Effectiveness of single‐ vs dual‐coil implantable defibrillator leads: An observational analysis from the SIMPLE study
Bibliographic record
Abstract
INTRODUCTION: Dual-coil leads (DC-leads) were the standard of choice since the first nonthoracotomy implantable cardioverter/defibrillator (ICD). We used contemporary data to determine if DC-leads offer any advantage over single-coil leads (SC-leads), in terms of defibrillation efficacy, safety, clinical outcome, and complication rates. METHODS AND RESULTS: In the Shockless IMPLant Evaluation study, 2500 patients received a first implanted ICD and were randomized to implantation with or without defibrillation testing. Two thousand and four hundred seventy-five patients received SC-coil or DC-coil leads (SC-leads in 1025/2475 patients; 41.4%). In patients who underwent defibrillation testing (n = 1204), patients with both lead types were equally likely to achieve an adequate defibrillation safety margin (88.8% vs 91.2%; P = 0.16). There was no overall effect of lead type on the primary study endpoint of "failed appropriate shock or arrhythmic death" (adjusted HR 1.18; 95% CI, 0.86-1.62; P = 0.300), and on all-cause mortality (SC-leads: 5.34%/year; DC-leads: 5.48%/year; adjusted HR 1.16; 95% CI, 0.94-1.43; P = 0.168). However, among patients without prior heart failure (HF), and SC-leads had a significantly higher risk of failed appropriate shock or arrhythmic death (adjusted HR 7.02; 95% CI, 2.41-20.5). There were no differences in complication rates. CONCLUSION: In this nonrandomized evaluation, there was no overall difference in defibrillation efficacy, safety, outcome, and complication rates between SC-leads and DC-leads. However, DC-leads were associated with a reduction in the composite of failed appropriate shock or arrhythmic death in the subgroup of non-HF patients. Considering riskier future lead extraction with DC-leads, SC-leads appears to be preferable in the majority of patients.
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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".