Department of Laboratory and Transfusion Medicine, Hospital of University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
Second Department of Internal Medicine, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
PLoS One. 2020 Jun 15;15(6):e0234294. doi: 10.1371/journal.pone.0234294. eCollection 2020.
Although global longitudinal strain (GLS) measurements provide useful predictive information, measurement variability is still a major concern. We sought to determine whether fully automated GLS measurements could predict future cardiac events in patients with known or suspected heart failure (HF).
GLS was measured using fully automated 2D speckle tracking analysis software (AutoStrain, TomTec) in 3,150 subjects who had undergone clinically indicated brain natriuretic peptide (BNP) assays and echocardiographic examinations. Among 1,514 patients in the derivation cohort, optimal cut-off values of BNP and GLS for cardiac death (CD) and major adverse cardiovascular events (MACEs) were determined using survival classification and regression tree (CART) analysis. The remaining 1,636 patients, comprising the validation cohort, were stratified into subgroups according to predefined cut-off values, and survival curves were compared.
Survival CART analysis selected GLS with cut-off values of 6.2% and 14.0% for predicting CD. GLS of 6.9% and 13.9% and BNP of 83.2 pg/mL and 206.3 pg/mL were selected for predicting MACEs. For simplicity, we defined GLS of 7% and 14% and BNP of 100 pg/mL and 200 pg/mL as cut-off values. These cut-off values stratify high-risk patients in the validation cohort with known or suspected HF for both CD and MACEs.
In addition to BNP, fully automated GLS measurements provide prognostic information for patients with known or suspected HF, and this approach facilitates clinical work flow.
尽管整体纵向应变（GLS）测量提供了有用的预测信息，但测量的可变性仍然是一个主要关注点。我们旨在确定是否可以使用全自动 GLS 测量来预测已知或疑似心力衰竭（HF）患者的未来心脏事件。
在 3150 名接受了临床指示的脑钠肽（BNP）检测和超声心动图检查的患者中，使用全自动 2D 斑点追踪分析软件（AutoStrain，TomTec）测量 GLS。在推导队列的 1514 名患者中，使用生存分类和回归树（CART）分析确定 BNP 和 GLS 的最佳截断值，用于预测心脏死亡（CD）和主要不良心血管事件（MACEs）。其余 1636 名患者，构成验证队列，根据预定义的截断值分为亚组，并比较生存曲线。
生存 CART 分析选择 GLS 截断值为 6.2%和 14.0%来预测 CD。GLS 的 6.9%和 13.9%和 BNP 的 83.2pg/mL 和 206.3pg/mL 被选择用于预测 MACEs。为了简单起见，我们将 GLS 的 7%和 14%和 BNP 的 100pg/mL 和 200pg/mL 定义为截断值。这些截断值可将验证队列中已知或疑似 HF 的患者分层为 CD 和 MACEs 的高危患者。
除了 BNP 之外，全自动 GLS 测量还为已知或疑似 HF 的患者提供预后信息，这种方法简化了临床工作流程。
