The electrical ventricular storm (VES) is defined as multiple sustained ventricular arrhythmias arising in a short time, often refractory to standard antiarrhythmic treatment. The three pillars of the physiopathogenesis of the VES are autonomic dysfunction, triggers, and an altered ventricular substrate. Incessant or highly recurrent ventricular arrhythmia impacts the hemodynamic status by worsening heart failure and increasing mortality. A stepwise, team-based, and tailored therapeutic approach is required to stop ventricular arrhythmia and regain the hemodynamic and electric stability of the patient. The authors focused on describing all currently available therapeutic approaches for VES, intending to establish the best VES therapeutic approaches. This process involves considering the patient’s specific condition, responses to previous treatments, and the potential risks and benefits of each approach. The options range from adjusting antiarrhythmic therapy to reprogramming of the ICD, sedation, epidural anaesthesia, stellate ganglia anaesthetic block, and the use of ECMO or left ventricular assist devices and radiofrequency catheter ablation. Particular attention is paid to the detailed management of genetic primary arrhythmia syndromes like long-QT syndrome, catecholaminergic polymorphic ventricular tachycardia, Brugada syndrome and Wolff–Parkinson–White syndrome, early repolarisation syndrome, right ventricular arrhythmogenic dysplasia, and idiopathic ventricular fibrillation. After overcoming the acute events of VES and obtaining hemodynamic stability, the treatment should shift toward an optimal balance of heart failure therapy, controlling the substrate by revascularisation procedures and resolving other pathology-generating ventricular arrhythmias. This article provides a comprehensive overview of ESV’s current management options using the most efficient strategies known to date.

The COVID-19 pandemic underscores the need for accurate prognostic tools to predict patient outcomes. This study evaluates the effectiveness of four prominent COVID-19 prediction scores—PAINT, ISARIC4C, CHIS, and COVID-GRAM—at two critical time points: at admission and seven days post-symptom onset, to assess their utility in predicting mortality among hospitalized patients. Conducted at the Clinical Emergency Hospital Pius Brînzeu in Timișoara, this retrospective analysis included adult patients hospitalized with confirmed SARS-CoV-2 infection. Eligible patients had complete data for the scores at both time points. Statistical analysis involved ROC curves and logistic regression to assess the scores’ predictive accuracy for mortality. The study included 215 patients, split into 139 survivors and 76 non-survivors. At admission, the PAINT, ISARIC4C, CHIS, and COVID-GRAM scores significantly differentiated between the survival outcomes (p < 0.0001). The best cutoff values at admission were 6.26 for PAINT, 7.95 for ISARIC4C, 5.58 for CHIS, and 0.63 for COVID-GRAM, corresponding to sensitivities of 85.47%, 80.56%, 88.89%, and 83.33% and specificities of 77.34%, 82.12%, 75.01%, and 78.45%, respectively. By day seven, the cutoff values increased, indicating deteriorating conditions in patients who eventually succumbed to the virus. The hazard ratios at admission for exceeding these cutoffs were significant: PAINT (HR = 3.45), ISARIC4C (HR = 2.89), CHIS (HR = 4.02), and COVID-GRAM (HR = 3.15), highlighting the scores’ abilities to predict severe outcomes. One week post symptom onset, these scores’ predictive values and corresponding hazard ratios increased, further validating their prognostic significance over time. The evaluated COVID-19 prediction scores robustly predict mortality at admission and become more predictive by the seventh day of symptom onset. These findings support the use of these scores in clinical settings to facilitate early identification and intervention for high-risk patients, potentially improving patient outcomes during the ongoing global health crisis.