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Record W4391438324 · doi:10.1161/str.55.suppl_1.155

Abstract 155: Critical Care Decisions After Large Core Cerebral Infarctions: <i>A Secondary Analysis From the SELECT2 Trial</i>

2024· article· en· W4391438324 on OpenAlexaff
Scott E. Kasner, Michael DeGeorgia, Jan‐Karl Burkhardt, Michael Abraham, Michael Chen, Muhammad Shazam Hussain, Santiago Ortega‐Gutiérrez, Yin Hu, Nicholas C. Bambakidis, Deep Pujara, Faris Shaker, Spiros Blackburn, Rami Moussa, Leonid Churilov, Wei Xiong, Amanda Opaskar, Faisal Al-Shaibi, Hannah Johns, Sophia Sundararajan, Clark Sitton, Cathy A. Sila, Anthony J. Furlan, Vítor Mendes Pereira, Michael D. Hill, James C. Grotta, Marc Ribó, Ameer E Hassan, Bruce Campbell, Amrou Sarraj

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of CalgarySt. Michael's Hospital
Fundersnot available
KeywordsMedicineRandomizationPopulationRelative riskRandomized controlled trialStroke (engine)SurgeryCardiologyInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Background/hypothesis: The SELECT2 trial randomly assigned patients with LVO and large ischemic cores to either endovascular thrombectomy (EVT) or medical management (MM). This population is at high risk for cerebral edema and other complications, often leading to critical decisions about decompressive hemicraniectomy (DHC) or early withdrawal of care (WOC). We hypothesized that patients initially treated with EVT were more likely to get life-sustaining care regardless of recanalization success, presumably because initial treatment with EVT led toward an expectation of aggressive care, while those treated with MM expected futility. Methods: We analyzed the full SELECT2 study population using the as-treated principle, comparing the use of DHC and early (within 7 days from randomization) transition to comfort measures/WOC. We also compared these decisions based on recanalization success in those receiving EVT. We further tested baseline characteristics for association with these outcomes. Results: Patients treated with EVT were as likely to undergo DHC (aRR:1.19 [0.75-1.88], p=0.46) or WOC (aRR:0.94 [0.66-1.34], p=0.72) as those given MM (Table). Time to DHC was also similar (EVT 47[19-74] vs. MM 36[27-61] hours, p=0.95). Patients with successful (mTICI≥2b) recanalization were numerically less likely to undergo DHC than those with unsuccessful (TICI 0-2a) recanalization (aRR:0.66 [0.33-1.3], p=0.23), while WOC was similar (Table). Larger estimated core volumes were associated with both DHC and WOC, with DHC used more in younger and WOC more in older patients. Conclusions: In the SELECT2 trial of patients with large infarct cores, DHC was performed in ~1 in 6 and WOC in ~1 in 5, without an observed difference based on treatment with EVT or MM. The similar distribution of decisions to proceed with DHC or to change goals of care to acute palliative measures provides reassurance that the overall trial outcomes were not biased by open-label treatment allocation.

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)0.010
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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.022
GPT teacher head0.315
Teacher spread0.293 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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