Acute outcomes for the full US cohort of the FLASH mechanical thrombectomy registry in pulmonary embolism 
Bibliographic record
Abstract
BACKGROUND: Evidence supporting interventional pulmonary embolism (PE) treatment is needed. AIMS: We aimed to evaluate the acute safety and effectiveness of mechanical thrombectomy for intermediate- and high-risk PE in a large real-world population. METHODS: FLASH is a multicentre, prospective registry enrolling up to 1,000 US and European PE patients treated with mechanical thrombectomy using the FlowTriever System. The primary safety endpoint is a major adverse event composite including device-related death and major bleeding at 48 hours, and intraprocedural adverse events. Acute mortality and 48-hour outcomes are reported. Multivariate regression analysed characteristics associated with pulmonary artery pressure and dyspnoea improvement. RESULTS: mean increase in cardiac index (18.9%; p<0.0001) in patients with depressed baseline values. Most patients (62.6%) had no overnight intensive care unit stay post-procedure. At 48 hours, the echocardiographic right ventricle/left ventricle ratio decreased from 1.23±0.36 to 0.98±0.31 (p<0.0001 for paired values) and patients with severe dyspnoea decreased from 66.5% to 15.6% (p<0.0001). Conclusions: Mechanical thrombectomy with the FlowTriever System demonstrates a favourable safety profile, improvements in haemodynamics and functional outcomes, and low 30-day mortality for intermediate- and high-risk PE.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".