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Record W4399422562 · doi:10.1212/wnl.0000000000209454

Association Between Time to Treatment With Endovascular Thrombectomy and Home-Time After Acute Ischemic Stroke

2024· article· en· W4399422562 on OpenAlexaffabout
Raed A. Joundi, Michael D. Hill, Jillian Stang, Dana Nicol, Amy Yu, Moira K. Kapral, James A. King, Mary-Lou Halabi, Eric E. Smith

Bibliographic record

VenueNeurology · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsAlberta Health
Fundersnot available
KeywordsMedicineStroke (engine)Ischemic strokeEndovascular treatmentAcute strokeCardiologyInternal medicineEmergency medicineSurgeryIschemiaTissue plasminogen activatorAneurysm

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Home-time is a patient-prioritized stroke outcome that can be derived from administrative data linkages. The effect of faster time-to-treatment with endovascular thrombectomy (EVT) on home-time after acute stroke is unknown. METHODS: We used the Quality Improvement and Clinical Research registry to identify a cohort of patients who received EVT for acute ischemic stroke between 2015 and 2022 in Alberta, Canada. We calculated days at home in the first 90 days after stroke. We used ordinal regression across 6 ordered categories of home-time to evaluate the association between onset-to-arterial puncture and higher home-time, adjusting for age, sex, rural residence, NIH Stroke Scale, comorbidities, intravenous thrombolysis, and year of treatment. We used restricted cubic splines to assess the nonlinear relationship between continuous variation in time metrics and higher home-time, and also reported the adjusted odds ratios within time categories. We additionally evaluated door-to-puncture and reperfusion times. Finally, we analyzed home-time with zero-inflated models to determine the minutes of earlier treatment required to gain 1 day of home-time. RESULTS: We had 1,885 individuals in our final analytic sample. There was a nonlinear increase in home-time with faster treatment when EVT was within 4 hours of stroke onset or 2 hours of hospital arrival. There was a higher odds of achieving more days at home when onset-to-puncture time was <2 hours (adjusted odds ratio 2.36, 95% CI 1.77-3.16) and 2 to <4 hours (1.37, 95% CI 1.11-1.71) compared with ≥6 hours, and when door-to-puncture time was <1 hour (aOR 2.25, 95% CI 1.74-2.90), 1 to <1.5 hours (aOR 1.89, 95% CI 1.47-2.41), and 1.5 to <2 hours (1.35, 95% CI 1.04-1.76) compared with ≥2 hours. Results were consistent for reperfusion times. For every hour of faster treatment within 6 hours of stroke onset, there was an estimated increase in home-time of 4.7 days, meaning that approximately 1 day of home-time was gained for each 12.8 minutes of faster treatment. DISCUSSION: Faster time-to-treatment with EVT for acute stroke was associated with greater home-time, particularly within 4 hours of onset-to-puncture and 2 hours of door-to-puncture time. Within 6 hours of stroke onset, each 13 minutes of faster treatment is associated with a gain of 1 day of home-time.

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)0.006
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 score0.095
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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