Predictors of parenchymal hemorrhage after endovascular treatment in acute ischemic stroke: data from ANGEL-ACT Registry
Bibliographic record
Abstract
BACKGROUND: Parenchymal hemorrhage (PH) is a troublesome complication after endovascular treatment (EVT). OBJECTIVE: To investigate the incidence, independent predictors, and clinical impact of PH after EVT in patients with acute ischemic stroke (AIS) due to anterior circulation large vessel occlusion (LVO). METHODS: Subjects were selected from the ANGEL-ACT Registry. PH was diagnosed according to the European Collaborative Acute Stroke Study classification. Logistic regression analyses were performed to determine the independent predictors of PH, as well as the association between PH and 90-day functional outcome assessed by modified Rankin Scale (mRS) score. RESULTS: Of the 1227 enrolled patients, 147 (12.0%) were diagnosed with PH within 12-36 hours after EVT. On multivariable analysis, low admission Alberta Stroke Program Early CT score (ASPECTS)(adjusted OR (aOR)=1.13, 95% CI 1.02 to 1.26, p=0.020), serum glucose >7 mmol/L (aOR=1.82, 95% CI 1.16 to 2.84, p=0.009), and neutrophil-to-lymphocyte ratio (NLR; aOR=1.05, 95% CI 1.02 to 1.09, p=0.005) were associated with a high risk of PH, while underlying intracranial atherosclerotic stenosis (ICAS; aOR=0.42, 95% CI 0.22 to 0.81, p=0.009) and intracranial angioplasty/stenting (aOR=0.37, 95% CI 0.15 to 0.93, p=0.035) were associated with a low risk of PH. Furthermore, patients with PH were associated with a shift towards to worse functional outcome (mRS score 4 vs 3, adjusted common OR (acOR)=2.27, 95% CI 1.53 to 3.38, p<0.001). CONCLUSIONS: In Chinese patients with AIS caused by anterior circulation LVO, the risk of PH was positively associated with low admission ASPECTS, serum glucose >7 mmol/L, and NLR, but negatively related to underlying ICAS and intracranial angioplasty/stenting. TRIAL REGISTRATION NUMBER: NCT03370939.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".