Handling of Ventricular Fibrillation in the Emergency Setting

A successful case of electrical storm rescue after acute myocardial infarction

BACKGROUND

Electrical storm (ES) is a heterogeneous clinical emergency that can present with malignant ventricular arrhythmias such as ventricular fibrillation (VF), ventricular tachycardia (VT), requiring the need for cardiac defibrillation. ES is a life-threatening condition with a high mortality rate. Successfully managing ES in the setting of acute myocardial infarction (MI) is expected to be known by physicians on call to reduce in-hospital mortality.

CASE PRESENTATION

A 57-year-old man presenting with acute onset chest pain was found to have an infero-posterior ST-segment elevation myocardial infarction (STEMI) complicated by acute right ventricular MI secondary to total occlusion of the proximal right coronary artery (RCA). The patient developed ES in the form of recurrent VF that was managed successfully with electrical defibrillation, antiarrhythmic therapy with amiodarone and esmolol, endotracheal intubation, sedation, electrolyte replacement, volume resuscitation, comfort care, psychological intervention, and percutaneous coronary intervention (PCI) of the occluded epicardial artery. With these interventions used in quick succession and with the aspiration of a massive RCA thrombus, the patient was reversed to hemodynamic stability, did not have further episodes of VF, and survived the index hospitalization.

CONCLUSION

ES is a rare but fatal complication of acute MI. Residents on night shifts should be better prepared and equipped to deal with this rare condition. We hope our successful experience can benefit physicians on call who take care of acute MI patients that deteriorate with ES.

Critical Requirements for the Initiation of a Cardiac Arrhythmia in Rat Ventricle: How Many Myocytes?

Cardiovascular disease is the leading cause of death worldwide due in a large part to arrhythmia. In order to understand how calcium dynamics play a role in arrhythmogenesis, normal and dysfunctional Ca²⁺ signaling in a subcellular, cellular, and tissued level is examined using cardiac ventricular myocytes at a high temporal and spatial resolution using multiscale computational modeling. Ca²⁺ sparks underlie normal excitation-contraction coupling. However, under pathological conditions, Ca²⁺ sparks can combine to form Ca²⁺ waves. These propagating elevations of (Ca²⁺)_i can activate an inward Na⁺-Ca²⁺ exchanger current (I_NCX) that contributes to early after-depolarization (EADs) and delayed after-depolarizations (DADs). However, how cellular currents lead to full depolarization of the myocardium and how they initiate extra systoles is still not fully understood. This study explores how many myocytes must be entrained to initiate arrhythmogenic depolarizations in biophysically detailed computational models. The model presented here suggests that only a small number of myocytes must activate in order to trigger an arrhythmogenic propagating action potential. These conditions were examined in 1-D, 2-D, and 3-D considering heart geometry. The depolarization of only a few hundred ventricular myocytes is required to trigger an ectopic depolarization. The number decreases under disease conditions such as heart failure. Furthermore, in geometrically restricted parts of the heart such as the thin muscle strands found in the trabeculae and papillary muscle, the number of cells needed to trigger a propagating depolarization falls even further to less than ten myocytes.

Prediction and classification of ventricular arrhythmia based on phase-space reconstruction and fuzzy c-means clustering

BACKGROUND AND OBJECTIVE

Prediction and classification of Ventricular Arrhythmias (VA) may allow clinicians sufficient time to intervene for stopping its escalation to Sudden Cardiac Death (SCD). This paper proposes a novel method for predicting VA and classifying its type, in particular, the fatal VA even before the event occurs.

METHODS

A statistical index J based on the combination of phase-space reconstruction (PSR) and box counting has been used to predict VA. The fuzzy c-means (FCM) clustering technique is applied for the classification of impending VA.

RESULTS

32 healthy and 32 arrhythmic subjects from two open databases - PTB Diagnostic database (PTBDB) and CU Ventricular Tachyarrhythmia (CUDB) database respectively; were used to validate our proposed method. Our method showed average prediction time of approximately 5 min (4.97 min) for impending VA in the tested dataset while classifying four types of VA (VA without ventricular premature beats (VPBs), ventricular fibrillation (VF), ventricular tachycardia (VT), and VT followed by VF) with an average 4 min (approximately) before the VA onset, i.e., after 1 min of the prediction time point with average accuracy of 98.4%, a sensitivity of 97.5% and specificity of 99.1%.

CONCLUSIONS

The results obtained can be used in clinical practice after rigorous clinical trial to advance technologies such as implantable cardioverter defibrillator (ICD) that can help to preempt the occurrence of fatal ventricular arrhythmia - a main cause of SCD.

Two Targets, One Hit: new Anticancer Therapeutics to Prevent Tumorigenesis Without Cardiotoxicity

A serious adverse effect of cancer therapies is cardiovascular toxicity, which significantly limits the widespread use of antineoplastic agents. The promising new field of cardio-oncology offers the identification of potent anti-cancer therapeutics that effectively inhibit cancer cell proliferation without causing cardiotoxicity. Future introduction of recently identified cardio-safe compounds into clinical practice (including ERK dimerization inhibitors or BAX allosteric inhibitors) is expected to help oncologists avoid unwanted cardiological complications associated with therapeutic interventions.