Predicting fluid responsiveness during infrarenal aortic cross-clamping in pigs

Parameter estimation to study the immediate impact of aortic cross-clamping using reduced order models

Aortic cross-clamping is a common strategy during vascular surgery, however, its instantaneous impact on hemodynamics is unknown. We, therefore, developed two numerical models to estimate the immediate impact of aortic clamping on the vascular properties. To assess the validity of the models, we recorded continuous invasive pressure signals during abdominal aneurysm repair surgery, immediately before and after clamping. The first model is a zero-dimensional (0D) three-element Windkessel model, which we coupled to a gradient-based parameter estimation algorithm to identify patient-specific parameters such as vascular resistance and compliance. We found a 10% increase in the total resistance and a 20% decrease in the total compliance after clamping. The second model is a nine-artery network corresponding to an average human body in which we solved the one-dimensional (1D) blood flow equations. With a similar parameter estimation method and using the results from the 0D model, we identified the resistance boundary conditions of the 1D network. Determining the patient-specific total resistance and the distribution of peripheral resistances through the parameter estimation process was sufficient for the 1D model to accurately reproduce the impact of clamping on the pressure waveform. Both models gave an accurate description of the pressure wave and had a high correlation (R² > .95) with experimental blood pressure data.

Effects of Cross-Clamping on Vascular Mechanics: Comparing Waveform Analysis With a Numerical Model

BACKGROUND

Immediate changes in vascular mechanics during aortic cross-clamping remain widely unknown. By using a numerical model of the arterial network, vascular compliance and resistance can be estimated and the time constant of pressure waves can be calculated and compared with results from the classic arterial waveform analysis.

METHODS

Experimental data were registered from continuous invasive radial artery pressure measurements from 11 patients undergoing vascular surgery. A stable set of beats were chosen immediately before and after each clamping event. Through the arterial waveform analysis, the time constant was calculated for each individual beat and for a mean beat of each condition as to compare with numerical simulations. Overall proportional changes in resistance and compliance during clamping and unclamping were calculated using the numerical model.

RESULTS

Arterial waveform analysis of individual beats indicated a significant 10% median reduction in the time constant after clamping, and a significant 17% median increase in the time constant after unclamping. There was a positive correlation between waveform analysis and numerical values of the time constant, which was moderate (ρ = 0.51; P = 0.01486) during clamping and strong (ρ = 0.77; P ≤ 0.0001) during unclamping. After clamping, there was a significant 16% increase in the mean resistance and a significant 23% decrease in the mean compliance. After unclamping, there was a significant 19% decrease in the mean resistance and a significant 56% increase in the mean compliance.

CONCLUSIONS

There are significant hemodynamic changes in vascular compliance and resistance during aortic clamping and unclamping. Numerical computer models can add information on the mechanisms of injury due to aortic clamping.

The pathophysiology of aortic cross-clamping

During open aortic surgery, interrupting the blood flow through the aorta by applying a cross-clamp is often a key step to allow for surgical repair. As a consequence, ischemia is induced in parts of the body distal to the clamp site. This significant alteration in the blood flow is almost always associated with hemodynamic changes. Upon release of the cross-clamp, the blood flow is restored, triggering an ischemia-reperfusion response, leading to many pathophysiological processes such as inflammation, humoral changes, and metabolite circulation that could lead to injury in many organ systems and may significantly influence the postoperative outcome. It is therefore important to understand these processes and how they can be treated in order to allow for safe surgical aortic repairs while ensuring the best possible outcomes.

Intraoperative management of heart-lung interactions: "from hypothetical prediction to improved titration"

Extensive literature describes the suitability of dynamic parameters to predict responsiveness in fluid. However, based on heart-lung interactions, these parameters can have serious limitations, including the use of protective lung ventilation. Although the latter seems to be beneficial for healthy patients undergoing high-risk surgery, the intraoperative interpretation of dynamic parameters to predict fluid responsiveness can be hazardous. In this context, the attending physician could, alternatively, titrate the need of fluids with a small fluid challenge, which remains unaffected by low tidal volume, the presence of arrhythmia, or the presence of spontaneous ventilation. When intraoperative prediction of fluid responsiveness is required in mechanically ventilated patients, "improved" titration should be preferred to a hypothetical prediction.