Inequality between women and men in ICD implantation
Bibliographic record
Abstract
Background: The impact of sex on ICD implantation practice and survival remain a topic of controversy. To assess sex-specific differences in ICD implantation practice we compared clinical characteristics and survival in women and men. Methods: From a nationwide registry, all new ICD implantations performed between 01/02/2010 and 31/01/2019 in Belgian patients were analyzed retrospectively. Baseline characteristics and survival rates were compared between sexes. To identify predictors of mortality, multivariable Cox regression was performed. Results: Only 3096 (20.9%) of 14,787 ICD implantations were performed in women. Within each type of underlying cardiomyopathy, the proportion women were lower than men. The main indication in men was ischemic vs dilated cardiomyopathy in women. Women were overall younger (59.1 ± 15.1 vs 62.6 ± 13.1 years; p < 0.001) and had less comorbidities except for oncological disease. More women functioned in NYHA-class III (33.6% vs 27.9%; p < 0.001) and had a QRS > 150 ms (29.4% vs 24.3%; p < 0.001), consistent with a higher use of CRT-D devices (31.7% vs 25.1%; p < 0.001). Women had more complications, reflected by the need to more re-interventions within 1 year (4.3% vs 2.7%, p < 0.001). After correction for covariates, sex-category was not a significant predictor of mortality (p = 0.055). Conclusion: There is a significant sex-disparity in ICD implantation rates, not fully explained by epidemiological differences in the prevalence of cardiomyopathies, which could imply an undertreatment of women. Women differ from men in baseline characteristics at implantation suggesting a selection bias. Further research is necessary to evaluate if women receive equal sudden cardiac death prevention.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".