Hypertonic versus isotonic crystalloid infusion for cerebral perfusion pressure in a porcine experimental cardiac arrest model.

BACKGROUND: The effect of intravenous (IV) fluid administration type on cerebral perfusion pressure (CePP) during cardiopulmonary resuscitation (CPR) is controversial. The purpose of this study was to evaluate the association between IV fluid type and CePP in a porcine cardiac arrest model. METHODS: We randomly assigned 12 pigs to the hypertonic crystalloid, isotonic crystalloid and no-fluid groups. After 4 min of untreated ventricular fibrillation (VF), chest compression was conducted for 2 cycles (CC only). Chest compression with IV fluid infusion (CC + IV) was followed for 2 cycles. Advanced life support, including defibrillation and epinephrine, was added for 8 cycles (ALS phase). Mean arterial pressure (MAP), intracranial pressure (ICP) and CePP were measured. A paired t-test was used to measure the mean difference in CePP. RESULTS: Twelve pigs underwent the experiment. The hypertonic crystalloid group showed higher CePP values than those demonstrated by the isotonic crystalloid group from ALS cycles 2 to 8. The MAP values in the hypertonic group were higher than those in the isotonic group starting at ALS cycle 2. The ICP values in the hypertonic group were lower than those in the isotonic group starting at ALS cycle 4. From ALS cycles 2 to 8, the reduction in the mean difference in the isotonic group was larger than that in the other groups. CONCLUSION: In a VF cardiac arrest porcine study, the hypertonic crystalloid group showed higher CePP values by maintaining higher MAP values and lower ICP values than those of the isotonic crystalloid group.

Prediction of Increased Intracranial Pressure in Traumatic Brain Injury Using Quantitative Electroencephalogram in a Porcine Experimental Model.

Continuous and non-invasive measurement of intracranial pressure (ICP) in traumatic brain injury (TBI) is important to recognize increased ICP (IICP), which can reduce treatment delays. The purpose of this study was to develop an electroencephalogram (EEG)-based prediction model for IICP in a porcine TBI model. Thirty swine were anaesthetized and underwent IICP by inflating a Foley catheter in the intracranial space. Single-channel EEG data were collected every 6 min in 10 mmHg increments in the ICP from baseline to 50 mmHg. We developed EEG-based models to predict the IICP (equal or over 25 mmHg) using four algorithms: logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and random forest (RF). We assessed the performance of each model based on the accuracy, sensitivity, specificity, and AUC values. The accuracy of each prediction model for IICP was 0.773 for SVM, 0.749 for NB, 0.746 for RF, and 0.706 for LR. The AUC of each model was 0.860 for SVM, 0.824 for NB, 0.802 for RF, and 0.748 for LR. We developed a machine learning prediction model for IICP using single-channel EEG signals in a swine TBI experimental model. The SVM model showed good predictive power with the highest AUC value.