Validation of the HERMES-24 Score for Outcome Prediction Post Large Vessel Occlusion Treatment in Later Time Window
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials (HERMES)-24 score is highly predictive of outcomes after anterior circulation large vessel occlusion (LVO) treatment, irrespective of intervention in the early time window. Recent evidence has further broadened the eligibility of endovascular therapy (EVT) to patients with late presentation or unwitnessed onset including those with stroke-on-awakening. We aimed to investigate the prediction ability of the HERMES-24 score in patients with anterior circulation LVO and small ischemic core presenting in the late time window from last seen normal. METHODS: Data are from the Analysis of Pooled Data from Randomized Studies of Thrombectomy More Than 6 Hours After Last Known Well collaboration, a patient-level meta-analysis of 6 randomized trials of EVT beyond 6 hours after last known well, with an enrollment period from September 2014 to March 2019. Patients who were also part of the HERMES collaboration data set were excluded from the analyses. The HERMES-24 score was calculated as the sum of the patient's age/10 and NIH Stroke Scale (NIHSS) score at 24 hours after randomization. The predictive ability of the score for a 90-day outcome (modified Rankin Scale [mRS] scores ≤2 and ≤3, ordinal mRS score, and mortality) was investigated. RESULTS: -statistic [95% CI] 0.921 [0.872-0.969], 0.879 [0.827-0.930], 0.805 [0.746-0.852], and 0.805 [0.738-0.871], respectively). DISCUSSION: The HERMES-24 score was highly predictive of 90-day outcome among patients with stroke due to LVO and small ischemic core for those presenting in the late time window, irrespective of intervention. This score must be further validated in a real-world clinical setting if it is applicable to all patients with LVO admitted in late time windows.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.013 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".