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Record W7118517282 · doi:10.1097/wco.0000000000001449

Endovascular treatment of distal medium vessel occlusions

2025· article· en· W7118517282 on OpenAlexaff
Antonio Ciacciarelli, Umberto Pensato, Johanna M. Ospel

Bibliographic record

VenueCurrent Opinion in Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEndovascular treatmentMedium termClinical trialContrast mediumMEDLINE

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Endovascular treatment (EVT) has dramatically improved outcomes of patients suffering from acute ischemic stroke due to large vessel occlusion (LVO), becoming the standard of care. However, up to one-third of ischemic strokes are caused by distal medium vessel occlusions (DMVO), which are beyond the LVO territory. Medical management, including intravenous thrombolysis, leaves more than half of DMVO patients disabled at 3 months, with mortality exceeding 10%. In face of this grim prognosis, expanding EVT to DMVO has gained considerable interest. This review summarizes the clinical, anatomical, and imaging features of DMVO stroke, discusses recent EVT trial results and their interpretation, and outlines future directions for establishing safe and effective reperfusion strategies in this population. RECENT FINDINGS: Recent randomized trials investigating EVT for DMVO stroke yielded neutral results overall. However, they provided important insights about patient subgroups likely to benefit from intervention and set key challenges to improving the management of patients with DMVO. SUMMARY: While current evidence does not support routine EVT for DMVO stroke, the field is evolving rapidly. Ongoing advances in device technology, patient selection, and trial design hold promise for refining treatment and improving outcomes in carefully selected patients.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score0.498

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 head0.031
GPT teacher head0.337
Teacher spread0.306 · 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 designNot applicable
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

Citations2
Published2025
Admission routes1
Has abstractyes

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