Does Early Coronary Angiography Improve Survival After out-of-Hospital Cardiac Arrest? A Systematic Review With Meta-Analysis

Background

In patients with out-of-hospital cardiac arrest who achieve return of spontaneous circulation, coronary angiography (CAG) might improve outcomes. We conducted a systematic review and meta-analysis to elucidate the benefit and optimal timing of early CAG in comatose out-of-hospital cardiac arrest patients with return of spontaneous circulation.

Trends in Long-Term Mortality After Congenital Heart Surgery

Background

Congenital heart surgery has improved the survival of patients with even the most complex defects, but the long-term survival after these procedures has not been fully described.

A Case of Survival after Cardiac Arrest and 3? Hours of Resuscitation

Although survival rates after cardiac arrest remain low, new techniques are improving patients'' outcomes. We present the case of a 40-year-old man who survived a cardiac arrest that lasted approximately 3½ hours. Resuscitation was performed with strict adherence to American Heart Association/American College of Cardiology Advanced Cardiac Life Support guidelines until bedside extracorporeal membrane oxygenation could be placed. A hypothermia protocol was initiated immediately afterwards. The patient had a full neurologic recovery and was bridged from dual ventricular assist devices to a total artificial heart. On hospital day 160, he underwent orthotopic heart and cadaveric kidney transplantation. On day 179, he was discharged from the hospital in ambulatory condition.To our knowledge, this is the only reported case in which a patient survived with good neurologic outcomes after a resuscitation that lasted as long as 3½ hours. Documented cases of resuscitation with good recovery after prolonged arrest give hope for improved overall outcomes in the future.     

Impact of Chronic Thrombocytopenia on In-Hospital Outcomes After Percutaneous Coronary Intervention

Objectives

This study sought to evaluate the impact of chronic thrombocytopenia (cTCP) on clinical outcomes after percutaneous coronary intervention (PCI).

Should We Perform an Immediate Coronary Angiogram in All Patients After Cardiac Arrest?: Insights From a Large French Registry

Objectives

This study sought to assess the relationship between an immediate invasive strategy and survival after an out-of-hospital cardiac arrest (OHCA) of presumed cardiac cause, according to prognosis evaluated on hospital arrival.

Improved Survival After the Ross Procedure Compared With Mechanical Aortic Valve Replacement

Background

It is unclear whether the Ross procedure offers superior survival compared with mechanical aortic valve replacement (AVR).

New Concepts in Sudden Cardiac Arrest to Address an Intractable Epidemic: JACC State-of-the-Art Review

Sudden cardiac arrest (SCA) is one of the largest causes of mortality globally, with an out-of-hospital survival below 10% despite intense research. This document outlines challenges in addressing the epidemic of SCA, along the framework of respond, understand and predict, and prevent. Response could be improved by technology-assisted orchestration of community responder systems, access to automated external defibrillators, and innovations to match resuscitation resources to victims in place and time. Efforts to understand and predict SCA may be enhanced by refining taxonomy along phenotypical and pathophysiological “axes of risk,” extending beyond cardiovascular pathology to identify less heterogeneous cohorts, facilitated by open-data platforms and analytics including machine learning to integrate discoveries across disciplines. Prevention of SCA must integrate these concepts, recognizing that all members of society are stakeholders. Ultimately, solutions to the public health challenge of SCA will require greater awareness, societal debate and focused public policy.     

Combined Application of Circulatory Assist Devices Following Cardiac Arrest in Patients after Cardiac Surgery

Objectives To evaluate retrospectively the potential benefits of combined utilization of various assisted circulation devices in cardiac arrest patients who did not respond to conventional cardiopulmonary cerebral resuscitation (CPCR). Methods Assisted circulation devices, including emergency cardiopulmonary bypass (ECPB), intra-aortic balloon pump (IABP), and left ventricular assist device (LVAD), were applied to 16 adult patients who had cardiac arrest 82 min-56 h after open heart surgery and did not respond to 20 min or longer conventional CPCR. ECPB was applied to 2 patients, ECPB plus IABP to 8 patients, ECPB plus IABP and LVAD to 6 patients. Results One patient recovered fully and one patient died. Of the other 14 patients, 13 resumed spontaneous cardiac rhythm and one did not; none of them could be weaned from ECPB. Further treatment of the 14 patients with combinations of assisted circulation devices enabled 6 patients to recover. One of the 7 recovered patients died of reoccurring cardiac arrest after 11 days; the other 6 were discharged in good condition and were followed up for 3 -49 months (mean =22 months). Of the 6 discharged patients one suffered cerebral embolism during LVAD treatment, resulting in mild limitation of mobility of the right limbs; the other 5 never manifested any central nervous system complications. There was no late deaths giving a 37.5% (6/16) long-term survival rate. Conclusions ECPB could effectively reestablish blood circulation and oxygen supply, rectify acidosis, and improve internal milieu. The combined utilization of ECPB, IABP, and LVAD reduces the duration of ECPB, improves the incidence of recovery, and offers beneficial alternatives to refractory cardiac arrest patients.     

Machine Learning Prediction Models for In-Hospital Mortality After Transcatheter Aortic Valve Replacement

ObjectivesThis study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.BackgroundExisting risk prediction tools for in-hospital complications in patients undergoing TAVR have been designed using statistical modeling approaches and have certain limitations.MethodsPatient data were obtained from the National Inpatient Sample database from 2012 to 2015. The data were randomly divided into a development cohort (n = 7,615) and a validation cohort (n = 3,268). Logistic regression, artificial neural network, naive Bayes, and random forest machine learning algorithms were applied to obtain in-hospital mortality prediction models.ResultsA total of 10,883 TAVRs were analyzed in our study. The overall in-hospital mortality was 3.6%. Overall, prediction models’ performance measured by area under the curve were good (>0.80). The best model was obtained by logistic regression (area under the curve: 0.92; 95% confidence interval: 0.89 to 0.95). Most obtained models plateaued after introducing 10 variables. Acute kidney injury was the main predictor of in-hospital mortality ranked with the highest mean importance in all the models. The National Inpatient Sample TAVR score showed the best discrimination among available TAVR prediction scores.ConclusionsMachine learning methods can generate robust models to predict in-hospital mortality for TAVR. The National Inpatient Sample TAVR score should be considered for prognosis and shared decision making in TAVR patients.