Computational simulation of passive leg-raising effects on hemodynamics during cardiopulmonary resuscitation

A Pilot Study to Examine the Effect of Passive Straight Leg Raise Performed During Cardiopulmonary Resuscitation on Cerebral Perfusion Measured by Noninvasive Cerebral Oximetry

Passive leg raise (PLR) during cardiopulmonary resuscitation (CPR) is simple and noninvasive maneuver, which can potentially improve patient-related outcomes. Initial CPR guidelines have previously advocated "elevation of the lower extremities to augment artificial circulation during CPR." There is lack of supporting evidence for this recommendation.

DESIGN

This was a double cross-over physiologic efficacy randomized study.

SETTING AND PATIENTS

Study in 10 subjects with in-hospital cardiac arrest for whom CPR was undertaken.

INTERVENTION

Subjects were randomized to receive two cycles of CPR with PLR followed by two cycles of CPR without PLR (Group I) or vice-versa (Group II). Subjects had their foreheads (right and left) fitted with near infrared spectroscopy (NIRS) electrodes (O3 System-Masimo, Masimo corporation Forty Parker, Irvine CA) while undergoing CPR during the study. NIRS readings, a measure of mixed venous, arterial, and capillary blood oxygen saturation, act as a surrogate measure of cerebral blood perfusion during CPR.

MEASUREMENT AND MAIN RESULTS

PLR was randomly used "first" in five of them, whereas it was used "second" in the remaining five subjects. In subjects in whom PLR was performed during first two cycles (Group I), NIRS values were initially significantly greater. The performance of PLR during CPR in Group II attenuated the decline in NIRS readings during CPR.

CONCLUSIONS

PLR during CPR is feasible and leads to augmentation of cerebral blood flow. Furthermore, the expected decline in cerebral blood flow over time during CPR may be attenuated by this maneuver. The clinical significance of these findings will require further investigations.

Evaluating current guidelines for cardiopulmonary resuscitation using an integrated computational model of the cardiopulmonary system

OBJECTIVE

We aimed to use a high-fidelity computational model that captures key interactions between the cardiovascular and pulmonary systems to investigate whether current CPR protocols could potentially be improved.

METHODS

We developed and validated the computational model against available human data. We used a global optimisation algorithm to find CPR protocol parameters that optimise the outputs associated with return of spontaneous circulation in a cohort of 10 virtual subjects.

RESULTS

Compared with current protocols, myocardial tissue oxygen volume was more than 5 times higher, and cerebral tissue oxygen volume was nearly doubled, during optimised CPR. While the optimal maximal sternal displacement (5.5 cm) and compression ratio (51%) found using our model agreed with the current American Heart Association guidelines, the optimal chest compression rate was lower (67 compressions min^-1). Similarly, the optimal ventilation strategy was more conservative than current guidelines, with an optimal minute ventilation of 1500 ml min^-1 and inspired fraction of oxygen of 80%. The end compression force was the parameter with the largest impact on CO, followed by PEEP, the compression ratio and the CC rate.

CONCLUSIONS

Our results indicate that current CPR protocols could potentially be improved. Excessive ventilation could be detrimental to organ oxygenation during CPR, due to the negative haemodynamic effect of increased pulmonary vascular resistance. Particular attention should be given to the chest compression force to achieve satisfactory CO. Future clinical trials aimed at developing improved CPR protocols should explicitly consider interactions between chest compression and ventilation parameters.

Mathematical model of modified hybrid pump mechanism for cardiopulmonary resuscitation

BACKGROUND AND OBJECTIVE

The "Cardiac pump theory" and "Thoracic pump theory" are representative theories of cardiopulmonary resuscitation (CPR) mechanisms. Based on these theories, many studies on mathematical modeling have been performed to help understand hemodynamics during CPR. However, there are parts that do not yet properly reflect the physiology of CPR. Therefore, this study aims to develop a lumped parameter model of CPR that can more accurately reflect the current CPR physiology.

METHODS

By adding compartments of the superior and inferior vena cava of the thoracic cavity to the existing CPR model, and the "Hybrid pump" mechanism was applied to simulate CPR. To compare the hemodynamics of the conventional CPR model and the developed CPR model, various conditions, such as active compression-decompression CPR with an impedance threshold valve device (ACD-CPR+ITV), head-up-tilt (HUT), and head-down-tilt (HDT), were simulated. The coronary perfusion pressure (CPP) was compared by modulating the compression ratio of the atrium and ventricle with the thoracic pump factor.

RESULTS

The result for the comparison of coronary blood flow showed that the existing model is predominant in the compression phase, whereas the developed model is dominant in the relaxation phase. ACD-CPR + ITV results showed that the CPP decreased by 5 % in the existing model, and increased by about 46 % in the developed model, revealing a distinct hemodynamic difference between the two models. Likewise, as a result of comparing the hemodynamic differences of the two models according to the changes in tilt angle, the HUT showed similar trends, while the HDT showed slightly different results. The CPP varied accordingly with the ratio of the ventricular and atrial thoracic pump factor.

CONCLUSION

Comparison of the hemodynamics with the existing model by simulating various conditions showed that the developed CPR model reflects the CPR physiology better. The model suggests that the hemodynamics may vary depending on the ventricle and atrium compression ratio. This study may provide an important basis for helping understand various situations and patient-specific hemodynamic characteristics during CPR through in-depth research, such as patient-specific model and parameter optimization.