Finding the optimal access for proximal upper limb artery (PULA) interventions: Lessons learned from the <scp>PULA</scp> multicenter registry
Bibliographic record
Abstract
OBJECTIVE: The multicenter proximal upper limb artery (PULA) Registry was created to study the optimal puncture sites for the interventions involving the subclavian, axillary, and innominate arteries. BACKGROUND: Little is known about the optimal vascular access for PULA interventions, despite the well-known technical complexity of these procedures. METHODS: We performed the retrospective analysis of consecutive patients treated for symptomatic steno-occlusive disease of the proximal upper limb arteries between January 2015 and December 2019 in three high-volume centers. Acute thrombotic occlusions were excluded from the study. RESULTS: Two hundred and seventy-two patients were treated for significant stenosis and 108 for total occlusion. The baseline patient's characteristics were similar, except for the higher median age of the stenotic patients: 68.5 years (31.1; 90.0) versus 64 years (38.0; 86.0) p = 0.0015. Successful revascularization rate was higher in the stenotic group 93.75% (255/272) versus 86.11% (93/108) p = 0.0230, while the procedure length 27 min (8; 133) versus 46 min (7; 140) p = 0.0001 and fluoroscopy times 439 s (92; 2993) versus 864 s (86; 4176) p = 0.0001 were higher in the occlusion group. The main adverse event rate was similarly low. Dual access was used more often to treat occlusions (60.19% (65/108) vs. 11.40% (31/272) p = 0.0001) without significantly increasing the complication rate. The safest access was ultrasound-guided distal radial artery puncture, significantly better than conventional radial access with 0% (0/31) versus 13.6% (18/131) p = 0.0253 complication. CONCLUSIONS: The percutaneous revascularization of proximal upper limb arteries is a safe and effective. Dual access can be applied to increase treatment efficacy, without significantly compromising safety.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".