Prediction of Return of Spontaneous Circulation in a Pediatric Swine Model of Cardiac Arrest Using Low-Resolution Multimodal Physiological Waveforms.

ABSTRACT: Monitoring physiological waveforms, specifically hemodynamic variables (e.g., blood pressure waveforms) and end-tidal CO₂ (EtCO₂), during pediatric cardiopulmonary resuscitation (CPR) has been demonstrated to improve survival rates and outcomes when compared to standard depth-guided CPR. However, waveform guidance has largely been based on thresholds for single parameters and therefore does not leverage all the information contained in multimodal data. We hypothesize that the combination of multimodal physiological features improves the prediction of the return of spontaneous circulation (ROSC), the clinical indicator of short-term CPR success. We used machine learning algorithms to evaluate features extracted from eight low-resolution (4 samples per minute) physiolog

SUBMITTER: Silva LEV 

PROVIDER: S-EPMC10756325 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature