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Published on: January 30, 2020
Chest compression quality variables influencing the temporal development of ROSC-predictors calculated from the ECG
Kenneth Gundersen1, Jon Nysaether, Jan Terje Kvaløy
1Department of Electrical and Computing Engineering, University of Stavanger, Stavanger, Norway. Kenneth.gundersen@uis.no
Background:
Predictive measures that reflect the probability of return of spontaneous circulation (ROSC) if the patient is defibrillated can be calculated from the electrocardiogram during ventricular fibrillation (VF) and ventricular tachycardia (VT). It has not been studied how the quality of chest compressions affect the development of such ROSC predictors.
Materials And Methods:
We have formulated a model for the effect of chest compressions on the ROSC predictor median-slope (MS). For untreated VF/VT MS is assumed to decay with time and increases in MS are attributed to the effect of chest compressions. The model correlates observed trends in MS with compression quality variables derived from measurements of compression depth and force recorded during out-of-hospital cardiac arrest. Among the quality variables tested were compression rate, depth, duty cycle, leaning depth, force, work and a novel quality indicator termed residual heart force. The model was first developed on an exploration dataset and thereafter validated against independent data.
Results:
When testing the indicators one by one, residual heart force (p<0.0001), force (p<0.0001) and work (p=0.0210) were significantly correlated to MS development. In multivariate analysis, residual heart force (p<0.0001) was the most significant indicator. Adjusting for residual heart force, there was a tendency that increased depth was associated with smaller effect of compressions (p=0.0330).
Conclusion:
Using MS as an indicator of the state of the myocardium, force-based compression quality variables are better indicators of efficient CPR than compression depth. A novel indicator termed residual heart force gives the best correlation with observed trends in MS.
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