In recent years, target temperature management (TTM) has been increasingly applied to cardiac arrest patients, and programs and strategies for TTM are in a constant state of update and refinement. This paper analyzes and proposes relevant strategies from the concept of TTM, its clinical application status for cardiac arrest patients in domestic and international medical institutions, its deficiencies in the clinical practice, and factors affecting the development of TTM, with a view to providing a realistic basis for the development of high-quality TTM in medical institutions.
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.
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.
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.
ObjectiveTo systematically evaluate the clinical value of machine learning (ML) for predicting the neurological outcome of out-of-hospital cardiac arrest (OHCA), and to develop a prediction model. MethodsWe searched the PubMed, Web of Science, EMbase, CNKI, Wanfang database from January 1, 2011 to November 24, 2021. Studies on ML for predicting neurological outcomes in OHCA pateints were collected. Two researchers independently screened the literature, extracted the data and evaluated the bias of the included literature, evaluated the accuracy of different models and compared the area under the receiver operating characteristic curve (AUC). ResultsA total of 20 studies were included. Eleven of the studies were from open source databases and nine were from retrospective studies. Sixteen studies directly predicted OHCA neurological outcomes, and four predicted OHCA neurological outcomes after target temperature management. A total of seven ML algorithms were used, among which neural network was the ML algorithm with the highest frequency (n=5), followed by support vector machine and random forest (n=4). Three papers used multiple algorithms. The most frequently used input characteristic was age (n=19), followed by heart rate (n=17) and gender (n=13). A total of 4 studies compared the predictive value of ML with other classical statistical models, and the AUC value of ML model was higher than that of classical statistical models. ConclusionExisting evidence suggests that ML can more accurately predict OHCA nervous system outcomes, and the predictive performance of ML is superior to traditional statistical models in certain situations.
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.
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.
ObjectiveTo explore the value of platelet-lymphocyte ratio (PLR) after return of spontaneous circulation (ROSC) combined with Sequential Organ Failure Assessment (SOFA) for estimating the short-term prognosis of ROSC patients suffered from in-hospital cardiac arrest (IHCA).MethodsROSC adult patients who suffered from IHCA during treatment in the Emergency Department of West China Hospital of Sichuan University between 00:00, August 1st, 2010 and 23:59, July 31st, 2018 were included retrospectively. The basic and clinical data of patients were collected. Patients were divided into survival group and death group according to the 28-day prognosis. Through logistic regression and receiver operating characteristic (ROC) curve analysis, the efficacy of PLR after ROSC combined with SOFA score in predicting the 28-day prognosis of IHCA patients was explored.ResultsA total of 199 patients were included, including 135 males and 64 females, with a mean age of (60.45±17.52) years old. There were 154 deaths and 45 survivors within 28 days. There were statistically significant differences between the survival group and the death group in terms of epinephrine dosage, SOFA score, proportion of patients complicated with respiratory diseases, and post-ROSC laboratory indexes including PLR, hemoglobin, red blood cell count, lymphocyte count, indirect bilirubin, serum albumin, cholesterol, and activated partial thrombin time (P<0.05). The result of multivariate logistic regression analysis showed that epinephrine dosage [odds ratio (OR)=1.177, 95% confidence interval (CI) (1.024, 1.352), P=0.022], SOFA score [OR=1.536, 95%CI (1.173, 2.010), P=0.002], PLR after ROSC [OR=1.011, 95%CI (1.004, 1.018), P=0.002] were independent risk factors for ROSC patients’ death on day 28. The areas under the ROC curve of epinephrine dosage, SOFA score and PLR after ROSC were 0.702, 0.703 and 0.737, respectively, to predict the patients’ 28-day outcome. Combining the epinephrine dosage and PLR after ROSC with SOFA score respectively to predict the 28-day outcome of patients, the areas under the ROC curve were 0.768 and 0.813, respectively.ConclusionsThe significant increase of PLR after ROSC is an independent risk factor for death within 28 days after ROSC. The combined application of PLR after ROSC and SOFA score in the 28-day outcome prediction of patients has better predictive efficacy.
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.
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.