Usefulness of Respiratory Stability Time-Guided Management to Prevent Readmission of Chronic Heart Failure Patients at Home: A Multicenter, Single-Arm, Open-Label Clinical Study (ITMETHOD-HF-III)

Figures

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  Figure 1. Methodology to calculate RST values (reused with permission) [18]. All spectral power is normalized by the power spectral density or the ratio of the maximum power of the components. All respiration frequency points with a power spectral density > 10% are equally adopted in the assessment of respiratory instability. Very low-frequency points of the periodic breathing curve are only adopted if the power spectral density of the very low-frequency component is >50% of the maximum power of the respiratory component. Respiratory frequency points are evaluated using standard deviation, and RST value is defined as the inverse of the standard deviation. CSR, Cheyne–Stokes respiration; Resp, respiration; RST, respiratory stability time.

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  Figure 2. Registration and follow-up route. Following obtaining written, informed consent and screening, patients are registered in this study (primary registration). Following validation of RST measurement, patients are formally registered, and RST monitoring is started (secondary registration). RST, respiratory stability time.

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  Figure 3. Entire RST telemonitoring system between home, cloud server, and hospital. All respiratory signals are obtained and transferred to a cloud server. The all-night RST value is automatically calculated on the server until the next morning. The researchers in each institute monitor RST values every day remotely by reviewing data on the cloud server. HF, heart failure; RST, respiratory stability time.

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  Figure 4. Calculation of all-night RST values in a cloud server (reused with permission) [19]. Breathing signals to calculate all-night RST are collected from 23:00 to 5:00 o’clock of the next morning every day. In the pre-processing steps for RST measurement, we focus on two frequency ranges: high-frequency respiratory components (0.11–0.5 Hz) and very low-frequency components corresponding to the periodic breathing (0.008–0.04 Hz). These two signals are divided into serial 5 min segments every 50 s. For each epoch of the 5 min high- and very low-frequency data, power spectra are serially calculated with the maximum entropy method and normalized as a percentage of the maximum power of the respiratory components. The high-frequency distribution for spectral power > 10% of the maximum and the very low-frequency distribution for spectral power > 50% of the maximum are adopted to calculate a standard deviation of respiratory frequency variations. The RST value is defined as the reciprocal of the standard deviation. For each epoch, RST value is serially calculated and averaged to represent all-night respiratory instability. RSTs are graded as colors acconrding their severity: blue, normal;…

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  Figure 5. Representation of high RST (A) and low RST levels (B) (reused with permission) [18]. In stable periodic breathing, the frequency spectrum is narrowly distributed, and the RST value is high (A). In unstable periodic breathing, the spectral components are widely distributed and include very low-frequency components, resulting in a low RST value. Cheyne–Stokes respiration; Resp, respiration RST, respiratory stability time.

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  Figure 6. A flowchart illustrating the logic behind RST alert thresholds. Patients are advised to visit the outpatient clinic and undergo medication up-titration if (1) RST falls below 20 s for two consecutive nights, or (2) RST previously maintained above 45 s for over one month subsequently decreases below 30 s within a 10–90 day period. If neither condition is met, patients continue regular telemonitoring.