Implantable cardiac defibrillator and mortality in non-ischaemic cardiomyopathy: an updated meta-analysis
Bibliographic record
Abstract
Objectives The benefit of implantable cardiac defibrillator (ICD) in symptomatic patients with systolic dysfunction and non-ischaemic cardiomyopathy remains controversial. We conducted a systematic review and meta-analysis to determine the effect of ICD in patients with non-ischaemic cardiomyopathy on (1) all-cause mortality, (2) cardiovascular mortality and (3) sudden cardiac death. Methods We searched citations in meta-analyses published until 2012, and in MEDLINE, Embase, PubMed and Cochrane databases from 2012 to October 2016. We included randomised controlled trials (RCTs) evaluating the effect of ICD therapy on all-cause and cardiovascular mortality and sudden cardiac death in patients with non-ischaemic cardiomyopathy. Independent reviewers evaluated study eligibility, abstracted data and assessed risk of bias in duplicate. We used random-effect models to meta-analyse relative risks (RR) and hazard ratios (HR) across studies, the Grades of Recommendation, Assessment, Development, and Evaluation system to quantify absolute effects and quality of evidence, and I 2 to evaluate heterogeneity. Results We identified six RCTs including 1715 patients experiencing 421 deaths. ICD therapy was associated with reduced overall mortality (HR 0.78, 95% CI 0.66 to 0.92, I 2 = 0%, risk difference 4.7%, high quality), cardiovascular mortality (RR 0.77, 95% CI 0.60 to 0.98, I 2 = 39%, risk difference 3.3%, high quality) and sudden cardiac death (RR 0.45, 95% CI 0.29 to 0.70, I 2 = 0%, risk difference 4.1%, high quality). The benefit of ICD was not influenced by the use of amiodarone in the comparison group, the duration of follow-up, by use of β-blockers and ACE inhibitors/angiotensin receptor blocker or cardiac resynchronisation therapy. Conclusion Primary prevention ICD therapy reduces all-cause and cardiovascular mortality and sudden cardiac death in patients with non-ischaemic cardiomyopathy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".