Effect of age and baseline ASPECTS on outcomes in large-vessel occlusion stroke: results from the HERMES collaboration
Bibliographic record
Abstract
BACKGROUND: Patient age and baseline Alberta Stroke Program Early CT score (ASPECTS) are both independent predictors of outcome in acute ischemic stroke patients treated with endovascular therapy (EVT). We assessed the combined effect of age and ASEPCTS on clinical outcome in acute ischemic stroke patients with LVO with and without EVT, and EVT treatment effect in different age/ASPECTS subgroups. METHODS: The HERMES collaboration pooled data of seven randomized controlled trials that tested the efficacy of EVT. Adjusted logistic regression was performed to test for multiplicative interaction of age and ASPECTS with the primary outcome (ordinal mRS) and secondary outcomes (mRS 0-2/0-1/0-3) in the EVT and control arms. Patients were then stratified by age (<75 vs ≥ 75 years) and ASPECTS (0-5/6-7/8-10), and adjusted effect-size estimates for the association of EVT were derived for the six age/ASPECTS subgroups. RESULTS: 1735 patients were included in the analysis. There was no multiplicative interaction between age and ASPECTS on clinical outcomes. In the exploratory subgroup analysis, we found a nominally negative point estimate for the association of EVT with clinical outcome in the ASPECTS 0-5/age ≥75, subgroup (acOR 0.36, 95% CI 0.07 to 1.89). The point estimate for moderate outcome (mRS0-3) nominally favored EVT (aOR 1.24, 95% CI 0.16 to 9.84). In all other subgroups, effect size-estimates consistently favored EVT. CONCLUSION: There was no multiplicative interaction of age and ASPECTS on clinical outcomes in EVT or control arm patients. Outcomes in patients ≥75 years with ASPECTS 0-5 were poor, irrespective of treatment. Further investigation to define the role of EVT and range of acceptable outcomes in this subgroup is warranted.
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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 | 0.059 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".