Mechanical thrombectomy with a balloon-guide catheter: sheathless transradial versus transfemoral approach
Bibliographic record
Abstract
BACKGROUND: The transradial approach (TRA) for mechanical thrombectomy (MT) for acute ischemic stroke has been limited by the size of catheters usable in the radial artery, with the smaller access site precluding balloon-guide catheter (BGC) use. However, promising results have been reported for a TRA with a sheathless BGC (sTRA). We sought to perform a comparative study of MT with a BGC via the sTRA versus the transfemoral approach (TFA). METHODS: A retrospective review of our MT database was conducted. Baseline, procedure-related, and outcome data were compared for patients aged ≥18 years with anterior circulation large vessel occlusion, Alberta Stroke Program Early CT Score ≥6, and prestroke modified Rankin Scale score ≤2 treated with either approach. RESULTS: Ninety-three consecutive patients (34 sTRA and 59 TFA) were included. Both groups had similar demographics, comorbidities, stroke severity, intravenous alteplase use, and occlusion location. Mean time from puncture to final recanalization was faster in the sTRA group (29 vs 36 min, p=0.059) despite a higher access site crossover rate in the sTRA group (11.8% vs 0%, p=0.016). There were no differences between groups regarding last modified Thombolysis in Cerebral Infarction score; first-pass or modified first-pass effect; time from last known well to puncture; use of stent-retriever, aspiration, or combination first approach; number of passes; symptomatic intracranial hemorrhage; hospital stay; 90-day functional independence; and mortality. National Institutes of Health Scale score and modified first-pass effect were the only independent predictors of poor outcomes. CONCLUSIONS: Comparable patients treated with MT via the sTRA or TFA had similar angiographic and clinical outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".