MétaCan
Menu
Back to cohort
Record W4400892661 · doi:10.1136/jnis-2024-snis.393

E-288 Do physicians intuitively select slow progressors for thrombectomy in the extended time window?

2024· article· en· W4400892661 on OpenAlexaffabout
Salome Bosshart, A Stebner, Charlotte Zerna, Emma Harrison, Timothy Kleinig, Volker Pütz, Daniel Kaiser, Brett Graham, Aixi Yu, Brian van Adel, Jai Shankar, Ryan McTaggart, Vítor Mendes Pereira, Don Frei, Mayank Goyal, Marcelo Hill, Johanna M. Ospel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsSt. Michael's HospitalFoothills Medical CentreUniversity of ManitobaMcMaster UniversitySunnybrook Health Science CentreUniversity of CalgaryHamilton General HospitalRoyal University Hospital
Fundersnot available
KeywordsWindow (computing)Computer scienceTherapeutic windowMedicineOperating system

Abstract

fetched live from OpenAlex

Background In acute ischemic stroke, infarction progresses over time. Accordingly, in patients presenting within 6 hours from last-known-well, longer average time from symptom onset to endovascular treatment (EVT) is associated with worse clinical outcome. However, recent data on late window EVT suggests that outcomes can be equally good. We investigated the association of clinical outcome with a) time from last-known-well to arrival at the EVT-hospital and b) time from hospital arrival to arterial access for anterior circulation large vessel occlusion patients treated >6hours from last-known-well. Methods Retrospective analysis of the prospective, multicenter cohort study ESCAPE-LATE. Patients presenting >6 hours after last-known-well with anterior circulation large vessel occlusion undergoing EVT were included. The primary outcome was the clinical outcome on the modified Rankin Scale (mRS). Secondary outcomes were good (mRS 0–2) and poor clinical outcome (mRS 5–6) at 90 days, as well as the National Institutes of Health Stroke Scale (NIHSS) at 24 hours after EVT. Associations of time intervals with outcomes were assessed with univariable and multivariable logistic regression. Results Two-hundred patients were included in the analysis, of whom 85(43%) were female. 90-day mRS was available for 135 patients. Hundred-thirty-five of 150 patients (90%) had moderate-to-good collateral status and the median Alberta Stroke Program Early CT Score (ASPECTS) was 8 (IQR=7–10). No association between ordinal mRS and time from last-known-well to arrival at the EVT-hospital (OR=1.01, 95%CI=1.00–1.02) or time from hospital arrival to arterial access (OR=-0.01, 95%CI=-0.02–0.00) was seen in unadjusted and adjusted regression models. Conclusion No relationship was observed between pre-hospital or in-hospital workflow times and clinical outcomes. Baseline ASPECTS and collateral status were favorable in a large majority of patients, suggesting that physicians may have chosen to predominantly treat slow progressors in the late time window, in whom prolonged workflow times have less impact on outcomes. Disclosures S. Bosshart: None. A. Stebner: None. C. Zerna: None. E. Harrison: None. T. Kleinig: None. V. Pütz: None. D. Kaiser: None. B. Graham: None. A. Yu: None. B. van Adel: None. J. Shankar: None. R. McTaggart: None. V. Pereira: None. D. Frei: None. M. Goyal: 1; C; Medtronic. M. Hill: 1; C; Medtronic. J. Ospel: None.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0190.004

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 head0.112
GPT teacher head0.476
Teacher spread0.363 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same topicClinical practice guidelines implementationFrench-language works237,207