Heart Failure Patients Unresponsive to Implantable Cardioverter-Defibrillator Therapy: A Neglected Problem
Bibliographic record
Abstract
After publication of the DANISH (Danish Study to Assess the Efficacy of ICDs in Patients with Non-ischemic Systolic Heart Failure on Mortality) trial,1 a debate has arisen in the cardiologists' community on the clinical benefit of implantable cardioverter-defibrillator (ICD) in the modern therapy of non-ischaemic heart failure (HF) patients,2 selected according to the current ICD guideline recommendations (i.e. ejection fraction value and HF functional class).3 The DANISH trial is a recent large randomized controlled trial that compared ICD therapy vs. optimal medical treatment in patients with non-ischaemic cardiomyopathy, and reported no mortality benefit of ICD therapy.1 In support of the current guidelines, recent meta-analyses showed instead a statistically significant clinical efficacy of ICD therapy by pooling DANISH results with those of the earlier studies carried out in the 2000s.4 In this debate, little attention has been paid to the different factors concurring to ICD clinical benefit and to their evolution over time. The clinical benefit of ICD therapy in patients with HF and low ejection fraction is mainly determined by: (i) the baseline risk of total mortality, cardiac death, and sudden cardiac death (SCD); (ii) the percentage of ICD-unresponsive patients (i.e. patients experiencing SCD despite ICD implantation). In particular, the unresponsiveness of patients to ICD therapy and its detrimental effects on ICD clinical benefit are a crucial, but fairly neglected problem.5
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".