BACKGROUND

Postoperative atrial fibrillation (POAF) is the most common arrythmia to occur after cardiovascular surgery. Inflammation being pivotal in POAF perpetuation has been utilized as a therapeutic target. Owing to their anti-inflammatory and anti-oxidant effects, beta-blockers (BB) and N-acetylcysteine (NAC) became research interests in the pursuit for an effective POAF prevention strategy.

To determine the efficacy of NAC plus BB versus BB alone in preventing POAF in cardiac surgery patients.

A literature search using the following search engines: PubMed/Medline, Cochrane Review Central, Clinical Trials Registry, ResearchGate, Mendeley and Google Scholar for relevant randomized trials were conducted. Published and unpublished studies indexed from inception until 2023 were included. Three independent reviewers evaluated the randomized clinical trials (RCTs) for eligibility. The pooled estimates for POAF prevention as primary outcome and MACE, mortality, myocardial infarction, stroke, ICU LOS and hospital LOS as secondary outcomes were measured using the RStudio statistical software.

Seven eligible RCTs allocated 1069 cardiac surgery patients to NAC + BB (n=539) and BB alone (N = 530) treatment arms. The effect estimate using random effect model disclosed significantly reduced POAF events (RR 0.62, 95% CI [0.44, 0.86], p = 0.005) in those on NAC + BB. While no statistical difference between the study arms were demonstrated in reducing mortality (RR 0.63, 95% CI [0.23, 1.73], p = 0.37); myocardial infarction (RR 1.02, 95% CI [0.49, 2.13], p = 0.96); stroke (RR 0.95, 95% CI [0.24, 3.68], p = 0.94); ICU LOS (std. mean difference 0.14, 95% CI [-0.43, 0.70], p = 0.41), and hospital LOS (std. mean difference 0.08, 95% CI [-0.06, 0.21], p = 0.19).

Among cardiac surgery patients, the use of NAC in combination with BB compared with BB alone significantly reduced POAF.

Cardiovascular diseases and psychological disorders represent two major threats to human physical and mental health. Research on electrocardiogram (ECG) signals offers valuable opportunities to address these issues. However, existing methods are constrained by limitations in understanding ECG features and transferring knowledge across tasks. To address these challenges, this study developed a multi-resolution feature encoding network based on residual networks, which effectively extracted local morphological features and global rhythm features of ECG signals, thereby enhancing feature representation. Furthermore, a model compression-based continual learning method was proposed, enabling the structured transfer of knowledge from simpler tasks to more complex ones, resulting in improved performance in downstream tasks. The multi-resolution learning model demonstrated superior or comparable performance to state-of-the-art algorithms across five datasets, including tasks such as ECG QRS complex detection, arrhythmia classification, and emotion classification. The continual learning method achieved significant improvements over conventional training approaches in cross-domain, cross-task, and incremental data scenarios. These results highlight the potential of the proposed method for effective cross-task knowledge transfer in ECG analysis and offer a new perspective for multi-task learning using ECG signals.
Humans ; Electrocardiography/methods* ; Mental Health ; Algorithms ; Signal Processing, Computer-Assisted ; Machine Learning ; Arrhythmias, Cardiac/diagnosis* ; Cardiovascular Diseases ; Neural Networks, Computer ; Mental Disorders

Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

OBJECTIVES: The Charlson comorbidity index reflects overall comorbidity burden and has been applied in cardiovascular medicine. However, its role in predicting in-hospital mortality in patients with acute myocardial infarction (AMI) complicated by ventricular arrhythmias (VA) remains unclear. This study aims to evaluate the predictive value of the Charlson comorbidity index in this setting and to construct a nomogram model for early risk identification and individualized management to improve outcomes. METHODS: Using the open-access critical care database MIMIC-IV (Medical Information Mart for Intensive Care IV), we identified intensive care unit (ICU) patients diagnosed with AMI complicated by VA. Patients were grouped according to in-hospital survival. The predictive performance of the Charlson comorbidity index and other clinical variables for in-hospital mortality was analyzed. Key predictors were selected using the least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable Logistic regression. A nomogram model was constructed based on the regression results. Model performance was assessed using receiver operating characteristic (ROC) curves and calibration plots. RESULTS: A total of 1 492 patients with AMI and VA were included, of whom 340 died and 1 152 survived during hospitalization. Significant differences were observed between survivors and non-survivors in sex distribution, vital signs, comorbidity burden, organ function, and laboratory parameters (all P<0.05). The area under the curve (AUC) of the Charlson comorbidity index for predicting in-hospital mortality was 0.712 (95% CI 0.681 to 0.742), significantly higher than albumin, international normalized ratio (INR), hemoglobin, body temperature, and platelet count (all P<0.001), but comparable to Sequential Organ Failure Assessment (SOFA) score (P>0.05). LASSO regression identified seven key predictors: the Charlson comorbidity index (quartile groups: T1, <6; T2, ≥6-<7; T3, ≥7-<9; T4, ≥9), ventricular fibrillation, age, systolic blood pressure, respiratory rate, body temperature, and SOFA score. Multivariate Logistic regression showed that compared with T1, mortality risk increased significantly in T2 (OR=1.996, 95% CI 1.135 to 3.486, P=0.016), T3 (OR=3.386, 95% CI 2.192 to 5.302, P<0.001), and T4 (OR=5.679, 95% CI 3.711 to 8.842, P<0.001). Age (OR=1.056, P<0.001), respiratory rate (OR=1.069, P<0.001), SOFA score (OR=1.223, P<0.001), and ventricular fibrillation (OR=2.174, P<0.001) were independent risk factors, while systolic blood pressure (OR=0.984, P<0.001) and body temperature (OR=0.648, P<0.001) were protective factors. The nomogram incorporating these predictors achieved an AUC of 0.849 (95% CI 0.826 to 0.871) with high discrimination and good calibration (mean absolute error=0.014). CONCLUSIONS The Charlson comorbidity index is an independent predictor of in-hospital mortality in AMI patients complicated by VA, with performance comparable to the SOFA score. The nomogram model based on the Charlson comorbidity index and additional clinical variables effectively estimates mortality risk and provides a valuable reference for clinical decision-making.
Humans ; Nomograms ; Hospital Mortality ; Myocardial Infarction/complications* ; Male ; Female ; Comorbidity ; Middle Aged ; Aged ; Arrhythmias, Cardiac/complications* ; ROC Curve ; Intensive Care Units

OBJECTIVE: To retrieve the evidence for threshold setting of multi-parameter electrocardiograph (ECG) monitors in intensive care unit (ICU), and summarize the best evidence. METHODS: After literature retrieval, clinical guidelines, expert consensus, evidence summary and systematic review that met the requirements were screened. Guidelines were evaluated by the appraisal of guidelines for research and evaluation II (AGREE II), expert consensus and systematic review were evaluated by the Australian JBI evidence-based health care center authenticity evaluation tool, and evidence summary was evaluated by the CASE checklist. High-quality literature was selected to extract evidence related to the use and setup of multi-parameter ECG monitors in the ICU. RESULTS: A total of 19 literatures were included, including 7 guidelines, 2 expert consensus, 8 systematic reviews, 1 evidence summary, and 1 national industry standard. After evidence extraction, translation, proofreading and summary, a total of 32 pieces of evidence were integrated. The included evidence involved the environmental preparation for the application of the ECG monitor, the electrical requirements of the ECG monitor, ECG monitor use process, ECG monitor alarm setting principles, ECG monitor alarm heart rate or heart rhythm monitoring setting, ECG monitor alarm blood pressure monitoring setting, ECG monitor alarm respiratory and blood oxygen saturation threshold setting, alarm delay warning time setting, adjusting alarm setting method, evaluating alarm setting time, improving the comfort of monitoring patients, reducing nuisance alarm report the occurrence, alarm priority processing, alarm intelligent processing and so on. CONCLUSIONS This summary of evidence involves many aspects of the setting and application of ECG monitor. According to the latest guidelines and expert consensus, it is updated and revised to guide healthcare workers to monitor patients more scientifically and safely, and aims to ensure patient safety.
Humans ; Clinical Alarms ; Australia ; Intensive Care Units ; Arrhythmias, Cardiac ; Electrocardiography ; Monitoring, Physiologic

Temporary cardiac pacing is an essential technique in the diagnosis and treatment of arrhythmias. Due to its urgency, complexity, and uncertainty, it is necessary to develop an evidence-based emergency operation norms. Currently, there is no specific consensus guidelines at home or abroad. The Emergency Branch of Chinese Medical Association organized relevant experts to draft the Chinese emergency expert consensus on bedside temporary cardiac pacing (2023) to guide the operation and application of bedside cardiac pacing. The formulation of the consensus adopts the consensus meeting method and the evidentiary basis and recommendation grading of the Oxford Center for Evidence-based Medicine in the United States. A total of 13 recommendations were extracted from the discussion on the methods of bedside temporary cardiac pacing, the puncture site of transvenous temporary cardiac pacing, the selection of leads, the placement and placement of leads, pacemaker parameter settings, indications, complications and postoperative management. The recommended consensus includes the choice between transcutaneous and transvenous pacing, preferred venous access for temporary transvenous pacing, the target and best guidance method for implantation of bedside pacing electrodes, recommended default pacemaker settings, recommended indications for sinoatrial node dysfunction, atrioventricular block, acute myocardial infarction, cardiac arrest, ventricular and supraventricular arrhythmias. They also recommended ultrasound guidance and a shortened temporary pacing support time to reduce complications of temporary transvenous cardiac pacing, recommended bedrest, and anticoagulation after temporary transvenous pacing. Bedside temporary cardiac pacing is generally safe and effective. Accurate assessment, correct selection of the pacing mode, and timely performance of bedside temporary cardiac pacing can further improve the survival rate and prognosis of related emergency patients.
Humans ; Cardiac Pacing, Artificial/methods* ; Pacemaker, Artificial ; Arrhythmias, Cardiac/therapy* ; Myocardial Infarction/therapy* ; Electrodes

OBJECTIVE: The transformations that occur in diterpenoid alkaloids during the process of sand frying for Chinese herbal medicine preparation have yet to be clarified. This study investigated the structural changes that take place in 3-acetylaconitine during a simulation of heat-processing and evaluated the toxicity and biological activity of the pyrolysis products. METHODS: The diterpenoid alkaloid 3-acetylaconitine was heated at 180 °C for 15 min to simulate the process of sand frying. The pyrolysis products were separated using column chromatography, and their structures were investigated using high-resolution electrospray ionization mass spectroscopy and nuclear magnetic resonance spectroscopy. Further, in vivo cardiotoxicity and acute toxicity of 3-acetylaconitine and its pyrolysis products were compared, and the aconitine-induced arrhythmia model was employed to evaluate the antiarrhythmic effect of the pyrolysis products. RESULTS: Two new diterpenoid alkaloids, pyroacetylaconitine and 16-epi-pyroacetylaconitine, a pair of epimers at C-16, were isolated. After comparing the structures of these compounds, possible transformation pathways were proposed. Compared with the prototype compound, 3-acetylaconitine, the cardiotoxicity and acute toxicity of the heat-transformed products were significantly decreased. In the biological activity assay, the two pyrolysis products exhibited an effective increase in ventricular premature beat latency, a reduction in the occurrence of ventricular tachycardia, as well as an increase in the rate of arrhythmia inhibition, implying strong antiarrhythmic activity. CONCLUSION Compared with 3-acetylaconitine, its pyrolysis products displayed lower toxicity and good antiarrhythmic effects; thus, they have potential for being developed into antiarrhythmic medicines. Please cite this article as: Wang YJ, Wang Y, Tao P. Structural characterization, in vivo toxicity and biological activity of two new pyro-type diterpenoid alkaloids derived from 3-acetylaconitine. J Integr Med. 2023; 21(3): 302-314.
Humans ; Aconitine/chemistry* ; Cardiotoxicity ; Sand ; Alkaloids/toxicity* ; Arrhythmias, Cardiac/drug therapy* ; Diterpenes/toxicity*

Humans ; Arrhythmias, Cardiac ; Tachycardia, Ventricular/surgery*

Accurate assessment of the risks associated with traditional Chinese medicine(TCM), such as the potential to induce serious cardiovascular adverse reactions including cardiac arrhythmias, is crucial. This article introduced the pharmacological evaluation strategies for cardiac safety and the progress in cardiac organ research, with a focus on discussing the application prospects of human induced pluripotent stem cells(hiPSCs) and organoids in assessing the risks of TCM-induced cardiac arrhythmias. Compared with traditional animal models, hiPSCs and organoid models provide better reference and predictive capabilities, allowing for more accurate simulation of human cardiac responses. Researchers have successfully generated various cardiac tissue models that mimic the structure and function of the heart to evaluate the effects of TCM on the heart. The hiPSCs model, by reprogramming adult cells into pluripotent stem cells and differentiating them into cardiac cells, enables the generation of personalized cardiac tissue, which better reflects individual differences and drug responses. This provides guidance for the assessment of TCM cardiac toxicity risks. By combining organoid model with cardiac safety pharmacology strategies such as electrocardiogram monitoring and ion channel function assessment, the impact of TCM on the heart can be comprehensively evaluated. In addition, the application of the Comprehensive in Vitro Proarrhythmia Assay(CiPA) approach improves the accuracy of evaluation. Applying the CiPA approach to TCM research reveals potential risks and provides a scientific basis for the clinical application and industrial development of TCM. In conclusion, organoid model and cardiac safety pharmacology evaluation strategies provide important tools for assessing the cardiac toxicity risks of TCM. The combination of hiPSCs model, comprehensive assessment methods, and the CiPA strategy enables an accurate assessment of the risks of TCM-induced cardiac arrhythmias, thus providing a scientific basis for the safe use and international recognition of TCM in clinical practice. This contributes to ensuring the safety and efficacy of TCM and promoting its clinical application and global acceptance.
Animals ; Humans ; Medicine, Chinese Traditional/adverse effects* ; Cardiotoxicity ; Induced Pluripotent Stem Cells ; Arrhythmias, Cardiac/chemically induced* ; Myocytes, Cardiac ; Organoids ; Drugs, Chinese Herbal/adverse effects*

OBJECTIVE: To explore incidence, risk factors and the relationship between preoperative heart failure and prognosis in elderly patients with hip fracture. METHODS: A retrospective analysis was performed on 1 569 elderly patients with hip fracture treated from January 2012 to December 2019, including 522 males and 1 047 females, aged 81.00 (75.00, 90.00) years old;896 intertrochanteric fractures and 673 femoral neck fractures. Patients were divided into heart failure and non-heart failure groups according to whether they developed heart failure before surgery, and heart failure was set as the dependent variable, with independent variables including age, gender, fracture type, comorbidities and hematological indicators, etc. Univariate analysis was performed at first, and independent variables with statistical differences were included in multivariate Logistic regression analysis. Independent risk factors for preoperative heart failure were obtained. The length of hospital stay, perioperative complications, mortality at 30 days and 1 year after surgery were compared between heart failure and non-heart failure groups. RESULTS: There were 91 patients in heart failure group, including 40 males and 51 females, aged 82.00 (79.00, 87.00) years old;55 patients with intertrochanteric fracture and 36 patients with femoral neck fracture. There were 1 478 patients in non-heart failure groups, including 482 males and 996 females, aged 81.00(75.00, 86.00) years old;841 patients with intertrochanteric fracture and 637 patients with femoral neck fracture. There were significant differences in age, sex, coronary heart disease, arrhythmia and dementia between two groups(P<0.05). Multivariate Logistic analysis of statistically significant factors showed that males(OR=1.609, P=0.032), age(OR=1.032, P=0.031), arrhythmia(OR=2.045, P=0.006), dementia (OR=2.106, P=0.014) were independent risk factor for preoperative heart failure. The 30-day and 1-year mortality rates were 9.9% and 26.4% in heart failure group and 3.6% and 13.8% in non-heart failure group, respectively;and had statistical significance between two groups (P<0.05). There were significant differences in pulmonary infection, cerebrovascular complications and cardiovascular complications between two groups (P<0.05). The duration of hospitalization in heart failure group was (16.21±10.64) d compared with that in non-heart failure group (13.26±8.00) d, and the difference was statistically significant (t=2.513, P=0.012). CONCLUSION Male, old age, arrhythmia and dementia are independent risk factors for heart failure after hip fracture in elderly patients. Patients with preoperative heart failure have a higher incidence of postoperative pulmonary infection, cerebrovascular and cardiovascular complications, higher mortality at 30 d and 1 year after surgery, and longer hospital stay.
Aged ; Female ; Humans ; Male ; Aged, 80 and over ; Retrospective Studies ; Hip Fractures/surgery* ; Femoral Neck Fractures ; Heart Failure/etiology* ; Prognosis ; Heart Diseases ; Risk Factors ; Postoperative Complications/etiology* ; Dementia ; Arrhythmias, Cardiac