More than 40 years after the first implantable cardioverter-defibrillator (ICD) implantation, sudden cardiac death (SCD) still accounts for more than five million deaths worldwide every year. Huge efforts in the field notwithstanding, it is now increasingly evident that the current strategy of long-term prevention based on left ventricular ejection fraction as the key selection criterion is actually of very limited impact, also because the largest absolute numbers of SCD are encountered in the general population not known to be at risk. It has been recently reemphasized that SCD is often not so sudden, with almost half of the victims experiencing typical warning symptoms preceding the event. Importantly, heeded and prompt medical attention can dramatically improve survival. Essentially, such timely action increases the chances of the SCD event being witnessed by emergency medical services and provides the opportunity for early intervention. In addition, newer technologies incorporating digital data acquisition, transfer between interconnected devices, and artificial intelligence, should allow dynamic, real-time monitoring of diverse parameters and therefore better identification of subjects at short-term SCD risk. Along with warning symptoms, these developments allow a new approach of near-term prevention based on the hours and minutes preceding SCD. In the present review, we challenge the current paradigm of mid- and long-term prevention using ICD in patients at the highest risk of SCD, and introduce a complementary concept applicable to the entire population that would aim to pre-empt SCD by timely detection and intervention within the minutes or hours prior to the event.
Keywords: Artificial intelligence; Implantable cardioverter-defibrillator; Near-term prevention; Remote monitoring; Sudden cardiac death; Symptoms.
© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Cardiology.