Ensemble Approach Combining Deep Residual Networks and BiGRU with Attention Mechanism for Classification of Heart Arrhythmias

This research introduces an innovative ensemble approach,combining Deep Residual Networks(ResNets)and Bidirectional Gated Recurrent Units(BiGRU),augmented with an Attention Mechanism,for the classification of heart arrhythmias.The escalating prevalence of cardiovascular diseases necessitates advanced diagnostic tools to enhance accuracy and efficiency.The model leverages the deep hierarchical feature extraction capabilities of ResNets,which are adept at identifying intricate patterns within electrocardiogram(ECG)data,while BiGRU layers capture the temporal dynamics essential for understanding the sequential nature of ECG signals.The integration of an Attention Mechanism refines the model’s focus on critical segments of ECG data,ensuring a nuanced analysis that highlights the most informative features for arrhythmia classification.Evaluated on a comprehensive dataset of 12-lead ECG recordings,our ensemble model demonstrates superior performance in distinguishing between various types of arrhythmias,with an accuracy of 98.4%,a precision of 98.1%,a recall of 98%,and an F-score of 98%.This novel combination of convolutional and recurrent neural networks,supplemented by attention-driven mechanisms,advances automated ECG analysis,contributing significantly to healthcare’s machine learning applications and presenting a step forward in developing non-invasive,efficient,and reliable tools for early diagnosis and management of heart diseases.

AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)algorithms.However,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation efficiency.This glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of arrhythmias.Our approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model selection.To validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our methodology.In the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for training.The second pipeline is dedicated to feature extraction and classification,utilizing deep learning models.Notably,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class arrhythmias.An ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model pipeline.In our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

Arrhythmia Detection by Using Chaos Theory with Machine Learning Algorithms

Heart monitoring improves life quality.Electrocardiograms(ECGs or EKGs)detect heart irregularities.Machine learning algorithms can create a few ECG diagnosis processing methods.The first method uses raw ECG and time-series data.The second method classifies the ECG by patient experience.The third technique translates ECG impulses into Q waves,R waves and S waves(QRS)features using richer information.Because ECG signals vary naturally between humans and activities,we will combine the three feature selection methods to improve classification accuracy and diagnosis.Classifications using all three approaches have not been examined till now.Several researchers found that Machine Learning(ML)techniques can improve ECG classification.This study will compare popular machine learning techniques to evaluate ECG features.Four algorithms—Support Vector Machine(SVM),Decision Tree,Naive Bayes,and Neural Network—compare categorization results.SVM plus prior knowledge has the highest accuracy(99%)of the four ML methods.QRS characteristics failed to identify signals without chaos theory.With 99.8%classification accuracy,the Decision Tree technique outperformed all previous experiments.

Prognostic relevance of ventricular arrhythmias in surgical patients with gastrointestinal tumors

BACKGROUND Individuals diagnosed with gastrointestinal tumors are at an increased risk of developing cardiovascular diseases.Among which,ventricular arrhythmia is a prevalent clinical concern.This suggests that ventricular arrhythmias may have predictive value in the prognosis of patients with gastrointestinal tumors.AIM To explore the prognostic value of ventricular arrhythmias in patients with gastrointestinal tumors receiving surgery.METHODS We retrospectively analyzed data from 130 patients undergoing gastrointestinal tumor resection.These patients were evaluated by a 24-h ambulatory electrocardiogram(ECG)at the Sixth Affiliated Hospital of Sun Yat-sen University from January 2018 to June 2020.Additionally,41 general healthy age-matched and sexmatched controls were included.Patients were categorized into survival and non-survival groups.The primary endpoint was all-cause mortality,and secondary endpoints included major adverse cardiovascular events(MACEs).RESULTS Colorectal tumors comprised 90%of cases.Preoperative ambulatory ECG monitoring revealed that among the 130 patients with gastrointestinal tumors,100(76.92%)exhibited varying degrees of premature ventricular contractions(PVCs).Ten patients(7.69%)manifested non-sustained ventricular tachycardia(NSVT).The patients with gastrointestinal tumors exhibited higher PVCs compared to the healthy controls on both conventional ECG[27(21.3)vs 1(2.5),P=0.012]and 24-h ambulatory ECG[14(1.0,405)vs 1(0,6.5),P<0.001].Non-survivors had a higher PVC count than survivors[150.50(7.25,1690.50)vs 9(0,229.25),P=0.020].During the follow-up period,24 patients died and 11 patients experienced MACEs.Univariate analysis linked PVC>35/24 h to all-cause mortality,and NSVT was associated with MACE.However,neither PVC burden nor NSVT independently predicted outcomes according to multivariate analysis.CONCLUSION Patients with gastrointestinal tumors exhibited elevated PVCs.PVCs>35/24 h and NSVT detected by 24-h ambulatory ECG were prognostically significant but were not found to be independent predictors.

Efficient ECG classification based on Chi-square distance for arrhythmia detection

This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia detection.The proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia detection.To optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness function.This synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia detection.Experimental results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous optimization.The classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia classification.The promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.

Facing ethical concerns in the age of precise gene therapy:Outlook on inherited arrhythmias

This editorial,comments on the article by Spartalis et al published in the recent issue of the World Journal of Cardiology.We here provide an outlook on potential ethical concerns related to the future application of gene therapy in the field of inherited arrhythmias.As monogenic diseases with no or few therapeutic options available through standard care,inherited arrhythmias are ideal candidates to gene therapy in their treatment.Patients with inherited arrhythmias typically have a poor quality of life,especially young people engaged in agonistic sports.While genome editing for treatment of inherited arrhythmias still has theoretical application,advances in CRISPR/Cas9 technology now allows the generation of knock-in animal models of the disease.However,clinical translation is somehow expected soon and this make consistent discussing about ethical concerns related to gene editing in inherited arrhythmias.Genomic off-target activity is a known technical issue,but its relationship with ethnical and individual genetical diversity raises concerns about an equitable accessibility.Meanwhile,the costeffectiveness may further limit an equal distribution of gene therapies.The economic burden of gene therapies on healthcare systems is is increasingly recognized as a pressing concern.A growing body of studies are reporting uncertainty in payback periods with intuitive short-term effects for insurance-based healthcare systems,but potential concerns for universal healthcare systems in the long term as well.Altogether,those aspects strongly indicate a need of regulatory entities to manage those issues.

Analysis of the Efficacy of Low-Dose Betaloc Combined with Amiodarone in Treating Ventricular Arrhythmia

Objective:To explore and analyze the clinical effect of low-dose Betaloc combined with amiodarone in treating ventricular arrhythmia.Methods:70 patients with ventricular arrhythmia who were admitted to the Department of Cardiology of our hospital between August 2022 and August 2023 were selected as research subjects.They were divided into two groups using the coin-tossing method:the combination group(n=35)and the reference group(n=35).The combination group was treated with low-dose Betaloc and amiodarone,and the control group was treated with low-dose Betaloc alone.The treatment efficacy,cardiac function indicators,and related tested indicators of the two groups were compared.Results:The total efficacy of the treatment received by the combination group was much higher than that of the control group(P<0.05).Besides,after treatment,the cardiac function indicators such as left ventricular ejection fraction(LVEF),left ventricular end-systolic volume(LVESV),and cardiac index(CI)of the patients in the combination group were significantly better than those of the reference group(P<0.05).Furthermore,the high-sensitivity C-reactive protein(Hs-CRP),N-terminal prohormone of brain natriuretic peptide(NT-proBNP),adiponectin(APN),and other related test indicators of the patients in the combination group were significantly better than those of the reference group(P<0.05).Conclusion:Low-dose Betaloc combined with amiodarone has a noticeable effect in treating ventricular arrhythmia and deserves to be widely promoted.

Clinical Efficacy of Metoprolol Succinate Extended-Release Tablets in the Treatment of Post-Myocardial Infarction Ventricular Arrhythmias

Objective:To investigate the clinical efficacy of metoprolol succinate extended-release tablets in the treatment of post-myocardial infarction ventricular arrhythmias.Methods:The clinical data of 84 patients with post-myocardial infarction ventricular arrhythmia included in the study were collected and they were divided into Groups A and B with 42 cases each using the randomization method.Group A was treated with oral glucosamine hydrochloride,while Group B was administered oral metoprolol succinate extended-release tablets.Combined indicators were used to evaluate the improvement of clinical indicators,therapeutic effects,and the incidence of adverse reactions in the two groups.Results:The baseline data of the two groups of patients were not statistically significant(Pall>0.05);after treatment,the QT dispersion,corrected QT dispersion,and heart rate of Group B were lower than that of Group A(Pall=0.000<0.001);the 2 total clinical effectiveness of Group B was 95.24%,which was significantly higher than 80.95%in Group A(χ=4.087,P=0.043<0.05);the total incidence of adverse reactions in Group B was 4.76%,which was significantly lower than 219.04%in Group A(χ=4.087,P=0.043<0.05).Conclusion:In the treatment of post-myocardial infarction ventricular arrhythmia,the use of metoprolol succinate extended-release tablets can effectively correct the QT dispersion of patients,improve their heart rate,increase clinical effectiveness,and reduce the incidence of adverse reactions.

An Attention Based Neural Architecture for Arrhythmia Detection and Classification from ECG Signals

Arrhythmia is ubiquitous worldwide and cardiologists tend to provide solutions from the recent advancements in medicine.Detecting arrhythmia from ECG signals is considered a standard approach and hence,automating this process would aid the diagnosis by providing fast,costefficient,and accurate solutions at scale.This is executed by extracting the definite properties from the individual patterns collected from Electrocardiography(ECG)signals causing arrhythmia.In this era of applied intelligence,automated detection and diagnostic solutions are widely used for their spontaneous and robust solutions.In this research,our contributions are two-fold.Firstly,the Dual-Tree Complex Wavelet Transform(DT-CWT)method is implied to overhaul shift-invariance and aids signal reconstruction to extract significant features.Next,A neural attention mechanism is implied to capture temporal patterns from the extracted features of the ECG signal to discriminate distinct classes of arrhythmia and is trained end-to-end with the finest parameters.To ensure that the model’s generalizability,a set of five traintest variants are implied.The proposed model attains the highest accuracy of 98.5%for classifying 8 variants of arrhythmia on the MIT-BIH dataset.To test the resilience of the model,the unseen(test)samples are increased by 5x and the deviation in accuracy score and MSE was 0.12%and 0.1%respectively.Further,to assess the diagnostic model performance,AUC-ROC curves are plotted.At every test level,the proposed model is capable of generalizing new samples and leverages the advantage to develop a real-world application.As a note,this research is the first attempt to provide neural attention in arrhythmia classification using MIT-BIH ECG signals data with state-of-the-art performance.

Electrophysiologic Effects of Sophoridine on a Canine Model of Ischemic Ventricular Tachyarrhythmias

A canine model of ischemic ventricular tachyarrhythmias was established in open-chest dogs subjected to programmed electrical stimulation (PES) for 5￣8 days after acute myocardial infarction. The electrophysiologic effects of sophoridine (Sop) and procainamide (PA) were observed in this canine model. With routine methods of PES, ventricular tachycardia (VT) and ventricular fibrilation (VF) could be reproducibly initiated in this model. Both drugs distinctly lengthened the QTc interval ( P <0.01) and the effective refractory period (ERP) in normal and ischemic ventricular myocardium ( P <0.01), decreased the dispersion of ERP in ischemic myocardium and the dispersion of ERP in left ventricle (P <0.05), and increased the diastolic excitability threshold of normal and ischemic ventricular myocardium remarkably ( P <0.01). Both drugs effectively prevented the PES-induced VT or VF and ischemia-induced VF ( P <0.05). The results indicated that this canine model is a good and reliable one, sophoridine and procainamide may be effective in preventing the onset of reentrant ventricular tachyarrhythmias after myocardial ischemic damage.

Fetal Bradyarrhythmias:Etiopathogenesis,Diagnosis and Treatment:Between Literature Review and Experience of a Tertiary Center

Fetal arrhythmias reach up around 10%of the total third-level perinatal cardiology references.Sustained bradycardia is defined as a baseline fetal heart rate(FHR)of less than 110 bpm sustained for at least 10 min.The overall incidence of malignant fetal bradyarrhythmias,such as complete atrioventricular block(AVB)and channellopathies,is relatively rare,1:5000 pregnancies,but represents a serious emergency for the gynecologist,neonatologists,and pediatric cardiologists.Fetal complete AVB is strongly associated with maternal connective tissue disease,but it can be also associated with congenital heart disease and usually with a poorer prognosis with high risk of fetal hydrops and abortion.Currently,the treatment of severe fetal bradyarrhythmias is principally pharmacological and aims to increase the FHR,besides an early resolution of underlying causes,when possible,and a promptly management of fetal heart failure.Intrauterine electrostimulation nowadays is an experimental pioneering method,reserved for limited selected cases.

Prophylactic effect of magnesium sulfate against reperfusion induced arrhythmias in the isolated rat hearts

Prophylactic effect of magnesium sulfate on reperfusion arrhythmias was studiedusing a left anterior descending coronary artery occlusion followed by reperfusion in theisolated rat heart.In the first studies,we have observed a bell-shaped relationship be-tween the incidence of reperfusion-induced ventricular fibrillation（VF）and the durationof preceding ischemia.With 5,10,15,20 and 25 min of ischemia,10,70,60,50 and 20per cent of the hearts exhibited irreversible VF,respectively.In the second studies（10 minischemia）,perfusate magnesium sulfate was increased to 3.6,4.8 and 6.0 mmol/L 1 min be-fore coronary ligation,VF fell in a dose-dependent manner from its control total inci-dence of 100%（1.2mmol/L MgSO4）to 82%,73% and 18%（P【0.01）,respectively.Heartrate was also reduced in a dose-dependent manner,falling from its control value of326±11 to 227±22 beats/min with the highest concentration of magnesium sulfate.Asperfusate magnesium sulfate was increased to 6.0 mmol/L just before reperfusion,no an-ti-arrhythmic effects were observed.With an anti-arrhythmic concentration of magnesiumsulfate（6.0 mmol/L,increased 1 min before ligation）,calcium concentration was increasedby 1.5 mmol/L at the same time,under these conditions the anti-arrhythmic effect of mag-nesium sulfate was lost and its negative chronotropic effect was also partially abolished.We conclude that magnesium sulfate has a certain prophylactic effect againstreperfusion induced arrhythmias and this could be due to a direct or indirect calci-um-antagonist action.

Classification of Electrocardiogram Signals for Arrhythmia Detection Using Convolutional Neural Network

With the help of computer-aided diagnostic systems,cardiovascular diseases can be identified timely manner to minimize the mortality rate of patients suffering from cardiac disease.However,the early diagnosis of cardiac arrhythmia is one of the most challenging tasks.The manual analysis of electrocardiogram(ECG)data with the help of the Holter monitor is challenging.Currently,the Convolutional Neural Network(CNN)is receiving considerable attention from researchers for automatically identifying ECG signals.This paper proposes a 9-layer-based CNN model to classify the ECG signals into five primary categories according to the American National Standards Institute(ANSI)standards and the Association for the Advancement of Medical Instruments(AAMI).The Massachusetts Institute of Technology-Beth Israel Hospital(MIT-BIH)arrhythmia dataset is used for the experiment.The proposed model outperformed the previous model in terms of accuracy and achieved a sensitivity of 99.0%and a positivity predictively 99.2%in the detection of a Ventricular Ectopic Beat(VEB).Moreover,it also gained a sensitivity of 99.0%and positivity predictively of 99.2%for the detection of a supraventricular ectopic beat(SVEB).The overall accuracy of the proposed model is 99.68%.

Ventricular Arrhythmia in the Fontan Circulation:Prevalence,Risk Factors and Clinical Implications

Objective:Sudden cardiac death(SCD)and malignant ventricular arrhythmia(VA)are increasingly recognized as important issues for people living with a Fontan circulation,but data are lacking.We sought to characterize the cohort who had sudden cardiac death,most likely related to VA and/or documented VA in the Australia and New Zealand Fontan Registry including risk factors and clinical outcomes.Methods:A retrospective cohort study was performed.Inclusion criteria were documented non-sustained ventricular tachycardia,sustained ventricular tachycardia,ventricular fibrillation,resuscitated cardiac arrest or SCD>30 days post-Fontan completion.Results:Of 1611 patients,20(1.2%)had VA;14(1.0%)had VA without SCD and 6(<1%)had SCD(6%of all deaths recorded in Registry;5 of those had documented VA at the time of arrest and 1 was presumed to be VA-associated).The median age at first VA was 20.5(14–32)years,10(50%)were females,and the median age at Fontan operation was 8(4–17)years.On univariable analysis,hypoplastic left heart syndrome(p=0.03)and older age Fontan operation(p<0.001)were associated with VA.Earlier Fontan era(p<0.003),atriopulmonary Fontan(p<0.001),pre-Fontan atrioventricular valve repair(p=0.013)pre-or post-Fontan atrial arrhythmia(p=0.010)were associated with SCD.Patients with VA had a 3 times higher risk of death or heart transplant(HR 3.27(1.19,8.98),p=0.02).Conclusions:A proportion of people living with a Fontan circulation have malignant VA.Routine VA screening in this cohort is essential.More data are needed to aid risk stratification.

Effect and mechanism of Irbesartan on occurrence of ventricular arrhythmias in rats with myocardial ischemia through connexin43(cx43)

Objective: To explore the effect and mechanism of angiotensin II receptor blockers-Irbesartan on occurrence of ventricular arrhythmias in rats with myocardial ischemia. Methods: Rats with embryonic cardiomyocytes-H9c2 were randomly divided into control group. ischemia group. Irbesartan group and Irbesartan+ischemia group. The cell viability of rats in each group was tested using MTT. Real-time PCR was employed to detect the expression of connexin43 (Cx43) mRNA and western blot to detect the expression of Cx43 and phosphorylated Cx43. SD rats were randomly divided into the sham-operation group (SO). myocardial infarction group (MI). Irbesartan group and MI+ Irbesartan group, with 10 rats in each group. HE staining was employed to observe the change in the pathomorpholouy of left ventricular tissue and TUNEL method to analyze the cell apoptosis in the tissue. The immunofluorescence was adopted to observe the expression and distribution of Cx43 in the left ventricular myocardium and study the change in the expression of Cx43 in the cardiac muscular tissue at mRNA and protein level. Results: The intervention of lrbesartan in the condition of ischemia indicated the significant decrease in the number of necrotic cells. The expression of Cx43 was significantly decreased under the culture of ischemia (P<0.05), but in the presence of Irbesartan, the expression of Cx43 was increased compared with the ischemia group (p<0.01). The results of WB assay showed the similar trend of change at mRNA level. There was the significant difference in the score of ventricular arerythmia between MI group and SO group (P<0.01). The incidence of ventricular tachycardia or ventricular fibrillation was significantly increased compared with the one in SO group (P<0.05). There was the significant difference in the overall score between MI+Irbesartan group and MI group (P<0.05). The expression of Cx43 in the cardiac muscular tissue in MI group was significantly decreased (P<0.01(US) SO group). But the expression of Cx43 was increased after the treatment with Irbesartan. Conclusions: Irbesartan can inhibit the injury of H9c2 cardiomyocytes and the decreased expression of Cx43 that are induced by the ischemic myocardial infarction. Irbesartan can also improve the reconstruction of Cx43 in rats with ischemic myocardium to inhibit the myocardial infarction-induced arrhythmias.

Effects of antiarrhythmic peptide 10 on acute ventricular arrhythmia

Objective:To observe the effects antiarrhythmic peptide 10(AAPIO) aon acute ventricular arrhythmia and the phosphorylation state of ischemic myocardium conncxin.Methods:Acute total ischemia and partial ischemia models were established by ceasing perfusion and ligating the left anterior descending coronary artery in SD rats.The effects of AAP10(1 mg/L) on the incidence rate of ischemia-induced ventricular arrhythmia were observed.The ischemic myocardium was sampled to detect total-Cx43 and NP-Cx43 by immunofluorcsecnt staining and western blotting,the total-Cx43 expression was detected through image analysis system by semi-quantitative analysis.Results:AAP10 could significantly decrease the incidence of ischemia-induced ventricular tachycardia and ventricular fibrillation.During ischemic stage,total ischemia(TI) and AAP10 total ischemia(ATI) groups were compared with partial ischemia(Pi) and AAP10 partial ischemia(API) groups.The rates of incidence for arrhythmia in the ATI and API groups(10%and 0%) were lower than those in the TI and PI groups(60%and 45%).The difference between the two groups was statistically significant(P=0.019,P=0.020).The semi-quantitative analysis results of the ischemic myocardium showed that the total-Cx43 protein expression distribution areas for TI.ATI,PI and API groups were significantly decreased compared with the control group.On the other hand,the NP-Cx43 distribution areas of TI,ATI,PI and API groups were significantly increased compared with the control group(P>0.05).AAP10 could increase the total-Cx43 expression in the ischemic area and decrease the NP-Cx43 expression.Western blot results were consistent with the results of immunofluorescence staining.Conclusions:AAP10 can significantly decrease the rate of incidence of acute ischemia-induced ventricular tachycardia and ventricular fibrillation.Acute ischemic ventricular arrhythmias may have a relationship with the decreased phosphorylation of Cx43 induced by ischemia.AAP10 may stimulate the phosphorylation of Cx43 by increasing the totai-Cx43 expression and decreasing the NP-Cx43 expression in the ischemic area,so as to decrease ventricular arrhythmia.

Continuous Positive Airway Pressure Effectively Alleviates Arrhythmias in Patients with Obstructive Sleep Apnea:Possible Relationship with Counteracting Oxidative Stress

This work is aimed at exploring the clinical efficacy of continuous positive airway pressuie(CPAP)in treatment of patients with arrhythmias combined with obstructive sleep apnea(OSA).Through evaluating serum native thiol,malonaldehyde(MDA)and nicotinamide adenine dinucleotide phosphate oxidase(NADPH oxidase)in these patients and describing the effects on oxidative parameters of CPAP therapy for 3 months,we confirmed the impact of oxidative stress on arrhythmias.A total of 64 patients with OSA combined with arrhythmias were collected from April 2014 to April 2017 with full clinical information.Patients were divided into two groups(paired experiment design):32 patients in group A(control group),who received unchanged anti-arrhythmia treatment and 32 patients in group B,who were subjected to unchanged pharmacological anti-arrhythmia therapy combined with CPAP.OSA related parameters were compared between the two groups after 3-month therapy.And the levels of parameters of oxidative stress in patients were measured before and after CPAP therapy.After 3 months of CPAP therapy,compared with the control group,the percentage of sage N3(NREM 3)and stage R(REM)in total sleep time was significantly increased,while apnea-hypopnea index(AHI)and the Epworth Sleepiness Scale(ESS)score were evidently decreased.Meanwhile,the lowest oxygen saturation(LSpCh)was also elevated after CPAP treatment for 3 months.The CPAP therapy significantly prevented the occurrence of arrhythmias(P<0.05).Both the MDA level and NADPH oxidase levels were significantly lower in the group B than in the group A(P<0.05).But serum native thiol was improved by CPAP treatment(P<0.05).In conclusion,proper use of CPAP therapy provides significant benefits for the treatment of arrhythmia in patients with OSA.

Cardiac arrhythmias and cardiac arrest related to mushroom poisoning: A case report

BACKGROUND Mushroom exposure is a global health issue.The manifestations of mushroom poisoning (MP) may vary.Some species have been reported as rhabdomyolytic,hallucinogenic,or gastrointestinal poisons.Critical or even fatal MPs are mostly attributable to Amanita phalloides,with the development of severe liver or renal failure.Myocardial injury and even cases mimicking ST-segment elevation myocardial infarction (STEMI) have been previously reported,while cardiac arrhythmia or cardiac arrest is not commonly seen.CASE SUMMARY We report a 68-year-old woman with MP who suffered from delirium,seizure,long QT syndrome on electrocardiogram (ECG),severe cardiac arrhythmias of multiple origins,and cardiac arrest.She was intubated and put on blood perfusion.Her kidney and liver functions were intact;creatine kinase-MB was mildly elevated,and then fell within normal range during her hospital stay.We sent the mushrooms she left for translation elongation factor subunit 1α,ribosomal RNA gene sequence,and internal transcribed spacer sequence analyses.There were four kinds of mushrooms identified,two of which were found to be toxic.CONCLUSION This is the first time that we found cardiac toxicity caused by Panaeolus subbalteatus and Conocybe lactea,which were believed to be toxic to the liver,kidney,and brain.We suggest that intensive monitoring and ECG follow-up are essential to diagnose prolonged QT interval and different forms of tachycardia in MP patients,even without the development of severe liver or renal failure.The mechanisms need to be further investigated and clarified based on animal experiments and molecular signal pathways.

Arrhythmia risk in liver cirrhosis

Interactions between the functioning of the heart and the liver have been described, with heart diseases affecting the liver, liver diseases affecting the heart, and conditions that simultaneously affect both. The heart is one of the most adversely affected organs in patients with liver cirrhosis. For example, arrhythmias and electrocardiographic changes are observed in patients with liver cirrhosis. The risk for arrhythmia is influenced by factors such as cirrhotic cardiomyopathy, cardiac ion channel remodeling, electrolyte imbalances,impaired autonomic function, hepatorenal syndrome, metabolic abnormalities, advanced age, inflammatory syndrome, stressful events, impaired drug metabolism and comorbidities. Close monitoring of cirrhotic patients is needed for arrhythmias, particularly when QT intervalprolonging drugs are given, or if electrolyte imbalances or hepatorenal syndrome appear. Arrhythmia risk may persist after liver transplantation due to possible QT interval prolongation, persistence of the parasympathetic impairment, post-transplant reperfusion and chronic immunosuppression, as well as consideration of the fact that the transplant itself is a stressful event for the cardiovascular system. The aims of the present article were to provide a review of the most important data regarding the epidemiology, pathophysiology, and biomarkers of arrhythmia risk in patients with liver cirrhosis, to elucidate the association with long-term outcome, and to propose future research directions.

C-reactive protein as a predictor of malignant ventricular arrhythmias in non-ST elevation myocardial infarction

Objective To investigate whether C-reactive protein (CRP) is a biomarker of malignant ventricular arrhythmias (MVA) occurring in non-ST elevation myocardial infarction (NSTEMI) patients with Global Registry of Acute Coronary events (GRACE) scores < 140. Methods A total of 1450 NSTEMI patients were included in this study. Hs-CRP blood levels were measured via a turbidimetric immunoassay after confirming the diagnosis of NSTEMI with GRACE scores < 140. Results Consistent with prior studies, the MVA occurrence rate in our cohort was 6.7%, and patients with MVA exhibited a reduced left ventricular ejection fraction (46.1%± 6.9% vs. 61.5%± 8.7%, P = 0.032), a higher incidence of Killip classification > 1 (34.1% vs. 24.2%, P < 0.001), an increased surgical revascularization rate (34.1% vs. 9.7%, P < 0.001), and increased mortality (16.5% vs. 5.8%, P < 0.001). Serum hs-CRP levels were higher (P = 0.003) in NSTEMI patients with MVA, and this increase appeared unrelated to other clinical parameters. The C-statistic to discriminate MVA was 0.82 (95% CI: 0.74–0.89). Using receiver operating characteristics analysis, we optimized a cutoff point of 16 mL/L, and the sensitivity and specificity were 95% and 61%, respectively;the positive predictive value was 20% and the negative predictive value was 99%. Conclusions An hs-CRP assay is a potential MVA biomarker in low-risk NSTEMI patients with GRACE scores < 140. If validated in prospective studies, hs-CRP may offer a low-cost supplementary strategy for risk stratification for NSTEMI patients.