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Record W4413340893 · doi:10.1101/2025.08.06.25333179

First Line Thrombectomy Devices in Intracranial Atherosclerotic Disease: An analysis of the RESCUE-ICAS registry

2025· preprint· en· W4413340893 on OpenAlexaff
A Mierzwa, Ahmad Abu Qdais, Imad Samman Tahhan, Shadi Yaghi, Violiza Inoa, Francesco Capasso, Michael Nahhas, Robert M. Starke, Isabel Fragata, Matthew T. Bender, Krisztina Moldovan, Ilko Maier, Jonathan A Grossberg, Pascal Jabbour, Marios‐Nikos Psychogios, Edgar A. Samaniego, Jan-Karl Burkhardt, Brian T. Jankowitz, Mohamad Abdalkader, David Altschul, Justin Mascitelli, Robert W. Regenhardt, Stacey Q Wolfe, Mohamad Ezzeldin, Kaustubh Limaye, Hosam Al-Jehani, Nitin Goyal, Stavropoula Tjoumakaris, Ali Alawieh, Mohammed Almekhlafi, Eytan Raz, Syed Zaidi, Alejandro M Spiotta, Kimberly Kicielinski, Jonathan Lena, Zachary Hubbard, Osama O. Zaidat, Colin P. Derdeyn, Ramesh Grandhi, Eyad Almallouhi, Mohammad Anadani, Adam de Havenon, Thanh N. Nguyen, Ameer E Hassan, Mouhammad Jumaa, Sami Al Kasab

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineRescue therapyCardiologyInternal medicineEmergency medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Managing atherosclerotic large vessel occlusion is procedurally challenging. Prior literature pertaining to technical considerations remain heterogenous and further research is necessary to highlight important differences. As such, first-line thrombectomy technique remains an active area of debate with respect to rate of recanalization, need for rescue stenting, and hemorrhagic complications. Methods This is a pre-planned analysis of the prospective RESCUE-ICAS registry which included atherosclerotic large vessel occlusions treated with mechanical thrombectomy from 25 sites. Patients were excluded if they had missing data on first-line technique or primary outcomes. Patients were dichotomized into two cohorts based on whether their first-line thrombectomy technique was with aspiration alone or a stentriever (SR). Primary procedural outcome was first-pass effect while primary safety outcome was mortality at 90 days. Propensity score matching and inverse probability weighted analysis were performed with respect to primary and secondary outcomes. Results 419 were patients included in this analysis with 266 and 153 patients in the aspiration and stentriever cohorts, respectively. The cohort’s mean age was 68 (SD ±13) years, and the majority of patients were white (59%) and male (62%). There were no significant baseline demographic differences between cohorts; however, ICA occlusions were more common in the stentriever cohort (52% vs 31%), while MCA occlusions were more frequent in the aspiration cohort (35% vs 15%). In the un-adjusted model, first pass effect was higher in stentriever versus aspiration (35.3% vs 23.7%, p = 0.01) with equivalent mortality rates (31% vs 26%, p = 0.31). Distal embolization rates were higher in the aspiration cohort (9.8% vs 3.9%, p = 0.03), yet aspiration was associated with lower composited procedural complications (6% vs 11%, p = 0.01). Propensity score matching and weighted analysis demonstrated that differences in primary clinical efficacy and safety outcomes were insignificant between cohorts. Conclusion In patients with atherosclerotic large vessel occlusions, first line stentriever utilization was associated with higher first-pass effect rates, lower rates of distal embolization and shorter procedural length compared to aspiration. However, no clinical outcome difference was appreciated between the two groups and aspiration was associated with lower complication rates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.301
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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