The transseptal puncture experience: Safety insights from FDA MAUDE database
Bibliographic record
Abstract
BACKGROUND: There is a paucity of literature on safety and efficacy of various transseptal puncture (TSP) needles. OBJECTIVES: To assess the reported mechanisms of failure, complications, and outcomes among the most frequently used transseptal needles in the United States. METHODS: We queried the Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database between January 2011 and January 2021 for reports on the most commonly used transseptal needles: NRG (Baylis Medical, Montreal, Canada), and BRK (St. Jude, Saint Paul, MN)]. The primary outcome was the mechanism of failure. Secondary outcomes included clinical consequences of device failure. RESULTS: The final analysis included 306 reports of failure/complication with TSP needles (NRG n = 70, BRK n = 236). The most commonly reported mode of failure was detachment of the needle component (i.e., clip, hub, stopcock, shaft, spring, or needle tip) (14.7% overall; 17.8% BRK; and 4.3% NRG). Among these reports, cardiac perforation was the most common complication (69.9% overall; 69.1% for BRK; and 72.9% for NRG). Pericardiocentesis was the second most commonly reported complication (45.1% overall; 48.3% for BRK; and 34.3% for NRG). The procedure was successfully completed in 33.3% of all cases (36.4% for BRK and 22.9% for NRG), while surgical conversion was needed in (13.4% overall; 14% for BRK and 11.4% for NRG) of the reports. Death occurred in 3.9% of all cases overall (3.4% for BRK and 5.7% for NRG). CONCLUSIONS: Needle detachment was the most common mode of failure, and cardiac perforation was the most common complication reported with TSP needles. Future efforts should focus on innovative TSP needle design, best practice guidelines, including role of imaging guidance, and increased TSP training.
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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 | 0.009 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".