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Fig 1.

Computational steps applied for wave intensity analysis.

From tonometrically measured radial pressure (A), aortic pressure (B) is obtained by a generalized transfer function (SphygmoCor). Aortic blood flow (C) is modelled from aortic pressure (ARCSolver) (or measured by Doppler ultrasound for model validation only). Pulse wave velocity c times blood density ρ is estimated from the slope of the approximately linear part of the PU-loop during early systole (D) to derive forward and backward wave intensity (E).

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Fig 1 Expand

Table 1.

Baseline characteristics of both patient groups in the main and the test population.

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Table 2.

Pulse wave analysis, wave intensity analysis and ECG parameters.

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Table 2 Expand

Table 3.

Univariable logistic regression models for EF-status (0: Normal, 1: Reduced).

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Fig 2.

ROC curve analysis.

Left: Comparison of the ROC curves obtained with central pulse pressure (PP), ejection duration (ED), S to D ratio (SDR) and QRS-duration. Right: ROC curves obtained with a combination of ED and SDR, and ED and SDR when adjusted for medication. Area under the curve (AUC) and 95% confidence interval are given in the same colors.

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Fig 2 Expand

Table 4.

Stepwise multivariable logistic regression models for EF-status (0: Normal, 1: Reduced) using pressure-derived parameters with and without adjustment for medication.

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Table 5.

Approach to diagnose or exclude a reduced ejection fraction by a stepwise classification scheme.

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Table 6.

Pulse wave analysis, wave intensity analysis and ECG parameters in the test population.

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Table 7.

Approach to diagnose or exclude a reduced ejection fraction by a stepwise classification scheme with fixed criteria in the test population.

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Table 7 Expand