Abstract 17276: Implantable Cardioverter-Defibrillator Therapy in Women: Population-based Outomes
Bibliographic record
Abstract
Background: Due to the low enrolment of women in implantable cardioverter-defibrillator (ICD) trials, there is controversy whether the survival benefit of ICDs applies to both sexes. Population-based data examining sex differences in ICD outcomes may provide further clarification. Methods: Study data were derived from a provincial registry in British Columbia (BC), the Cardiac Services BC Registry, where all ICD recipients are recorded. Patients ≥18 years with a new ICD implant from Jan 2003 to Dec 2012 were included. Data were linked to BC Vital Statistics to determine all-cause mortality. Survival was assessed using Kaplan-Meier methods stratified by sex and compared using the log-rank test. The Cox proportional-hazards model was used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) between sexes. The effect of demographics, comorbidities and medication use were explored and only factors with a p-value < 0.15 were included in the final model. Statistical analyses were performed with SAS software, version 9.3 (Cary, NC). Results: There were 3905 new ICD implants; of these, 704 were women (18%). Women were younger and had a lower prevalence of comorbidities. Except for beta-blockers, women were less likely to be prescribed cardiac medications. The overall survival of women was greater than men; however, women had a higher re-operation rate for complications (Figure). After adjusting for age, diabetes, coronary artery disease, congestive cardiomyopathy, peripheral vascular disease, acquired heart surgery, and anti-arrhythmic drug use, the sex difference in mortality was attenuated, adjusted HR 0.91, (95% CI: 0.75,1.12). Conclusions: Women may derive the same survival benefit as men but have a higher re-operation rate for complications. Ongoing analyses will determine whether the impact of sex on mortality differs among patients receiving an ICD for primary versus secondary prevention.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".