通过机器学习分析确定可预测射血分数保留型心力衰竭患者不良预后的多不饱和脂肪酸代谢物

Dhilhani Faleel, Ahmed Elzanaty, Vaishnavi Aradhyula, Rohit Vyas, Prabhatchandra R. Dube, Steven T. Haller, Rajesh Gupta, David J. Kennedy, Samer J. Khouri
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引用次数: 0

摘要

哪些分子与高频心衰患者未来的全因死亡风险或死亡或再次住院的综合不良后果相关。研究结果在高频血友病患者中,基线时9(10)-Epome、15(R)-PGE1、17-oxoRvD1、TXB3、RvD3、5(S),15(S)-DiHETE和11dh-2,3-dinor TXB2水平的升高可预测全因死亡率(所有P<0.05)。8-oxoRvD1、MaR1(n-3DPA)、PGE3 和 5,6-DiHETrE 的基线水平升高可预测死亡或再次住院的综合不良后果(均为 p<0.05)。结论这些发现支持了一个假设,即不同的 PUFA 代谢物在介导 HFpEF 心血管疾病方面发挥着重要作用。我们的研究为诊断和预后评估高频低氧血症患者的心血管风险引入了一个新的脂质组学框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Analysis of Identifies Polyunsaturated Fatty Acid Metabolites Predictive of Adverse Outcomes In Heart Failure with Preserved Ejection Fraction Patients
which molecules were associated with future risk of either all cause death or a combined adverse outcome of death or rehospitalization in the setting of HFpEF. Results: In patients with HFpEF, increased levels of 9(10)-Epome, 15(R)-PGE1, 17-oxoRvD1, TXB3, RvD3, 5(S),15(S)-DiHETE, and 11dh-2,3-dinor TXB2 at baseline were predictive of all cause mortality (all p<0.05). Increased baseline levels of 8-oxoRvD1, MaR1(n-3DPA), PGE3, and 5,6-DiHETrE were predictive of the combined adverse outcome of death or rehospitalization (all p<0.05). Conclusion: These findings support the hypothesis that distinct PUFA metabolites play a significant role in mediating cardiovascular disease in HFpEF. Our study introduces a novel lipidomics framework for the diagnostic and prognostic assessment of cardiovascular risk in HFpEF patients.
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