Sex differences in implantable cardioverter-defibrillator implantation indications and outcomes: lessons from the Nationwide Israeli-ICD Registry
Bibliographic record
Abstract
AIMS: Implantable cardioverter-defibrillators (ICDs) improve survival in certain high arrhythmic risk populations. However, there are sex differences regarding both the utilization and the benefit of these devices. Using a prospective national ICD registry, we aim to compare the indications for ICD implantation as well as outcomes in implanted women vs. men. METHODS AND RESULTS: All subjects implanted with an ICD or cardiac resynchronization therapy with a defibrillator (CRTD) in Israel between July 2010 and February 2013 were included. A total of 3544 subjects constructed the baseline cohort, of whom 615 (17%) were women. Women had the same age (64 years) and rate of secondary prevention indication (26%) as men. However, women were more likely than men to have significant heart failure symptoms (52 vs. 45%), QRS > 120 ms (41 vs. 36%), and a higher rate of non-ischaemic cardiomyopathy (54 vs. 21%, all P values <0.05). Using multivariate analysis, women were more likely to undergo CRTD implantation (odds ratio = 1.8, P < 0.01). Follow-up data were available for 1518 subjects with a mean follow-up of 12 months. During follow-up, there were no significant differences among genders in the rate of any single or the combined outcomes of appropriate device therapies, heart failure admissions, or death. First-year re-intervention rate was double among women (5.6 vs. 3.0%, P < 0.01). CONCLUSION: In real-world setting, women implanted with an ICD differ significantly from men in their baseline characteristics and in the use of CRTD devices. These, however, did not translate into outcome differences.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".