Towards Personalized Closed-Loop Mechanical CPR: A Model Relating Carotid Blood Flow to Chest Compression Rate and...

There is a growing interest in the personalization of chest compressions to increase blood flow during cardiopulmonary resuscitation (CPR), but there has been very little systematic work to test the feasibility of a closed loop mechanical CPR system. The purpose of this study is to determine if it is possible to model the response of the carotid blood flow to different chest compression waveforms as a function of time during resuscitation from cardiac arrest. This work tests several approaches to predict the carotid blood flow generated by the next chest compression based on knowledge of the duration of resuscitation, the chest compression rate, and the last compression's carotid blood flow.

Using an existing physiological database from swine cardiac arrest studies, we computed the features of CPR epoch, compression index, compression rate, and the previous carotid blood flow and used them as the inputs to our model in order to predict carotid blood flow using a Random Forest algorithm. We tested animal specific (estimated with data from a single animal) and global (estimated with data from all but one animals) models for effectiveness.

Animal specific models did not generalize when applied to the rest of the animals. The global model performed reasonably well when trained on six animals and tested on the 7th, resulting in errors of 40-160 μL per compression, compared to an average of approximately 400 μL net carotid blood flow per compression in early compressions. In addition, the global model highlighted the inter-animal variability in carotid blood flow generated by identical chest compression waveforms. Generation of probability distribution functions of carotid blood flows suggested at least three different distribution profiles in seven animals.

A single physiological metric, carotid blood flow, combined with information about the duration of resuscitation and the compression rate was sufficient to model and predict carotid blood flow in the next compression.

This demonstrates that the physiological response to chest compression can be predicted from a relatively modest data set. This suggests that closed loop mechanical CPR is a viable medical device target.