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Record W4400878014 · doi:10.1161/strokeaha.123.045871

HERMES-24 Score Derivation and Validation for Simple and Robust Outcome Prediction After Large Vessel Occlusion Treatment

2024· article· en· W4400878014 on OpenAlexafffund
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, Yvo B.W.E.M. Roos, Wim H. van Zwam, Mohamed Najm, Dar Dowlatshahi, Michael D. Hill, Andrew M. Demchuk

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsOttawa HospitalUniversity of Calgary
FundersNational Health and Medical Research CouncilCanadian Institutes of Health ResearchMaastricht Universitair Medisch CentrumHLS TherapeuticsServierStrykerDaiichi Sankyo EuropeBayer HealthCareNational Stroke FoundationCSL BehringNational Heart Foundation of AustraliaMedical Research CouncilBiogenAbbott Laboratories
KeywordsMedicineCohortModified Rankin ScaleLogistic regressionStroke (engine)DerivationThrombusInternal medicineSurgeryIschemic strokeIschemiaArtery

Abstract

fetched live from OpenAlex

BACKGROUND: Clinicians need simple and highly predictive prognostic scores to assist practical decision-making. We aimed to develop a simple outcome prediction score applied 24 hours after anterior circulation acute ischemic stroke treatment with endovascular thrombectomy and validate it in patients treated both with and without endovascular thrombectomy. METHODS: Using the HERMES (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) collaboration data set (n=1764), patients in the endovascular thrombectomy arm were divided randomly into a derivation cohort (n=430) and a validation cohort (n=441). From a set of candidate predictors, logistic regression modeling using forward variable selection was used to select a model that was both parsimonious and highly predictive for modified Rankin Scale (mRS) ≤2 at 90 days. The score was validated in validation cohort, control arm (n=893), and external validation cohorts from the ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischaemic Stroke; n=1066) and INTERRSeCT (Identifying New Approaches to Optimize Thrombus Characterization for Predicting Early Recanalization and Reperfusion With IV Alteplase and Other Treatments Using Serial CT Angiography; n=614). RESULTS: In the derivation cohort, we selected 2 significant predictors of mRS ≤2 (National Institutes of Health Stroke Scale score at 24 hours and age [β-coefficient, 0.34 and 0.06]) and derived the HERMES-24 score: age (years)/10+National Institutes of Health Stroke Scale score at 24 hours. The HERMES-24 score was highly predictive for mRS ≤2 (c-statistic 0.907 [95% CI, 0.879-0.935]) in the derivation cohort. In the validation cohort and the control arm, the HERMES-24 score predicts mRS ≤2 (c-statistic, 0.914 [95% CI, 0.886-0.944] and 0.909 [95% CI, 0.887-0.930]). Observed provability of mRS ≤2 ranged between 3.1% and 3.4% when HERMES-24 score ≥25, while it ranged between 90.6% and 93.0% when HERMES-24 score <10 in the derivation cohort, validation cohort, and control arm. The HERMES-24 score also showed c-statistics of 0.894 and 0.889 for mRS ≤2 in the ESCAPE-NA1 and INTERRSeCT populations. CONCLUSIONS: The post-treatment HERMES-24 score is a simple validated score that predicts a 3-month outcome after anterior circulation large vessel occlusion stroke regardless of intervention, which helps prognostic discussion with families on day 2.

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)0.021
metaresearch head score (Gemma)0.047
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 score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.047
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.288
Teacher spread0.260 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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