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. 2020 Jun 15;15(6):e0234294.
doi: 10.1371/journal.pone.0234294. eCollection 2020.

Prediction of cardiac events using fully automated GLS and BNP titers in patients with known or suspected heart failure

Kyoko Otani  1 , Yukie Higa  1 , Tetsuji Kitano  2 , Yosuke Nabeshima  2 , Masaaki Takeuchi  1
Affiliations

Prediction of cardiac events using fully automated GLS and BNP titers in patients with known or suspected heart failure

Kyoko Otani et al. PLoS One. .

Abstract

Background: 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).

Methods: 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.

Results: 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.

Conclusions: 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.

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Conflict of interest statement

Dr. Takeuchi has received equipment grant from TomTec. All authors have no other conflicts of interest related to employment, consultancy, patents, products in development, and marketed products. This funding source had no involvement regarding analysis and interpretation of data, writing the manuscript and decision to submit the article for publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Step-by step approach to left ventricular (LV) volume and function measurements.
A: Manual registration of apical 4-chamber view at end-diastole. B: Automatic LV endocardial border tracing (green line) at end-diastole in apical 4-chamber view. C: 2D speckle tracking analysis throughout the cardiac cycle, and a GLS of 4-chamber view was determined. D: The same procedures on apical 2-chamber view. E: The same procedures on long-axis view. F: Displayed bull’s eye, LV volumes, LV ejection fraction (EF) and global longitudinal strain (GLS).
Fig 2
Fig 2. Optimal cut-off values of BNP and GLS, and Kaplan-Meier survival curves for predicting future cardiac death (CD) in the derivation group.
Survival CART analysis identified optimal BNP and GLS cut-off values to partition the risk of CD. Colored lines represent the survival curve for CD in each subset, classified using BNP and GLS cut-off values. BNP; B-type natriuretic peptide, GLS; global longitudinal strain, CART; classification and regression trees.
Fig 3
Fig 3. Optimal cut-off values of BNP and GLS, and Kaplan-Meier survival curves for predicting major adverse cardiovascular events (MACEs) in the derivation group.
Survival CART analysis identified optimal BNP and GLS cut-off values to partition the risk of MACEs. Colored lines represent the survival curve for MACEs in each subset, classified using BNP and GLS cut-off values. BNP; B-type natriuretic peptide, GLS; global longitudinal strain, CART; classification and regression trees.
Fig 4
Fig 4. Kaplan−Meier survival analysis for cardiac death (CD; A) and major adverse cardiovascular events (MACEs; B) in the validation group.
Each patient was classified into 1 of 3 groups, based upon GLS values from the CART analysis (Fig 4A), while each patient was classified into 1 of 5 groups according to cut-off values for BNP and GLS from the CART analysis (Fig 4B). Colored lines represent survival curves for CD (A) and MACEs (B). BNP; B-type natriuretic peptide, GLS; global longitudinal strain, CART; classification and regression trees.
Fig 5
Fig 5. Nested regression model assessing incremental values of blood examination parameters and GLS in the validation group.
BNP, sodium, creatinine and hemoglobin afforded significant incremental improvement over the model including age and sex, and LVEF provided significant additional prognostic value over the model including age, sex, BNP, sodium, creatinine and hemoglobin. The further addition of GLS had no incremental value for predicting risk of cardiac death (A) but had a significant incremental value for predicting major adverse cardiovascular events (MACEs; B). BNP; B-type natriuretic peptide, Cre; creatinine, GLS; global longitudinal strain, Hb; hemoglobin, LVEF; left ventricular ejection fraction, Na; sodium.
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