The effect of revascularization on mortality and risk of ventricular arrhythmia in patients with ischemic cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: There is clear evidence that patients with prior myocardial infarction and a reduced ejection fraction benefit from implantation of a cardioverter-defibrillator (ICD). It is unclear whether this benefit is altered by whether or not revascularization is performed prior to ICD implantation. METHODS: This was a retrospective cohort study following patients who underwent ICD implantation from 2002 to 2014. Patients with ischemic cardiomyopathy and either primary or secondary prevention ICDs were selected for inclusion. Using the electronic medical record, cardiac catheterization data, revascularization status (percutaneous coronary intervention or coronary bypass surgery) were recorded. The outcomes were mortality and ventricular arrhythmia. RESULTS: There were 606 patients included in the analysis. The mean age was 66.3 ± 10.1 years, 11.9% were women, and the mean LVEF was 30.5 ± 12.0, 58.9% had a primary indication for ICD, 82.0% of the cohort had undergone coronary catheterization prior to ICD implantation. In the overall cohort, there were fewer mortality and ventricular arrhythmia events in patients who had undergone prior revascularization. In patients who had an ICD for secondary prevention, revascularization was associated with a decrease in mortality (HR 0.46, 95% CI (0.24, 0.85) p = 0.015), and a trend towards fewer ventricular arrhythmia (HR 0.62, 95% CI (0.38, 1.00) p = 0.051). There was no association between death or ventricular arrhythmia with revascularization in patients with primary prevention ICDs. CONCLUSION: Revascularization may be beneficial in preventing recurrent ventricular arrhythmia, and should be considered as adjunctive therapy to ICD implantation to improve cardiovascular outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".