Acute poisoning is characterized by a sudden and rapid onset, most poisons lack specific antidotes. Even with the full use of blood purification, mechanical ventilation, and various drugs, it is often difficult to change the fatal outcome of critically ill patients. In recent years, extracorporeal membrane oxygenation (ECMO) has gradually gained attention and exploratory application in the treatment of acute poisoning due to its significant cardiopulmonary function support, veno-venous ECMO is used for severe lung injury after poisoning, acute respiratory distress syndrome and respiratory failure due to ineffective mechanical ventilation, and it can also be used to assist the removal of residual poisons in the lungs. Veno-arterial ECMO is commonly employed in patients with circulatory failure following poisoning, fatal cardiac arrhythmias, and arrest of cardiac and respiratory. The application of veno-arterio-venous ECMO has also been reported. The mode of ECMO necessitates timely adjustments according to the evolving illness, while ongoing exploration of additional clinical indications is underway. This review analyzes and evaluates the application scope and effectiveness of ECMO in acute poisoning in recent years, with a view to better exploring and rationalizing the use of this technology.
Objective Through establishment of brain slice model in rats with perfusion and oxygen glucose deprivation (OGD), we investigated whether this model can replicate the pathophysiology of brain injury in cardiopulmonary bypass (CPB) and deep hypothermic circulatory arrest (DHCA) or not and whether perfusion and OGD can induce preoligodendrocytes (preOL) injury or not, to provide cytological evidence for white matter injury after cardiopulmonary bypass. Methods Three to five living brain slices were randomly obtained from each of forty seven-day-old (P7) Sprague-Dawley (SD) rats with a mean weight of 14.7±1.5 g. Brain slices were randomly divided into five groups with 24 slices in each group: control group with normothermic artificial cerebralspinal fluid (aCSF) perfusion (36℃) and DHCA groups: OGD at 15℃, 25℃, 32℃ and 36℃. The perfusion system was established, and the whole process of CPB and DHCA in cardiac surgery was simulated. The degree of oligodendrocyte injury was evaluated by MBP and O4 antibody via application of immunohistochemistry. Results In the OGD group, the mature oligodendrocytes (MBP-positive) cells were significantly damaged, their morphology was greatly changed and fluorescence expression was significantly reduced. The higher the OGD temperature was, the more serious the damage was; preOL (O4-positive) cells showed different levels of fluorescence expression reduce in 36℃, 32℃ and 25℃ groups, and the higher the OGD temperature was, the more obvious decrease in fluorescence expression was. There was no statistically significant difference in the O4-positive cells between the control group and the 15℃ OGD group. Conclusion The perfused brain slice model is effective to replicate the pathophysiology of brain injury in CPB/DHCA which can induce preOL damage that is in critical development stages of oligodendrocyte cell line, and reduce differentiation of oligodendrocyte cells and eventually leads to hypomyelination as well as cerebral white matter injury.
Sudden cardiac arrest (SCA) is a lethal cardiac arrhythmia that poses a serious threat to human life and health. However, clinical records of sudden cardiac death (SCD) electrocardiogram (ECG) data are extremely limited. This paper proposes an early prediction and classification algorithm for SCA based on deep transfer learning. With limited ECG data, it extracts heart rate variability features before the onset of SCA and utilizes a lightweight convolutional neural network model for pre-training and fine-tuning in two stages of deep transfer learning. This achieves early classification, recognition and prediction of high-risk ECG signals for SCA by neural network models. Based on 16 788 30-second heart rate feature segments from 20 SCA patients and 18 sinus rhythm patients in the international publicly available ECG database, the algorithm performance evaluation through ten-fold cross-validation shows that the average accuracy (Acc), sensitivity (Sen), and specificity (Spe) for predicting the onset of SCA in the 30 minutes prior to the event are 91.79%, 87.00%, and 96.63%, respectively. The average estimation accuracy for different patients reaches 96.58%. Compared to traditional machine learning algorithms reported in existing literatures, the method proposed in this paper helps address the requirement of large training datasets for deep learning models and enables early and accurate detection and identification of high-risk ECG signs before the onset of SCA.
Extracorporeal cardiopulmonary resuscitation (ECPR) is a salvage therapy for patients suffering cardiac arrest refractory to conventional resuscitation, and provides circulatory support in patients who fail to achieve a sustained return of spontaneous circulation. ECPR serves as a bridge therapy that maintains organ perfusion whilst the underlying etiology of the cardiac arrest is determined and treated. Increasing recognition of the survival benefit associated with ECPR has led to increased use of ECPR during the past decade. Commonly used indications for ECPR are: age<70 years, initial rhythm of ventricular fibrillation or ventricular tachycardia, witnessed arrest, bystander cardiopulmonary resuscitation within 5 min, failure to achieve sustained return of spontaneous circulation within 15 min of beginning cardiopulmonary resuscitation. This review provides an overview of ECPR utilization, recent outcomes, risk factors, and complications of ECPR. Identifying ECPR indications, rapid deployment of extracorporeal life support equipment, and high-quality ECPR management strategies are of paramount importance to improve survival.
On September 18th, 2023, the American Heart Association published clinical management guidelines for patients with poisoning-induced cardiac arrest and critical cardiovascular illness in Circulation. Considering the important role of the guidelines in clinical practice, our team has divided them into three sections for detailed interpretation based on the different toxic effects of the drugs. This article is the second part of the interpretation, which combines the literature to interpret the recommendations related to cardiotoxic substance poisoning in the guidelines, mainly involving the clinical management of beta blockers, calcium channel blockers, digoxin and other cardiac glycosides, as well as sodium channel blocker poisoning, aiming to assist colleagues in their clinical practice through a detailed explanation of the key recommendations in the guidelines.
Objective To investigate the relationship between thrombocytopenia after the restoration of spontaneous circulation and short-term prognosis of patients with in-hospital cardiac arrest. Methods The demographic data, post-resuscitation vital signs, post-resuscitation laboratory tests, and the 28-day mortality rate of patients who experienced in-hospital cardiac arrest at the Emergency Department of West China Hospital, Sichuan University between January 1st, 2016 and December 31st, 2016 were retrospectively analyzed. Logistic regression was used to analyze the correlation between thrombocytopenia after the return of spontaneous circulation and the 28-day mortality rate in these cardiac arrest patients. Results Among the 285 patients included, compared with the normal platelet group (n=130), the thrombocytopenia group (n=155) showed statistically significant differences in red blood cell count, hematocrit, white blood cell count, prothrombin time, activated partial thromboplastin time, and international normalized ratio (P<0.05). The 28-day mortality rate was higher in the thrombocytopenia group than that in the normal platelet group (84.5% vs. 71.5%, P=0.008). Multiple logistic regression analysis indicated that thrombocytopenia [odds ratio =2.260, 95% confidence interval (1.153, 4.429), P=0.018] and cardiopulmonary resuscitation duration [odds ratio=1.117, 95% confidence interval (1.060, 1.177), P<0.001] were independent risk factors for 28-day mortality in patients with in-hospital cardiac arrest. Conclusion Thrombocytopenia after restoration of spontaneous circulation is associated with poor short-term prognosis in patients with in-hospital cardiac arrest.
Objective To explore the value of extracorporeal membrane oxygenation(ECMO) combined with hypothermia therapy for children patients with refractory cardiac arrest after congenital heart disease surgery. Methods From January 2013 to June 2016, we conducted a prospective study of 23 children (18 males, 5 females at age of 7±11 months) who underwent ECMO for refractory cardiac arrest after congenital heart disease surgery. All patients were randomly divided into two groups: a standard group (11 patients) and a hypothermia group (12 patients). The patients of the standard group received standard therapy (the core body temperature maintaining at 37.0℃) and the hypothermia group received hypothermia therapy (the core body temperature maintaining at 33.0℃). The hospital discharge rate, the rate of weaning from ECMO and the morbidity were compared between the two groups. Results Eleven of 23 patients (47.8%) were weaned from ECMO successfully and 7 of 23 patients (30.4%) discharged from hospital. The hospital discharge rate between the hypothermia group (n=6, 50.0%) and the standard group (n=1, 9.1%) had no statistical difference (χ2=4.537, P=0.069). The rate of weaning from ECMO of the hypothermia group (n=9, 75.0%) was higher than that of the standard group (n=2, 18.2%, χ2=7.425, P=0.006). The morbidity between the two groups had no statistical difference. Conclusion Extracorporeal cardiopulmonary resuscitation can improve the survival rate of the children who suffered from refractory cardiac arrest after congenital heart disease surgery. There is no evidence that ECMO combined with hyperthermia therapy is better than the only ECMO in improving the discharge rate. But ECMO combined with hypothermia therapy has higher rate of weaning from ECMO than that of the only ECMO.
As an important medical electronic equipment for the cardioversion of malignant arrhythmia such as ventricular fibrillation and ventricular tachycardia, cardiac external defibrillators have been widely used in the clinics. However, the resuscitation success rate for these patients is still unsatisfied. In this paper, the recent advances of cardiac external defibrillation technologies is reviewed. The potential mechanism of defibrillation, the development of novel defibrillation waveform, the factors that may affect defibrillation outcome, the interaction between defibrillation waveform and ventricular fibrillation waveform, and the individualized patient-specific external defibrillation protocol are analyzed and summarized. We hope that this review can provide helpful reference for the optimization of external defibrillator design and the individualization of clinical application.
Elderly patients account for 80% of cardiac arrest patients. The incidence of poor neurological prognosis after return of spontaneous circulation of these patients is as high as 90%, much higher than that of young. This is related to the fact that the mechanism of hippocampal brain tissue injury after ischemia-reperfusion in elderly cardiac arrest patients is aggravated. Therefore, this study reviews the possible mechanisms of poor neurological prognosis after return of spontaneous circulation in elderly cardiac arrest animals, and the results indicate that the decrease of hippocampal perfusion and the number of neurons after resuscitation are the main causes of the increased hippocampal injury, among which oxidative stress, mitochondrial dysfunction and protein homeostasis disorder are the important factors of cell death. This review hopes to provide new ideas for the treatment of elderly patients with cardiac arrest and the improvement of neurological function prognosis through the comparative analysis of elderly and young animals.
Detection and classification of malignant arrhythmia are key tasks of automated external defibrillators. In this paper, 21 metrics extracted from existing algorithms were studied by retrospective analysis. Based on these metrics, a back propagation neural network optimized by genetic algorithm was constructed. A total of 1,343 electrocardiogram samples were included in the analysis. The results of the experiments indicated that this network had a good performance in classification of sinus rhythm, ventricular fibrillation, ventricular tachycardia and asystole. The balanced accuracy on test dataset reached up to 99.06%. It illustrates that our proposed detection algorithm is obviously superior to existing algorithms. The application of the algorithm in the automated external defibrillators will further improve the reliability of rhythm analysis before defibrillation and ultimately improve the survival rate of cardiac arrest.