Background: Recent work evaluating intra-arrest transesophageal echocardiography (TEE) in cardiac arrest (CA) has demonstrated that chest compression (CC) location is a strong predictor of return of spontaneous circulation. However, advanced skills to interpret images during resuscitation represent an important barrier to implementation of this modality. Deep Learning (DL) models have been increasingly used to perform the automated interpretation of TEE images. Given the unique challenges during the interpretation of images, DL-based automation represents an attractive adjunct to facilitate the use of intra-arrest TEE. We sought to evaluate the feasibility of a DL model to identify CC location in TEE images obtained during CA resuscitation. Methods: We analyzed videos from out-of-hospital and in-hospital CA patients evaluated with TEE collected through the Resuscitative TEE Collaborative Registry (NCT04972526). We reviewed and selected images for the DL algorithm, using midesophageal long axis clips. Videos were selected based on the visualization of anatomical structures necessary to identify the CC location. Images were annotated by an expert classifying them in CC over the LV (CC-LV) vs CC over the left ventricular outflow tract (CC-LVOT). We used TEENet, an end-to-end DL approach with input of TEE clips containing single compression cycles, to classify clips in CC-LV and CC-LVOT. The TEENet architecture includes two 3D convolution layers, followed by a global average pooling layer, and then appends a fully connected layer with a sigmoid layer. We used the F1-score as the evaluation metric for the model's performance. Results: Ten videos containing a total of 47 single CC cycle clips were selected for inclusion in the model, each clip with an average of 25 frames. The model was trained using 80% of the data (37 clips) and tested using the remaining 20% (10 clips). The model achieved an F1-score of 0.7273 in classifying CC-LV from CC-LVOT. Conclusion: We report the creation of a novel DL-model with acceptable precision and recall performance in the detection of CC location using intra-arrest TEE videos. This work is a proof-of-concept for future research aimed to evaluate the potential of DL-assisted TEE-guided CA resuscitation.
Objectives: To evaluate the clinical impact, safety, and clinical outcomes of focused transesophageal echocardiography (TEE) in the evaluation of critically ill patients in the emergency department (ED) and intensive care units (ICU). Methods: We established a prospective, multicenter, observational registry involving adult critically ill patients in whom focused TEE was performed for evaluation of out-of-hospital cardiac arrest (OHCA), in-hospital cardiac arrest (IHCA), evaluation of undifferentiated shock, hemodynamic monitoring, and/or procedural guidance in the ED, ICU, or operating room (OR) setting. The primary objective of the current investigation was to evaluate the clinical impact and safety of focused, point-of-care TEE in critically ill patients. Data elements included patient and procedure characteristics, laboratory values, timing of interventions, clinical outcomes, and TEE video images. Results: A total of 771 cases were collected from 27 hospitals, including 506 (66%) intra and post arrest OHCA and IHCA, 221 (29%) initial evaluation of undifferentiated shock, 71 (9%) hemodynamic monitoring, and 93 (12%) procedural guidance. TEE changed management in 64% of cases of OHCA, in 71% of IHCA, and in 85% of patients with undifferentiated shock. There were no reported esophageal perforations or oropharyngeal injuries, and other procedural complications were rare. Conclusion: A prospective, multicenter, and multidisciplinary TEE registry was successfully implemented, and demonstrated that focused TEE is safe and clinically impactful across multiple critical care applications. Further studies from this research network will accelerate the development of outcome-oriented research and knowledge translation on the use of TEE in emergency and critical care settings.
Every year the American Heart Association's Resuscitation Science Symposium (ReSS) brings together a community of international resuscitation science researchers focused on advancing cardiac arrest care.
The optimal management of CSF drainage in acute hydrocephalus, in particular when to initiate drain weaning, remains uncertain. This study aimed to evaluate the impact of timing and method of drain weaning on patient outcomes.
Cerebral white and grey matter injury is the leading cause of an adverse neurodevelopmental outcome in prematurely born infants. High oxygen concentrations have been shown to contribute to the pathogenesis of neonatal brain damage. Here, we focused on motor‐cognitive outcome up to the adolescent and adult age in an experimental model of preterm brain injury. In search of the putative mechanisms of action we evaluated oligodendrocyte degeneration, myelination, and modulation of synaptic plasticity‐related molecules. A single dose of erythropoietin (20,000 IU/kg) at the onset of hyperoxia (24 hours, 80% oxygen) in 6‐day‐old Wistar rats improved long‐lasting neurocognitive development up to the adolescent and adult stage. Analysis of white matter structures revealed a reduction of acute oligodendrocyte degeneration. However, erythropoietin did not influence hypomyelination occurring a few days after injury or long‐term microstructural white matter abnormalities detected in adult animals. Erythropoietin administration reverted hyperoxia‐induced reduction of neuronal plasticity‐related mRNA expression up to four months after injury. Thus, our findings highlight the importance of erythropoietin as a neuroregenerative treatment option in neonatal brain injury, leading to improved memory function in adolescent and adult rats which may be linked to increased neuronal network connectivity.