The spatial ventricular gradient is associated with adverse outcomes in acute pulmonary embolism

Figures

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  FIGURE 1. Transforming a 12‐lead ECG into a vectorcardiogram and measuring the SVG. (a) A 12‐lead ECG is converted into a median beat vectorcardiogram (VCG) using the Kors transformation matrix aligning serial QRST complexes. (b) The SVG vector is the sum of the QRS area and T‐wave area vectors. (c) The SVG magnitude is the length of the SVG vector, adapted from Waks et al. (2021) with permission. ECG, electrocardiogram, SVG, spatial ventricular gradient.

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  FIGURE 2. TAPSE versus SVG. Scatter plots of TAPSE versus SVG magnitude and vector components, together with regression lines. Abnormal TAPSE (low values) was correlated with lower SVG magnitude. This was driven by the X and Y components of the SVG vector, which were positively correlated with TAPSE. The Z component of the SVG was slightly inversely correlated, see Table 2 for regression coefficients. LV, left ventricular; RV, right ventricular; SVG, spatial ventricular gradient; TAPSE, tricuspid annular plane systolic excursion,

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  FIGURE 3. Qualitative RV Hypokinesis versus SVG. Box plots of SVG versus RV hypokinesis, assessed qualitatively on TTE as none, borderline, mild, and moderate to severe. p < .01 for the trend in each plot. RV, right ventricular; SVG, spatial ventricular gradient; TTE, transthoracic echocardiogram.

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  FIGURE 4. RV/LV ratio versus SVG. Scatter plots of RV/LV ratio versus SVG magnitude and vector components, together with regression lines. See Table S1 for regression coefficients. LV, left ventricular; RV, right ventricular; SVG, spatial ventricular gradient.

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  FIGURE 5. SVG versus PE severity. Box plots of SVG versus PE severity, stratified as low risk (N = 42), intermediate risk (N = 247), or high risk (N = 28), see methods for definitions. p < .01 for the trend in each plot. SVG, spatial ventricular gradient; PE, pulmonary embolism.

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  FIGURE 6. ROC curves of multivariable logistic regression models for adverse events after pulmonary embolism. Multivariable logistic regression models were constructed with imaging data, and either traditional ECG criteria (presence of S1Q3T3, RBBB, and precordial TWI) for RV strain, or the SVG. Imaging data included RV/LV ratio measured from both CT scan and TTE, as well as TAPSE measured on TTE. The ROC for the model using imaging data and traditional ECG criteria is 0.70. When SVG vector data are substituted for traditional ECG criteria, the ROC improves from 0.70 to 0.77 (p = .012). CT, computed tomography; LV, left ventricular; RBBB, right bundle branch block; ROC, receiver operating characteristic; RV, right ventricular; SVG, spatial ventricular gradient; TAPSE, tricuspid annular plane systolic excursion; TTE, transthoracic echocardiogram.