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Record W4403755333 · doi:10.1161/svin.124.001421

Predictors and Outcomes of Excellent Recanalization Versus Successful Recanalization After Thrombectomy in Proximal and Distal Medium Vessel Occlusion Strokes: A Multinational Study

2024· article· en· W4403755333 on OpenAlexaff
Vivek Yedavalli, Hamza Salim, Basel Musmar, Nimer Adeeb, Kareem El Naamani, Nils Henninger, Sri Hari Sundararajan, Anna Luisa Kühn, Jane Khalife, Sherief Ghozy, Luca Scarcia, Benjamin Yong‐Qiang Tan, Jeremy J. Heit, Robert W. Regenhardt, Nicole M Cancelliere, Joshua D. Bernstock, Aymeric Rouchaud, Jens Fiehler, Sunil A. Sheth, Muhammed Amir Essibayi, Ajit S. Puri, Christian Dyzmann, Marco Colasurdo, Xavier Barreau, Leonardo Renieri, João Pedro Filipe, Pablo Harker, Răzvan Alexandru Radu, Mohamad Abdalkader, Piers Klein, Thomas R. Marotta, Julian Spears, Takahiro Ota, Ashkan Mowla, Pascal Jabbour, Arundhati Biswas, Frédéric Clarençon, James E. Siegler, Thanh N. Nguyen, Ricardo Varela, Amanda Baker, David Altschul, Nestor R. Gonzalez, Markus Möhlenbruch, Vincent Costalat, Benjamin Gory, Christian Paul Stracke, Mohammad Ali Aziz‐Sultan, Constantin Hecker, Hamza Shaikh, David S. Liebeskind, Alessandro Pedicelli, Andrea Alexandre, Illario Tancredi, Tobias D. Faizy, Erwah Kalsoum, Boris Lubicz, Aman B. Patel, Vítor Mendes Pereira, Adrien Guenego, Adam A. Dmytriw

Bibliographic record

VenueStroke Vascular and Interventional Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineOcclusionSurgeryCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Background Acute ischemic stroke arising from medium vessel occlusions (MeVO) poses substantial challenges in treatment and management. This study aims to elucidate the outcomes and factors contributing to achieving excellent recanalization (modified Thrombolysis in Cerebral Infarction [mTICI] 2c–3) versus successful recanalization (mTICI 2b) in patients with MeVO stroke undergoing mechanical thrombectomy (MT). Methods We conducted a multinational study analyzing data from the MAD‐MT (Multicenter Analysis of Distal Medium Vessel Occlusions: Effect of Mechanical Thrombectomy) registry, encompassing 37 centers across North America, Asia, and Europe, collected between September 2017 and July 2023. The study included acute ischemic stroke patients with MeVO treated with MT, with or without intravenous thrombolysis, who achieved mTICI 2b–3 post‐MT. Results Among 1463 patients with successful recanalization (mTICI 2b–3), 523 achieved mTICI 2b recanalization, and 940 achieved mTICI 2c–3. Distal occlusions exhibited higher odds of excellent recanalization compared with proximal MeVO vessel occlusions (odds ratio, 1.58; 95% CI, 1.17–2.15; P = 0.003). Cardioembolic stroke pathogenesis was associated with a higher likelihood of excellent recanalization (1.67; 95% CI, 1.07–2.59; P = 0.018). Patients achieving mTICI 2c–3 recanalization demonstrated lower initial National Institutes of Health Stroke Scale scores, significant improvements in postprocedural National Institutes of Health Stroke Scale shift, and a higher percentage of favorable 90‐day outcomes compared with those with mTICI 2b. However, no significant difference in 90‐day mortality rates was observed. Conclusion This study underscores that among patients with MeVO stroke with successful recanalization (mTICI 2b–3) there is higher likelihood of achieving excellent recanalization (mTICI 2c–3) in distal occlusions and cardioembolic pathogenesis. mTICI 2c–3 scores post‐MT correlate with improved clinical outcomes compared with mTICI 2b, affirming the superiority of excellent recanalization over successful recanalization in patients with MeVO stroke. Further prospective studies and randomized controlled trials are warranted for validation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.276
Teacher spread0.267 · 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 teacher head, 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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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