通过利用人群平均风险的偏差揭示临床有用的肥胖亚型

IF 58.7 1区医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nature Medicine Pub Date : 2025-01-17 DOI:10.1038/s41591-024-03477-7

引用次数: 0

摘要

肥胖症与许多危及生命的并发症有关。肥胖症的风险特征各不相同，因此预防肥胖症及其致病后果具有挑战性。在这项研究中，我们利用机器学习量化了体重指数与十种心血管风险指标之间的异质性关系，并据此开发和验证了强大的临床预测模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Clinically useful obesity subtypes revealed by harnessing deviations from population-average risk

查看原文本刊更多论文

Clinically useful obesity subtypes revealed by harnessing deviations from population-average risk

Obesity is associated with many life-threatening comorbidities. Its heterogeneous risk profile makes the prevention of obesity and its pathogenic consequences challenging. In this study, the heterogeneous relationships between body mass index and ten cardiovascular risk markers were quantified using machine learning, from which powerful clinical prediction models were developed and validated.

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来源期刊

Nature Medicine 医学-生化与分子生物学

CiteScore

100.90

自引率

0.70%

发文量

525

审稿时长

1 months

期刊介绍： Nature Medicine is a monthly journal publishing original peer-reviewed research in all areas of medicine. The publication focuses on originality, timeliness, interdisciplinary interest, and the impact on improving human health. In addition to research articles, Nature Medicine also publishes commissioned content such as News, Reviews, and Perspectives. This content aims to provide context for the latest advances in translational and clinical research, reaching a wide audience of M.D. and Ph.D. readers. All editorial decisions for the journal are made by a team of full-time professional editors. Nature Medicine consider all types of clinical research, including: -Case-reports and small case series -Clinical trials, whether phase 1, 2, 3 or 4 -Observational studies -Meta-analyses -Biomarker studies -Public and global health studies Nature Medicine is also committed to facilitating communication between translational and clinical researchers. As such, we consider “hybrid” studies with preclinical and translational findings reported alongside data from clinical studies.