Cardiac arrest among patients with infections: causes, clinical practice and research implications

Acute Adenoviral Infection Elicits an Arrhythmogenic Substrate Prior to Myocarditis

BACKGROUND

Viral cardiac infection represents a significant clinical challenge encompassing several etiological agents, disease stages, complex presentation, and a resulting lack of mechanistic understanding. Myocarditis is a major cause of sudden cardiac death in young adults, where current knowledge in the field is dominated by later disease phases and pathological immune responses. However, little is known regarding how infection can acutely induce an arrhythmogenic substrate before significant immune responses. Adenovirus is a leading cause of myocarditis, but due to species specificity, models of infection are lacking, and it is not understood how adenoviral infection may underlie sudden cardiac arrest. Mouse adenovirus type-3 was previously reported as cardiotropic, yet it has not been utilized to understand the mechanisms of cardiac infection and pathology.

METHODS

We have developed mouse adenovirus type-3 infection as a model to investigate acute cardiac infection and molecular alterations to the infected heart before an appreciable immune response or gross cardiomyopathy.

RESULTS

Optical mapping of infected hearts exposes decreases in conduction velocity concomitant with increased Cx43Ser368 phosphorylation, a residue known to regulate gap junction function. Hearts from animals harboring a phospho-null mutation at Cx43Ser368 are protected against mouse adenovirus type-3-induced conduction velocity slowing. Additional to gap junction alterations, patch clamping of mouse adenovirus type-3-infected adult mouse ventricular cardiomyocytes reveals prolonged action potential duration as a result of decreased IK1 and IKs current density. Turning to human systems, we find human adenovirus type-5 increases phosphorylation of Cx43Ser368 and disrupts synchrony in human induced pluripotent stem cell-derived cardiomyocytes, indicating common mechanisms with our mouse whole heart and adult cardiomyocyte data.

CONCLUSIONS

Together, these findings demonstrate that adenoviral infection creates an arrhythmogenic substrate through direct targeting of gap junction and ion channel function in the heart. Such alterations are known to precipitate arrhythmias and likely contribute to sudden cardiac death in acutely infected patients.

Use of machine learning algorithms to predict life-threatening ventricular arrhythmia in sepsis

Aims

Life-threatening ventricular arrhythmias (LTVAs) are common manifestations of sepsis. The majority of sepsis patients with LTVA are unresponsive to initial standard treatment and thus have a poor prognosis. There are very limited studies focusing on the early identification of patients at high risk of LTVA in sepsis to perform optimal preventive treatment interventions. We aimed to develop a prediction model to predict LTVA in sepsis using machine learning (ML) approaches.

Methods and results

Six ML algorithms including CatBoost, LightGBM, and XGBoost were employed to perform the model fitting. The least absolute shrinkage and selection operator (LASSO) regression was used to identify key features. Methods of model evaluation involved in this study included area under the receiver operating characteristic curve (AUROC), for model discrimination, calibration curve, and Brier score, for model calibration. Finally, we validated the prediction model both internally and externally. A total of 27 139 patients with sepsis were identified in this study, 1136 (4.2%) suffered from LTVA during hospitalization. We screened out 10 key features from the initial 54 variables via LASSO regression to improve the practicability of the model. CatBoost showed the best prediction performance among the six ML algorithms, with excellent discrimination (AUROC = 0.874) and calibration (Brier score = 0.157). The remarkable performance of the model was presented in the external validation cohort (n = 9492), with an AUROC of 0.836, suggesting certain generalizability of the model. Finally, a nomogram with risk classification of LTVA was shown in this study.

Conclusion

We established and validated a machine leaning-based prediction model, which was conducive to early identification of high-risk LTVA patients in sepsis, thus appropriate methods could be conducted to improve outcomes.

Comparison the efficacy of amiodarone and lidocaine for cardiac arrest: A network meta-analysis

BACKGROUND

There is no evidence that antiarrhythmic drugs can improve long-term survival or survival with favorable neurological outcomes in cardiac arrest patients. We did this network meta-analysis to comprehensively compare the efficacy of various antiarrhythmic drugs for cardiac arrest patients.

METHODS

We searched studies from inception until Nov 11, 2022 through PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, and Wanfang database. All studies comparing different antiarrhythmic drugs for cardiac arrest were included in this meta-analysis. Outcomes were survival to hospital discharge in cardiac arrest, survival to hospital admission/24 h and favorable neurological outcome. This network meta-analysis was performed by R software.

RESULTS

Finally, a total of 9 studies (10,980 patients) were finally included in this network meta-analysis. Amiodarone (odd ratio [OR] 2.28, 95% credibility interval [CrI] 1.61-3.27) and lidocaine (OR 1.53, 95% CrI 1.05-2.25) was superior than placebo in terms of the survival to hospital admission/24 h with statistically significant. Amiodarone (OR 2.19, 95% CrI 1.54-3.14) and lidocaine (OR 1.58, 95% CrI 1.09-2.32) was superior than placebo in terms of the survival to hospital discharge with statistically significant. Amiodarone (OR 2.43, 95% CrI 1.61-3.68) and lidocaine (OR 1.62, 95% CrI 1.04-2.53) was superior than placebo in terms of the favorable neurological outcome with statistically significant. The surface under the cumulative ranking (SUCRA) shows that amiodarone ranked first (SUCRA, 99.6%), lidocaine ranked second (SUCRA, 49.6%), placebo ranked the last (SUCRA, 0.86%). Inverted funnel plot is essentially symmetrical, it is possible that this study has a small sample effect or a small publication bias.

CONCLUSIONS

Amiodarone had the best effect on both survival to hospital admission, discharge and more favorable neurological outcome. Thus, amiodarone should be listed as first line drug for cardiac arrest. However, the quality of available evidence limits the formation of powerful conclusions regarding the comparative efficacy or safety of amiodarone or lidocaine used to treat cardiac arrest. Higher-quality randomized controlled trials are required for further research in future.

C-reactive Protein Elevation Is Associated With QTc Interval Prolongation in Patients Hospitalized With COVID-19

Background

The relationship between inflammation and corrected QT (QTc) interval prolongation is currently not well defined in patients with COVID-19.

Objective

This study aimed to assess the effect of marked interval changes in the inflammatory marker C-reactive protein (CRP) on QTc interval in patients hospitalized with COVID-19.

Methods

In this retrospective cohort study of hospitalized adult patients admitted with COVID-19 infection, we identified 85 patients who had markedly elevated CRP levels and serial measurements of an ECG and CRP during the same admission. We compared mean QTc interval duration, and other clinical and ECG characteristics between times when CRP values were high and low. We performed mixed-effects linear regression analysis to identify associations between CRP levels and QTc interval in univariable and adjusted models.

Results

Mean age was 58 ± 16 years, of which 39% were women, 41% were Black, and 25% were White. On average, the QTc interval calculated via the Bazett formula was 15 ms higher when the CRP values were “high” vs. “low” [447 ms (IQR 427–472 ms) and 432 ms (IQR 412–452 ms), respectively]. A 100 mg/L increase in CRP was associated with a 1.5 ms increase in QTc interval [β coefficient 0.15, 95% CI (0.06–0.24). In a fully adjusted model for sociodemographic, ECG, and clinical factors, the association remained significant (β coefficient 0.14, 95% CI 0.05–0.23).

Conclusion

An interval QTc interval prolongation is observed with a marked elevation in CRP levels in patients with COVID-19.

Risk of Permanent Pacemaker Implantation Following Bentall Operation

Conduction disorders following cardiac surgery are common complications with incidences of permanent pacemaker dependency up to 5%. However, data on pacemaker implantation rates in the long-term follow-up after Bentall operations are scarce. In a retrospective study, a mixed cohort of 260 patients including endocarditis and aortic dissection undergoing Bentall operation between March 1996 and December 2015 was analyzed. Median follow-up time was 60 (12-107) months. Early and late rates of permanent pacemaker implantation and associated risk factors were investigated. In the postoperative course 31 (11.9%) permanent pacemakers were implanted. The 30-day incidence of pacemaker implantations was 7.7% with operations performed after a median of 6 (3-12) days after the Bentall operation. After ten years, 21% of the Bentall patients were permanent pacemaker dependent. The risk factors for permanent pacemaker dependency included age above 75 years (16.1% vs 5.7%; P < 0.001), preoperative cardiac conduction disturbance (32.3% vs 22.7%, P = 0.018), aortic valve stenosis (38.7% vs 23.1, P = 0.008), infective endocarditis (19.4% vs 7.4%, P = 0.004), tricuspid valve reconstruction (6.5% vs 0.9%, P = 0.033), sepsis (12.9% vs 4.4%, P < 0.001) and non-cardiac reoperation (19.4% vs 8.7%, P = 0.004). Pacemaker implantation significantly increased the length of initial hospitalization (13 [8-26] days vs 8 [7-13] days; P = 0.003). In the long-term follow-up, mortality was not different between the groups. Permanent pacemaker dependency is a frequent complication in the short- and long-term follow-up after Bentall operations. Screening for cardiac conduction disturbances in the short- and long-term follow-up is recommended.

The prevalence of bacteremia in out of hospital cardiac arrest patients presenting to the emergency department of a tertiary care hospital

BACKGROUND

Out-of-hospital cardiac arrest (OHCA) remains one of the most common causes of death. There is a scarcity of evidence concerning the prevalence of bacteraemia in cardiac arrest patients presenting to the Emergency Department (ED). We aimed to determine the prevalence of bacteraemia in OHCA patients presenting to the ED, as well as study the association between bacteraemia and in-hospital mortality in OHCA patients. In addition, the association between antibiotic use during resuscitation and in-hospital mortality was examined.

METHODS AND RESULTS

This was a study of 200 adult OHCA patients who presented to the ED between 2015 and 2019. Bacteraemia was confirmed if at least one of the blood culture bottles grew a non-skin flora pathogen or if two blood culture bottles grew a skin flora pathogen from two different sites. The prevalence of bacteraemia was 46.5%. Gram positive bacteria, specifically Staphylococcus species, were the most common pathogens isolated from the bacteremic group. 42 patients survived to hospital admission. The multivariate analysis revealed that there was no association between bacteraemia and hospital mortality in OHCA patients (OR = 1.3, 95% CI= 0.2-9.2) with a p-value of .8. There was no association between antibiotic administration during resuscitation and hospital mortality (OR = 0.6, 95% CI= 0.1 - 3.8) with a p-value of .6.

CONCLUSION

In our study, the prevalence of bacteraemia among OHCA patients presenting to the ED was found to be 46.5%. Bacteremic and non-bacteremic OHCA patients had similar initial baseline characteristics and laboratory parameters except for higher serum creatinine and BUN in the bacteremic group. In OHCA patients who survived their ED stay there was no association between hospital mortality and bacteraemia or antibiotic administration during resuscitation. There is a need for randomised controlled trials with a strong patient oriented primary outcome to better understand the association between in-hospital mortality and bacteraemia or antibiotic administration in OHCA patients.KEY MESSAGESWe aimed to determine the prevalence of bacteraemia in OHCA patients presenting to the Emergency Department. In our study, we found that 46.5% of patients presenting to our ED with OHCA were bacteremic.Bacteremic and non-bacteremic OHCA patients had similar initial baseline characteristics and laboratory parameters except for higher serum creatinine and BUN in the bacteremic group.We found no association between bacteraemia and hospital mortality. There was no association between antibiotic administration during resuscitation and hospital mortality.There is a need for randomised controlled trials with a strong patient oriented primary outcome to better understand the association between in-hospital mortality and bacteraemia or antibiotic administration in OHCA patients.

Cardiac Arrest in an Extensive Pulmonary Tuberculosis Patient

Tuberculosis (TB) disease affects a large population worldwide but is often missed. Early diagnosis can be challenging at times due to failure to include TB in the differential diagnoses. Tuberculosis is a treatable disease but it can lead to undesirable consequences if left untreated. Here we report a case of a young Guatemalan woman presented with respiratory failure and extensive lung opacification on imaging who went into cardiac arrest. Post resuscitation, workup was significant for Mycobacterium tuberculosis (TB) on sputum smear. Despite appropriate treatment, she expired. The aim of this paper is to summarize TB complications that directly contribute to mortality as many clinicians do not consider TB as an immediate cause of death.

Independent Risk Factors for Sepsis-Associated Cardiac Arrest in Patients with Septic Shock

The clinical characteristics and laboratory values of patients with septic shock who experience in-hospital cardiac arrest (IHCA) have not been well studied. This study aimed to evaluate the prevalence of IHCA after admission into the emergency department and to identify the factors that increase the risk of IHCA in septic shock patients. This observational cohort study used a prospective registry of septic shock patients and was conducted at the emergency department of a university-affiliated hospital. The data of 887 adult (age ≥ 18 years) septic shock (defined using the Sepsis-3 criteria) patients who were treated with a protocol-driven resuscitation bundle therapy and were admitted to the intensive care unit between January 2010 and September 2018 were analyzed. The primary endpoint was the occurrence of sepsis-associated cardiac arrest. The patient mean age was 65 years, and 61.8% were men. Sepsis-associated cardiac arrest occurred in 25.3% of patients (n = 224). The 28-day survival rate after cardiac arrest was 6.7%. Multivariate logistic regression identified chronic pulmonary disease (odds ratio (OR) 2.06), hypertension (OR 0.48), unknown infection source (OR 1.82), a hepatobiliary infection source (OR 0.25), C-reactive protein (OR 1.03), and serum lactate level 6 h from shock (OR 1.34). Considering the high mortality rate of sepsis-associated cardiac arrest after cardiopulmonary resuscitation, appropriate monitoring is required in septic shock patients with major risk factors for IHCA.

Cardiac Arrest Risk During Acute Infections: Systemic Inflammation Directly Prolongs QTc Interval via Cytokine-Mediated Effects on Potassium Channel Expression

BACKGROUND

During acute infections, the risk of malignant ventricular arrhythmias is increased, partly because of a higher propensity to develop QTc prolongation. Although it is generally believed that QTc changes almost exclusively result from concomitant treatment with QT-prolonging antimicrobials, direct effects of inflammatory cytokines on ventricular repolarization are increasingly recognized. We hypothesized that systemic inflammation per se can significantly prolong QTc during acute infections, via cytokine-mediated changes in K⁺ channel expression.

METHODS

We evaluated (1) the frequency of QTc prolongation and its association with inflammatory markers, in patients with different types of acute infections, during active disease and remission; (2) the prevalence of acute infections in a cohort of consecutive patients with Torsades de Pointes; (3) the relationship between K⁺ channel mRNA levels in ventricles and peripheral blood mononuclear cells and their changes in patients with acute infection over time.

RESULTS

In patients with acute infections, regardless of concomitant QT-prolonging antimicrobial treatments, QTc was significantly prolonged but rapidly normalized in parallel to CRP (C-reactive protein) and cytokine level reduction. Consistently in the Torsades de Pointes cohort, concomitant acute infections were highly prevalent (30%), despite only a minority (25%) of these cases were treated with QT-prolonging antimicrobials. KCNJ2 K⁺ channel expression in peripheral blood mononuclear cell, which strongly correlated to that in ventricles, inversely associated to CRP and IL (interleukin)-1 changes in acute infection patients.

CONCLUSIONS

During acute infections, systemic inflammation rapidly induces cytokine-mediated ventricular electrical remodeling and significant QTc prolongation, regardless concomitant antimicrobial therapy. Although transient, these changes may significantly increase the risk of life-threatening ventricular arrhythmia in these patients. It is timely and warranted to transpose these findings to the current coronavirus disease 2019 (COVID-19) pandemic, in which both increased amounts of circulating cytokines and cardiac arrhythmias are demonstrated along with a frequent concomitant treatment with several QT-prolonging drugs. Graphic Abstract: A graphic abstract is available for this article.

Integrin ανβ3 modulates lipopolysaccharide-induced hyperpermeability in cardiac microvascular endothelial cells

Previous studies suggest an association of cardiac microvascular endothelial cells (CMECs) hyperpermeability with sepsis-related cardiac injury. Our results showed that CMECs permeability was dependent upon concentration and time of lipopolysaccharides (LPS) stimulation. Integrin ανβ3 expression decreased after LPS stimulation. Pretreatment with anti-integrin ανβ3 antibody enhanced LPS-induced hyperpermeability. Upregulation of integrin ανβ3 decreased LPS-induced hyperpermeability. F-actin remodeling was enhanced after LPS stimulation and was inhibited by up-regulation of integrin ανβ3. Inhibition of Src or Rac1 reduced CMECs permeability after LPS stimulation, but there were no differences in the phosphorylation of Src and Rac1 when over-expressing or blocking integrin β3. After pretreatment with Src or Rac1 inhibitor, no significant difference was found in the expression of integrin ανβ3 in LPS-induced CMECs. These finding suggested that integrin ανβ3 overexpression decreased LPS-stimulated CMECS permeability by inhibition of cytoskeletal remodeling, but the mechanism might not be mediated via Src/Rac1 signaling.

An intelligent warning model for early prediction of cardiac arrest in sepsis patients

BACKGROUND

Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have been conducted to predict cardiac arrest using machine learning. However, no previous research has used machine learning for predicting cardiac arrest in adult sepsis patients. Moreover, the potential of some techniques, including ensemble algorithms, has not yet been addressed in improving the prediction outcomes. It is required to find methods for generating high-performance predictions with sufficient time lapse before the arrest. In this regard, various variables and parameters should also been examined.

OBJECTIVE

The aim was to use machine learning in order to propose a cardiac arrest prediction model for adult patients with sepsis. It is required to predict the arrest several hours before the incidence with high efficiency. The other goal was to investigate the effect of the time series dynamics of vital signs on the prediction of cardiac arrest.

METHOD

30 h clinical data of every sepsis patients were extracted from Mimic III database (79 cases, 4532 controls). Three datasets (multivariate, time series and combined) were created. Various machine learning models for six time groups were trained on these datasets. The models included classical techniques (SVM, decision tree, logistic regression, KNN, GaussianNB) and ensemble methods (gradient Boosting, XGBoost, random forest, balanced bagging classifier and stacking). Proper solutions were proposed to address the challenges of missing values, imbalanced classes of data and irregularity of time series.

RESULTS

The best results were obtained using a stacking algorithm and multivariate dataset (accuracy = 0.76, precision = 0.19, sensitivity = 0.77, f1-score = 0.31, AUC= 0.82). The proposed model predicts the arrest incidence of up to six hours earlier with the accuracy and sensitivity over 70%.

CONCLUSION

We illustrated that machine learning techniques, especially ensemble algorithms have high potentials to be used in prognostic systems for sepsis patients. The proposed model, in comparison with the exiting warning systems including APACHE II and MEWS, significantly improved the evaluation criteria. According to the results, the time series dynamics of vital signs are of great importance in the prediction of cardiac arrest incidence in sepsis patients.

3D printing approaches for cardiac tissue engineering and role of immune modulation in tissue regeneration

Conventional tissue engineering, cell therapy, and current medical approaches were shown to be successful in reducing mortality rate and complications caused by cardiovascular diseases (CVDs). But still they have many limitations to fully manage CVDs due to complex composition of native myocardium and microvascularization. Fabrication of fully functional construct to replace infarcted area or regeneration of progenitor cells is important to address CVDs burden. Three-dimensional (3D) printed scaffolds and 3D bioprinting technique have potential to develop fully functional heart construct that can integrate with native tissues rapidly. In this review, we presented an overview of 3D printed approaches for cardiac tissue engineering, and advances in 3D bioprinting of cardiac construct and models. We also discussed role of immune modulation to promote tissue regeneration.