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Record W4406992577 · doi:10.1161/str.56.suppl_1.wp170

Abstract WP170: Association of Workflow Metrics with Functional Outcomes in the SELECT2 trial

2025· article· en· W4406992577 on OpenAlexaff
Fawaz Al‐Mufti, Ameer E Hassan, Michael Abraham, Shazam Hussain, Santiago Ortega‐Gutiérrez, Michael Chen, Deep Pujara, Hannah Johns, Clark Sitton, Leonid Churilov, Michael D. Hill, Marc Ribó, Bruce Campbell, Chirag D. Gandhi, Stavropoula Tjoumakaris, Amrou Sarraj

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAssociation (psychology)WorkflowStroke (engine)Internal medicine

Abstract

fetched live from OpenAlex

Introduction: Faster reperfusion from initial presentation was associated with improved outcomes after endovascular thrombectomy(EVT) in patients with small core strokes. However, the relationship between time and different workflow metrics with outcomes in not well-established in patients with large strokes. We aimed to analyze the clinical workflow and time measures and their effect on overall procedure and functional outcomes from SELECT2 trial. Methods: Patients enrolled in SELECT2 trial were stratified based on treatment arm and transfer status and various workflow metrics, both in-hospital and outside (limited to transferred patients) were compared and their effect on clinical outcomes were evaluated. Results: Of 352 enrolled, 141 patients (72 EVT, 69 MM) presented directly to EVT-capable centers, whereas 211(106 EVT, 105 MM) were transferred from referral centers. Among patients presenting directly, no difference was observed between time from LKW to arrival(EVT:376.5(119.5-638)min vs MM:435(118-802)min,p=0.50), arrival to imaging acquisition(EVT:14(10-21)min vs MM:16.5(11-25)min,p=0.21) or time from imaging to randomization(EVT:55(40.5-72.5)min vs MM:64(44-84)min,p=0.083)-Fig1a. For patients transferred to EVT-capable centers, no difference was observed between treatment arms in time from LKW to arrival - EVT:418(63-757)min vs MM:313(87.5-713)min,p=0.77; time from arrival to imaging – EVT:12(3.5-24)min vs MM:13.5(10-20)min,p=0.12; time from imaging to departure – EVT:123.5(82-195)min vs MM:128.5(85-197.5)min,p=0.95; transit time to EVT center – EVT:39(21.5-67)min vs MM:38.5(25.5-67.5)min,p=0.73); time from imaging to randomization – EVT:43(21-70)min vs MM:39(21-68)min,p=0.96)-Fig1b. Longer procedure time was associated with worse mRS (aGenOR:0.92, 95%CI:0.87-0.96,p-value:0.001 for every 10min). Longer time from perfusion imaging to reperfusion was associated with worse mRS in both direct(aGenOR:0.99(0.99-1.00),p=0.003 for every 10min) and transferred patients(aGenOR:0.98(0.95-1.00),p=0.038 for every 10min) fig2, but Interfacility transfer times or other time metrics were not significantly associated with functional outcomes. Conclusion: In large ischemic core infarct patients randomized in the SELECT2 trial, longer times from imaging to reperfusion and procedure time were associated with worse clinical outcomes after thrombectomy. Expedited and efficient workflow protocols at thrombectomy centers are vital to optimize outcomes in large core 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 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)0.005
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.400
Teacher spread0.322 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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