New research published in the European Heart Journal (a journal of the European Society of Cardiology [ESC]) shows that it is extremely difficult to predict with accuracy among patients who have had a heart attack those who will go on to suffer a sudden cardiac death, even among those with a left ventricular ejection fraction (LVEF) of 35% or lower – commonly used as a justification for prophylactic defibrillator implantation in those patients.
The authors of the study are an international consortium (partners of the EU-funded PROFID project and further data providers) including Professor Niels Peek, University of Manchester, Manchester, UK and The Healthcare Improvement Studies Institute (THIS Institute), University of Cambridge, Cambridge, UK; Professor Gerhard Hindricks and Dr Nikolaos Dagres of Deutsches Herzzentrum der Charité, Berlin, Germany, and colleagues. The PROFID project, which also includes the large PROFID EHRA clinical trial, is funded by the European Union's Horizon 2020 research and innovation programme. The findings of the study have provided the scientific foundation for the PROFID EHRA clinical trial, which is expected to change sudden cardiac death (SCD) prevention in clinical practice.
Sudden cardiac death is the leading cause of death, accounting for around 20% of deaths in Europe. Patients with previous myocardial infarction (heart attack) are at particular risk due to life-threatening ventricular arrhythmias (irregular heartbeats). The implantable cardioverter-defibrillator (ICD) detects and terminates these arrhythmias. However, defibrillator therapy is limited by the profound difficulty to identify patients at elevated sudden cardiac death risk as candidates for implantation.
Risk stratification of sudden cardiac death after heart attack and prevention by defibrillator currently rely on LVEF. However, improved risk stratification across the whole LVEF range (patients with LVEF ≤ 35% and also patients with LVEF > 35%) is required for decision-making on defibrillator implantation.
With this background, the authors pooled in this study 20 data sets from Europe, USA and Israel with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). The primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy.
There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In all of these three subgroups, LVEF poorly predicted sudden cardiac death. Considering additional parameters – including demographics, medical history, clinical parameters, biomarkers, medication, electrocardiography, and echocardiography (and, in a subset of data sets and patients, cardiac magnetic resonance imaging) - did not improve the predictive performance for the risk of sudden cardiac death across the three subgroups.
Professor Peek says: "The current analysis did not yield a tool that predicted the individual sudden cardiac death risk with satisfactory accuracy across a wide range of geographically dispersed datasets. Whether this result is related to the nature of sudden cardiac death or to inherent limitations of respective datasets cannot be answered. But the finding is consistent with mounting evidence that it is not possible to develop universally valid prediction models. In this case, a key inherent limitation lies on correct adjudication of cause of death. Misclassifications of cause of death are indeed frequent, reducing the performance of models for sudden cardiac death prediction. Furthermore, sudden cardiac death is the result of a complex, highly dynamic interplay of multiple factors that is difficult to capture, especially with single-time assessments."
He adds: "We cannot exclude the possibility that future research may discover novel biomarkers (for instance, genetic or imaging biomarkers, particularly using advanced AI techniques) with which it is possible to better predict the risk of sudden cardiac death, although the low incidence rate and the adjudication of the cause of death will always remain major challenges."
The ICD therapy rates in patients with an ICD and an LVEF ≤35% were significantly higher than the rates of sudden cardiac death in patients with an LVEF ≤35% but without an ICD. Although this finding may relate to some extent to differences between these two groups, it also suggests that only a portion of ICD therapies was lifesaving.
Professor Hindricks further explains: "A further limitation of the analysis is the large heterogeneity of the analysed data sets. This was dictated by the need to combine different data sets in order to achieve the sample size that is required to study the rare outcome of sudden cardiac death. These differences in design, data, outcome ascertainment, and follow-up of the analysed cohorts limit the strength of the conclusions. This indicates the need for contemporary data on sudden cardiac death prevention by ICD implantation after myocardial infarction."
Dr Dagres adds: "Recently introduced drugs for heart failure treatment such as sodium–glucose co-transporter 2 inhibitors or angiotensin receptor– neprilysin inhibitors were not available or not yet standard at the time of most cohorts. Therefore, it is unclear whether the results of the presented analysis are well applicable in patients treated with contemporary optimal therapy including these recently introduced agents and the latest revascularisation strategies."
The authors also emphasize that "In patients with LVEF > 35%, the lack of acceptably accurate risk stratification tools combined with the very low sudden cardiac death risk questions the feasibility of attempts at identification of high- risk candidates for targeted protection by defibrillator".
They conclude: "In patients with previous myocardial infarction, LVEF had poor predictive performance for the risk of sudden cardiac death among patients with severely impaired LVEF and among those with moderately reduced or preserved LVEF. The consideration of a large variety and wide spectrum of further candidate predictors did not improve the predictive performance. Thus, more accurate risk stratification and in particular identification of low-risk individuals with severely reduced LVEF as candidates for omission of defibrillator protection or of high-risk individuals with preserved LVEF as candidates for targeted defibrillator protection was not feasible, neither using LVEF nor using various other candidate predictors."
The authors say that the findings, demonstrating inability of LVEF and a range of other common variables to predict sudden cardiac death, "question the feasibility of approaches for personalised decision-making on defibrillator implantation. Considering the declining risk for sudden death, the effect of recently introduced heart failure drugs, the fact that non-sudden deaths account for the large majority of deaths in this population, and the still considerable complication rate of the devices, a re-evaluation of the benefit of routine prophylactic defibrillator implantation in patients with LVEF ≤ 35% appears necessary."
Therefore, as part of the PROFID project, the large scaled PROFID EHRA clinical trial is currently underway, which is re-evaluating the role of ICD implantation in post-myocardial infarction patients in the context of contemporary medical treatment. Important new information to optimally guide therapy is expected, that will address this serious health issue.
In a linked commentary, Dr Ezimamaka C Ajufo and Dr Usha B Tedrow, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA, say: "How should we identify individuals most likely to benefit from a primary prevention ICD post-MI? We agree with the core message of the present work that all individuals post-MI should be stratified for sudden cardiac death (SCD), irrespective of LVEF. The ideal approach would be easily applicable, multicomponent, and iterative. One possibly could leverage machine learning (AI) to integrate information from the medical record in order to screen all individuals post-MI for increased risk for SCD. Those found to be at persistently increased risk beyond the early MI period could then undergo targeted risk stratification, either invasively or non-invasively. Development of such a paradigm would need to utilise algorithms trained on a detailed modern dataset. Further, any proposed modifications to the current paradigm for prevention ICDs should clearly be tested in clinical trials prior to being considered for implementation."
