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Record W4387161479 · doi:10.1212/wnl.0000000000207869

Endovascular Thrombectomy in Patients With Very Low ASPECTS Scores

2023· review· en· W4387161479 on OpenAlexafffundabout
Aristeidis H. Katsanos, Luciana Catanese, Ashkan Shoamanesh

Bibliographic record

VenueNeurology · 2023
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsMedicineModified Rankin ScaleRandomized controlled trialOdds ratioStroke (engine)Meta-analysisInternal medicineOddsIschemic strokeLogistic regression

Abstract

fetched live from OpenAlex

OBJECTIVES: Randomized controlled trials (RCTs) have recently established the benefit of endovascular thrombectomy (EVT) in patients with large infarct core on baseline neuroimaging. We evaluated the utility of EVT in patients with very large infarct core, defined as Alberta Stroke Program Early CT scores (ASPECTS) of less than 3. METHODS: We performed a systematic review and meta-analysis of the subgroups of patients with baseline ASPECTS scores 0-2 included in RCTs evaluating the utility of EVT in the setting of a large infarct core. The outcome of interest was the probability of three-month functional improvement assessed with the generalized odds ratios (ORs) of the modified Rankin Scale (mRS) scores between patients receiving EVT and medical management. RESULTS: = 0.73). DISCUSSION: The results from our pooled analysis challenge the exclusion of patients presenting with ASPECTS scores less than 3 from receiving EVT if they are otherwise eligible.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.275
Teacher spread0.253 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations20
Published2023
Admission routes3
Has abstractyes

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