Effectiveness and safety of EVT in patients with acute LVO and low NIHSS
Bibliographic record
Abstract
Background and purpose: There is much uncertainty in endovascular treatment (EVT) decisions in patients with acute large vessel occlusion (LVO) and mild neurological deficits. Methods: From a prospective, nationwide stroke registry, all patients with LVO and baseline NIHSS <6 presenting within 24 h from the time last known well (LKW) were included. Early neurological deterioration (END) developed before EVT was prospectively collected as an increasing total NIHSS score ≥2 or any worsening of the NIHSS consciousness or motor subscores during hospitalization not related to EVT. Significant hemorrhage was defined as PH2 hemorrhagic transformation or hemorrhage at a remote site. The modified Rankin Scale (mRS) was prospectively collected at 3 months. Results: Among 1,083 patients, 149 (14%) patients received EVT after a median of 5.9 [3.6-12.3] h after LKW. In propensity score-matched analyses, EVT was not associated with mRS 0-1 (matched OR 0.99 [0.63-1.54]) but increased the risk of a significant hemorrhage (matched OR, 4.51 [1.59-12.80]). Extraneous END occurred in 207 (19%) patients after a median of 24.5 h [IQR, 13.5-41.9 h] after LKW (incidence rate, 1.41 [95% CI, 1.23-1.62] per 100 person-hours). END unrelated to EVT showed a tendency to modify the effectiveness of EVT (P-for-interaction, 0.08), which decreased the odds of having mRS 0-1 in mild LVO patients without END (adjusted OR, 0.63 [0.40-0.99]). Conclusions: The use of EVT in patients with acute LVO and low NIHSS scores may require the assessment of individual risks of early deterioration, hemorrhagic complications and expected benefit.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".