A cost‐effectiveness analysis comparing a conventional mechanical needle to a radiofrequency device for transseptal punctures
Bibliographic record
Abstract
INTRODUCTION: Transseptal puncture is an integral step in various catheter-based cardiac procedures and can be performed with either the conventional mechanical needle or an FDA-cleared device utilizing radiofrequency (RF) energy. Although a previous randomized trial suggested that the RF transseptal device may be faster and more often successful, the increased equipment costs may dissuade operators from routine use. This analysis compares the cost-effectiveness of the mechanical needle to the RF device during pulmonary vein isolation. METHODS: The rates of successful transseptal punctures for each device and transseptal-related complications were determined from the peer-reviewed medical literature. Procedural, equipment, and complication costs were obtained from peer-reviewed medical literature and the Healthcare Cost and Utilization Project. The effectiveness was defined as the probability of 30-day survival following a successful transseptal puncture. Monte Carlo probabilistic analyses tested variable effects of costs and complication rates on the incremental cost-effectiveness ratio. RESULTS: The 30-day effectiveness of the RF device vs the mechanical needle was 99.7% and 98.8%, respectively. After accounting for all costs of performing a single transseptal puncture, the cost at 30 days associated with the RF device was $41 less than the mechanical needle ($21 096 vs $21 137). The RF device was similarly dominant to the mechanical needle in double transseptal puncture scenarios. Finally, the RF device was more cost-effective than the mechanical needle at any willingness-to-pay in Monte Carlo probabilistic sensitivity analyses. CONCLUSIONS: Despite greater equipment costs, the RF device costs less and provides better effectiveness at 30 days than the conventional mechanical needle.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".