT、hs-CRP、GDF-15、ST2、PAI-1、半乳糖凝集素 3)的扩展集表现相当-0.88。92 种连续测量的循环蛋白中有 9 种为 CHF 患者不良临床事件提供了具有高区分能力的多变量模型。这些蛋白质反映了壁应力、重塑、内皮功能障碍、缺铁、止血/纤溶和固有免疫激活。包含这些蛋白质的面板可能有助于动态、个性化风险评估。临床试验注册:10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b70/8857321/1b9c940f7b4e/41598_2022_6698_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验