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Record W4391447895 · doi:10.1161/str.55.suppl_1.wp248

Abstract WP248: Developing and Validating Post-Treatment HERMES Score to Predict Outcome From Anterior Circulation Large Vessel Occlusion Stroke: A Meta-Analysis of Individual Data From 7 Randomized Clinical Trials

2024· article· en· W4391447895 on OpenAlexaff
Kõji Tanaka, Scott Brown, Mayank Goyal, Bijoy K. Menon, Bruce Campbell, Peter Mitchell, Tudor G. Jovin, Jeffrey L. Saver, Keith W. Muir, Phil White, Serge Bracard, Françis Guillemin, Diederik W.J. Dippel, Charles B.L.M. Majoie, Michael D. Hill, Andrew M. Demchuk

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCohortModified Rankin ScaleStroke (engine)Quality ScoreDerivationInternal medicineStatisticsIschemic strokeOperations management

Abstract

fetched live from OpenAlex

Introduction: Clinicians need simple and highly predictive prognostic scores to assist practical decision-making and family discussion. We aimed to develop and validate a simple prediction score applied at 24 hours to assist prognostication in patients with anterior circulation ischemic stroke due to large vessel occlusion. Methods: Using the HERMES collaboration dataset (n = 1764), patients in the endovascular therapy (EVT) arm were divided randomly into a derivation cohort (n = 430) and a validation cohort (n = 441). From a set of candidate predictors, forward selection using c-statistics was employed to select a model which was both parsimonious and highly predictive for modified Rankin Scale (mRS) ≤2 at 90 days. The score was validated in both the EVT validation cohort and in the control arm (n = 893) for mRS ≤2 and ≤3. Results: In the derivation cohort, two significant predictors of mRS ≤2 (National Institutes of Health Stroke Scale [NIHSS] score at 24 h and age [β-coefficient 0.34 and 0.06]) were selected. Incorporating other variables did not much improve model performance. Among models with different weights, we derived the HERMES score: age (years)/10 + NIHSS score at 24 h, based on model performance and simplicity. The HERMES score was highly predictive for mRS ≤2 in the derivation cohort, validation cohort-EVT, and control arm (c-statistics 0.907, 0.914, and 0.909, respectively). Evaluation of the score against mRS ≤3 as an alternative outcome yielded similar results (c-statistics 0.911, 0.903, and 0.885). Among 435 subjects (24.7%) with HERMES score ≥25, the observed probability was 3.1-3.4% for mRS ≤2 and 9.4-16.7% for mRS ≤3 in the derivation cohort, validation cohort-EVT, and control arm (Figure). Conclusions: The HERMES score is a simple validated score to predict outcomes in patients with anterior circulation large vessel occlusion ischemic stroke regardless of intervention. HERMES score should be helpful in prognostic discussion with families on day two.

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)0.043
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.055
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0080.031
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.253
GPT teacher head0.446
Teacher spread0.192 · 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 designMeta-analysis
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 routes1
Has abstractyes

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