esCCO

Pulse Wave Transit Time, PWTT, is defined as the time from the ECG R-wave peak to the pulse wave rise point. The pulse wave rise point is defined as the point where the differentiated pulse wave reaches 30% of its peak amplitude¹. PWTT consists of three intervals: pre-ejection period (PEP), pulse wave transit time through elastic artery (T1), and pulse wave transit time through peripheral arteries (T2) (Figure 1).

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PEP reflects cardiac contractility and preload and shortens as cardiac contractility and preload increase.        
T1 depend on arterial compliance, and it shortens when blood pressure increases. T2 reflects vascular resistance as blood vessel dilates. Thus, based on the various elements of hemodynamic management included in the PWTT, combined with physiological findings related to cardiac output (CO), we have been validating its clinical application.        
As a result, an initial attempt was made to infer blood pressure from PWTT. However, it became clear that changes in PWTT were different when cardiovascular agonist drugs were administered.        
It was observed that PWTT and stroke volume (SV) show a good correlation even when changes in blood pressure and SV do not coincide during drug administration (Figure 2).

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Most existing devices for cardiac output measurement use the pulse contour method, which calculates output from the arterial blood pressure waveform, as the measurement principle. This shows that there is a good correlation between stroke volume (SV) and pulse pressure (PP) (Equation (1)).

SV = K × PP (1) K: a constant

Also, in the basic concept of esCCO, PWTT and SV in Figure 2 are in good correlation, which can be shown as equation (2).

SV = α’ × PWTT ＋ β’ (2) α’: a constant β’: a coefficient

Equation (2) can be expanded to equation (3) by using equation (1) to include the compliance component K. 

SV= K × ( α × PWTT + β ) (3) α: a constant, β and K: coefficients

Based on the above, the cardiac output is continuously measured using PWTT, and esCCOis obtained using equation (4). 

CO = SV × HR = K × (α × PWTT + β) × HR = esCCO (4) 

α: a constant, β and K: coefficients (4)

esCCO obtains cardiac output from equation (4), which includes three coefficients (K, α and β).     
 

esCCO = K × (α ×PWTT ＋β) ×HR (4)

Of the three coefficients, α is a constant (2) which is obtained from previous studies. K and β are determined by inputting the three values (PWTT, PP and CO) calculated by monitoring during calibration.      
However, CO for calibration is obtained from patient information, which enables non-invasive measurement, one of esCCO’s greatest features.

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Reference       
1) Sugo Y, UkawaT, Takeda S, Ishihara H, Kazama T, Takeda Z. 2010. A Novel ContinuousCardiac Output Monitor Based on Pulse Wave Transit Time. Conf Proc IEEE Eng MedBiol Soc. 2010: 2853-6.       
2) Ishihara H, Okawa H, Tanabe K, Tsubo T, Sugo Y, Akiyama T, Takeda S. A New Non-Invasive Continuous Cardiac Output Trend Solely Utilizing Routine Cardiovascular Monitors. J Clin Monit, 2004; 18: 313–320.

Many technologies have been developed for less invasive cardiac output monitoring. esCCO is one of the technologies that determine the cardiac output using PWTT. When used together with basic monitoring of ECG, SpO₂, blood pressure using ECG electrodes, SpO₂ probes, and cuffs, esCCO may be applicable for clinical circulatory monitoring for all patients, including low-risk patients. The efficacy of esCCO was evaluated using PWTT in a multi-institutional joint study.

The study compared esCCO and cardiac output measured by intermittent bolus thermodilution (ICO) for 213 cases at 7 facilities in Japan (139 cases in ICU, 74 cases in OR). ECG, SpO₂ and invasive blood pressure were measured for all patients, and esCCO was calibrated once. For ICO measurement, cardiac output was measured once a day for ICU patients and hourly for OR patients, and just prior to removal of the pulmonary artery catheter for both ICU and OR patients.

ICO and esCCO were compared by correlation analysis and Bland-Altman analysis, and changes in bias over time were also evaluated.

Correlation between esCCO and ICO          
A total of 587 measurement points were obtained from 213 patients. The patient demographics are shown in Table 1.     
 

Table 1. Patient demographics

Correlation between esCCO and ICO was r = 0.79 (p<0.01) and bias ± precision was 0.13 ± 1.15 (L/min), which suggests that esCCO has a good measurement accuracy equivalent to ICO (Figure 4).

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The 95% confidence interval for mean bias between esCCO and ICO was 0.04 to 0.22. This was within the range of ± 0.3 (L/min) which is considered acceptable for clinical use³.      
To evaluate changes in bias over time, the data for the period after calibration in the OR group were divided into 5 intervals of 2 hours each. A significant difference was not found in the bias of these 5 intervals. (Welch's ANOVA p = 0.07)      
Also, in the ICU group, the data after calibration were divided into 3 intervals of 24 hours each. A significant difference was not found in the bias of these 3 intervals. (Repeated-measures ANOVA P = 0.781) (Figure 5).

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There was a strong correlation between esCCO and ICO and the bias was small. Bias change over time was also small.