MétaCan
Menu
Back to cohort

Agreement between core laboratory and study investigators for imaging scores in a thrombectomy trial

2018· article· en· W2803158721 on OpenAlexaboutno aff
Robert Fahed, Malek Ben Maacha, Célina Ducroux, Naïm Khoury, Raphaël Blanc, Michel Piotin, Bertrand Lapergue

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCore (optical fiber)Stroke (engine)Medical physicsRadiologyNuclear medicine

Abstract

fetched live from OpenAlex

PURPOSE: We aimed to assess the agreement between study investigators and the core laboratory (core lab) of a thrombectomy trial for imaging scores. METHODS: The Alberta Stroke Program Early CT Score (ASPECTS), the European Collaborative Acute Stroke Study (ECASS) hemorrhagic transformation (HT) classification, and the Thrombolysis In Cerebral Infarction (TICI) scores as recorded by study investigators were compared with the core lab scores in order to assess interrater agreement, using Cohen's unweighted and weighted kappa statistics. RESULTS: There were frequent discrepancies between study sites and core lab for all the scores. Agreement for ASPECTS and ECASS HT classification was less than substantial, with disagreement occurring in more than one-third of cases. Agreement was higher on MRI-based scores than on CT, and was improved after dichotomization on both CT and MRI. Agreement for TICI scores was moderate (with disagreement occurring in more than 25% of patients), and went above the substantial level (less than 10% disagreement) after dichotomization (TICI 0/1/2a vs 2b/3). CONCLUSION: Discrepancies between scores assessed by the imaging core lab and those reported by study sites occurred in a significant proportion of patients. Disagreement in the assessment of ASPECTS and day 1 HT scores was more frequent on CT than on MRI. The agreement for the dichotomized TICI score (the trial's primary outcome) was substantial, with less than 10% of disagreement between study sites and core lab. TRIAL REGISTRATION NUMBER: NCT02523261, Post-results.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.078
GPT teacher head0.346
Teacher spread0.268 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of NeuroInterventional SurgerySame topicAcute Ischemic Stroke ManagementFrench-language works237,207