A machine learning risk score predicts mortality across the spectrum of left ventricular ejection fraction
A machine learning risk score predicts mortality across the spectrum of left ventricular ejection fraction
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DOI：
10.1002/ejhf.2155
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发表时间：
2021-04-06
影响因子：
18.2
通讯作者：
Yagil, Avi
中科院分区：
文献类型：
--
作者：
Greenberg, Barry;Adler, Eric;Yagil, Avi
目的心力衰竭(HF)指南建议根据左心室射血分数(LVEF)对患者进行分类。然而，死亡风险在每个类别中都有很大的差异，单个患者的死亡可能性通常是不确定的。对死亡风险的准确评估是许多治疗决策过程中的重要组成部分。在这份报告中，我们评估了最近描述的基于机器学习的风险评分标记物-HF在预测三个指南定义的心衰类别中患者死亡率的准确性以及区分每个类别中患者的死亡风险的能力。方法和结果使用标记物-HF计算医院队列中4064名患者的死亡风险，这些患者被分成LVEF降低、中等或保留的组。在预测死亡率方面，标记性心力衰竭比左心室射血分数要准确得多，而且在所有三种心力衰竭类别中都非常准确，c-统计量在0.83到0.89之间。此外，标记性心力衰竭能准确区分指南所使用的三类心力衰竭中的高、中、低死亡风险水平的患者。结论标记性心力衰竭能准确预测指南中使用的三类心力衰竭患者的死亡率，并区分每一类患者的风险大小。标记性心力衰竭死亡风险预测应该有助于提供者就旨在减轻这种风险的治疗的可取性提出建议，特别是当这些治疗成本高昂或与不良事件相关时，以及患者及其家人在制定未来计划时。
Aims Heart failure (HF) guideline recommendations categorize patients according to left ventricular ejection (LVEF). Mortality risk, however, varies considerably within each category and the likelihood of death in an individual patient is often uncertain. Accurate assessment of mortality risk is an important component in the decision-making process for many therapies. In this report, we assess the accuracy of MARKER-HF, a recently described machine learning-based risk score, in predicting mortality of patients in the three guideline-defined HF categories and its ability to distinguish risk of death for patients within each category.Methods and results MARKER-HF was used to calculate mortality risk in a hospital-based cohort of 4064 patients categorized into groups with reduced, mid-range, or preserved LVEF. MARKER-HF was substantially more accurate than LVEF in predicting mortality and was highly accurate in all three HF categories, with c-statistics ranging between 0.83 to 0.89. Moreover, MARKER-HF accurately discriminated between patients at high, intermediate and low levels of mortality risk within each of the three categories of HF used by guidelines.Conclusions MARKER-HF accurately predicts mortality in patients within the three categories of HF used in guidelines for management recommendations and it discriminates between magnitude of risk of patients in each category. MARKER-HF mortality risk prediction should be helpful to providers in making recommendations regarding the advisability of therapies designed to mitigate this risk, particularly when they are costly or associated with adverse events, and for patients and their families in making future plans.