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Record W4400893641 · doi:10.1136/jnis-2024-snis.23

O-023 Perseverance past TICI 2B thrombectomy: studying the risk-to-benefit ratio as function of procedure time

2024· article· en· W4400893641 on OpenAlexaboutno aff
B El Baba, Youssef M. Zohdy, R Chalhoub, Bryan Howard, C Cawley, Feras Akbik, David L. Barrow, A Pabaney, Frank Tong, S Alkasab, P Jabbour, Nitin Goyal, A Arthur, Fazeel Siddiqui, Shinkichi YOSHIMURA, M. Park, W Brinjikji, C Maatouk, Daniele Romano, David Altschul, R Williamson, M. Moss, R De Leacy, Mohamad Ezzeldin, Peter Kan, Michael D. Levitt, R Grandhi, A Spiotta, J Mascitelli, J Grossberg, A Alawieh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsFunction (biology)Computer scienceMedicineBiology

Abstract

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Introduction In patients undergoing endovascular thrombectomy (EVT) for acute ischemic stroke, higher recanalization scores using the Thrombolysis In Cerebral Ischemia (TICI) score were demonstrated to predict EVT outcomes. Successful recanalization is commonly used to report TICI 2B score or higher corresponding to recanalization of at least 50% of the target territory. In this work, we study the risk-benefits associated with continued attempt to achieve higher TICI score beyond TICI 2B as function of procedure time. Methods This is a retrospective registry-based study of patients undergoing EVT for AIS at 30 centers internationally. Patients were reviewed for their demographics, admission deficits, and technical outcomes. The cohort was split into 4 groups: (1) patients with TICI 2B recanalization without attempts to enhance score, (2) patients with TICI 2B recanalization for whom additional attempts were made for higher score, and (3) patients with TICI 0–2A. Primary outcome is modified Rankin Score (mRS) at 90 days, secondary outcomes included improvement in post-procedural National Institute of Health Stroke Scale (NIHSS), final TICI score, and symptomatic intracranial hemorrhage (sICH). Successful recanalization was defined as TICI-2B or more, and complete recanalization was defined as TICI-3. Logistic regression models were used to study outcome predictors while controlling for admission and technical covariates using step-wise backpropagation to avoid bias in variable selection. Adjusted odds ratios (aOR) were reported. Results A total of 3071 patients were included in this study with mean age of 68, 48% females, and 89% rate of successful recanalization. We first compared groups (1) and (2) using logistic regression models, patients with additional attempts to improve TICI 2B score (Group 2) were associated with higher odds of achieving TICI 3 (aOR=6.8,p<0.001), but had significantly lower odds of good outcome (mRS 0–2) (aOR=0.73,p<0.001) without impact on rates of sICH. When comparing patients in group (2) to patients without successful recanalization (group 3), continued EVT past TICI-2B did not result in higher odds of good outcome compared to those with TICI1–2A (aOR=1.17,p=0.41). Using sensitivity analysis, we demonstrate that in patients who achieve TICI-2B within 15 min of puncture, additional attempts at improving the score was associated with higher odds of TICI-3 (aOR=35,p<0.01) without negative influence on functional outcome.(aOR=0.96,p=0.89). However, in patients where initial TICI-2B score was attained after 15 min of puncture, further attempts are associated with higher odds of TICI-3 (aOR=6.8,p<0.01) but with significantly lower odds of good outcome (aOR=67,p=0.015). Finally, longer time to conclude EVT procedure after TICI-2B was independently associated with lower odds of good outcome (aOR=0.88,p=0.021). Conclusions In patients with successful recanalization who achieved below perfect reperfusion scores, additional recanalization trials carry the cost of worsening outcomes specifically in patients whose initial recanalization required more than 15 min. Future prospective studies are needed to study whether achieving the point of trade-off between achieving perfect recanalization scores and patient outcomes. Disclosures B. El Baba: None. Y. Zohdy: None. R. Chalhoub: None. B. Howard: None. C. Cawley: None. F. Akbik: None. D. Barrow: None. A. Pabaney: None. F. Tong: None. S. Alkasab: 1; C; Stryker. P. Jabbour: 2; C; Balt, Cerus endovascular, MicroVention, Medtronic. N. Goyal: None. A. Arthur: 1; C; Balt, Medtronic, Microvention, Penumbra, Siemens. 2; C; Arsenal, Balt, Johnson and Johnson, Medtronic, Microvention, Penumbra, Scientia, Siemens, Stryker. 4; C; Azimuth, Bendit, Cerebrotech, Endostream, Magneto, Mentice, Neurogami, Neuros, Scientia, Serenity, Synchron, Tulavi, Vastrax, VizAI. F. Siddiqui: None. S. Yoshimura: None. M. Park: 5; C; Medtronic. W. Brinjikji: None. C. Maatouk: 2; C; Silk Road, Penumbra, Microvention, Stryker. 3; C; Silk Road, Penumbra. D. Romano: None. D. Altschul: None. R. Williamson: None. M. Moss: None. R. De Leacy: 1; C; Hyprevention, Kaneka Medical, Siemens Healthineers, SNIS foundation. 2; C; Stryker Neurovascular, Imperative Care, Cerenovus, Asahi Intec. 4; C; Synchron, Endostream, Q’Apel, Spartan Micro. 6; C; Editorial Board JNIS. M. Ezzeldin: None. P. Kan: 1; C; U18EB029353–01. 2; C; Stryker Neurovascular, Imperative Care, Microvention. 6; C; Editorial Board JNIS. M. Levitt: 1; C; Stryker, Medtronic. 2; C; Medtronic, Aeaean Advisers. 4; C; Hyperion Surgical, Proprio, Synchron, Cerebrotech, Fluid Biomed, Stereotaxis. 6; C; Travel support: Penumbra, Editorial board, Journal of NeuroInterventional Surgery, Metis Innovative: Adviser. R. Grandhi: None. A. Spiotta: 2; C; Stryker, Terumo, Penumbra, RapidAI. J. Mascitelli: 2; C; Stryker. J. Grossberg: 1; C; Georgia Research Alliance, Emory Medical Care Foundation, Department of Defense, Neurosurgery Catalyst. 4; C; NTI, Cognition. A. Alawieh: 6; C; Penumbra.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.079
GPT teacher head0.441
Teacher spread0.361 · 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
Published2024
Admission routes1
Has abstractyes

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