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Iterating the ASPECTS <6 threshold

2017· letter· en· W2778503239 on OpenAlexaboutno aff
J Mocco, Michael Chen

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2017
Typeletter
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Clinical trialAcute strokeClinical PracticeEmergency medicinePhysical therapyInternal medicineTissue plasminogen activator

Abstract

fetched live from OpenAlex

In response to the publication of the five positive stroke thrombectomy trials, the American Heart Association issued a focused update in 2015 of its guidelines for early management of patients with acute ischemic stroke, including the uncertainty of benefit of thrombectomy in patients with an Alberta Stroke Program Early CT Score (ASPECTS) <6 (level IIb), recommending further clinical trials.1 Investigators in many of these studies were trained to dichotomize ASPECTS scoring during enrollment. Doing so not only yielded higher interobserver agreement, particularly when a threshold of 7 was used, but also simplified and expedited enrollment.2 This may have inadvertently led to a more widespread trend in dichotomizing ASPECTS in clinical practice, with the presence or absence of evidence as justification. In this month’s issue of JNIS , Mourand et al 3 challenge the ASPECTS <6 threshold by reporting their single center results of 60 stroke thrombectomy patients treated from 2009 to 2014 presenting with ASPECTS ≤5. Their results suggest that there may still be efficacy and safety with stroke thrombectomy in the presence of large core infarcts. Median admission National Institutes of Stroke Scale (NIHSS) score was 20 and median age was 66 years. Most patients were …

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.161
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.054
GPT teacher head0.298
Teacher spread0.244 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2017
Admission routes1
Has abstractyes

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