esCCO
Reliable trending performance
Easy
No additional sensors
esCCO provides cardiac output information only using common vital sign parameters of ECG, SpO2 and blood pressure, requiring no additional sensors or special trainings. Hemodynamic trend monitoring will be available with esCCO for all care levels, not only during major surgeries but also in lower-risk procedures for high-risk patients showing a higher chance of bleeding or any hemodynamic stress. Also, esCCO can be a reliable index during fluid administration in various clinical settings. Adding esCCO to the conventional patient monitoring may lead to optimization of fluid management, decreased risk of complications and eventually to better outcome including reduced length of stay.
Hemodynamic monitoring after pulmonary artery or transpulmonary thermodilution catheter removal.
Hemodynamic optimization of patients who are ineligible for more aggressive and risky techniques (i.e. pulmonary artery catheter)
Support in the decision-making process for goal-directed fluid management and more.
Triage tool for early detection of sudden deterioration.
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 amplitude 1. 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).
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).
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.
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.
Correlation between esCCO and ICO
A total of 587 measurement points were obtained from 213 patients. The patient demographics are shown in Table 1.
n | Age | Gender (M/F) | Height (cm) | Weight (kg) | BSA (㎡) | |
|---|---|---|---|---|---|---|
| Total | 213 | 65.1 ± 12.7 | 142/71 | 160.0 ±10.3 | 59.2 ±12.5 | 1.61 ±0.20 |
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).
The 95% confidence interval for mean bias between esCCO and ICO was 0.04 to 0.22. This was within the range of ±ｍｉｎ0.3 (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).
Mean angular bias of esCCO and ICO was -1.8°, radial limits of agreement were ± 37.6°. (Figure 6. Left)
Mean angular bias of APCO and ICO was -3.3°, radial limits of agreement were ± 42.2°. (Figure 6. Right).
Thus, we can say that the correlation, bias, and trending ability between esCCO and ICO are comparable to those between APCO and ICO.
A case report (Figure 7) shows that the trending ability of esCCO is comparable with APCO.
31 years old male with height of 180 cm and weight of 93.8 kg.
The measured values of APCO and esCCO, respectively, were 6.5 L/min and 4.7 L/min after the induction of anesthesia, 7.3 L/min and 6.5 L/min before the start of suturing the grafted kidney, 14.3 L/min and 12.0 L/min before clamping of the artery (artery reperfusion) after the fluid challenge, and 7.4 L/min and 7.4 L/min at the end of the surgery.