Association of mortality and use of guideline-direct medical therapy following primary prevention defibrillator implantation
Bibliographic record
Abstract
Abstract Background Primary prevention implantable cardioverter-defibrillators (ICDs) are recommended for patients with heart failure with reduced ejection fraction. Previous studies have shown that a higher number of prescribed guideline-directed medical therapy (GDMT) medications improves survival rates at 2 years post-ICD implantation, though long-term data is lacking. Purpose This study investigated the impact of GDMT, and uniquely, antiarrhythmic medications, on long-term all-cause mortality following primary prevention ICD implantation. Methods A single-center, retrospective study was completed on all patients who received a primary prevention ICD between 2005 and 2024 (N=590). Baseline demographics, Charlson Comorbidity Index (CCI), GDMT (angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, angiotensin receptor/neprilysin inhibitors, beta-blockers, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter-2 inhibitors) and antiarrhythmic medications were recorded at the time of device implantation. The primary outcome was all-cause mortality at >5 years. Cox multivariable models were constructed, adjusting for age, sex, ejection fraction, CCI, number of GDMT, and antiarrhythmic medication use, to evaluate the impact of additional GDMT and antiarrhythmic medications on mortality, independently. Results Among 590 patients (69±12 years; 21% female), 4 (1%), 41 (7%), 223 (38%), 276 (47%), and 46 (8%) were on 0, 1, 2, 3, and 4 GDMT medications, respectively. Mortality rates were 12% (72) within 2 years, 14% (81) between 2–5 years, and 19% (111) >5 years post-implantation. The risk of death at >5 years post implantation decreased from 22% on 0/1 GDMT medication to 0% on 4 GDMT medications (p<0.01). Cox multivariable models indicated that each additional GDMT medication reduced mortality by 26% (HR: 0.74; P<0.001). Conversely, antiarrhythmic use was associated with a 27% increase in mortality (HR: 1.27; P<0.05). Conclusion Increasing GDMT medications is associated with improved long-term survival in patients post-ICD implantation, supporting escalating therapy when feasible. In contrast, antiarrhythmic use is associated with increased all-cause mortality.Figure 1
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".