Predictors of Symptomatic Hemorrhage After Endovascular Treatment for Anterior Circulation Occlusions: Turkish Endovascular Stroke Registry
Bibliographic record
Abstract
We evaluated the predictive factors of symptomatic intracranial hemorrhage (SICH) in endovascular treatment of stroke. We included 975 ischemic stroke patients with anterior circulation occlusion. Patients that had hemorrhage and an increase of ≥4 points in their National Institutes of Health Stroke Scale (NIHSS) after the treatment were considered as SICH. The mean age of patients was 65.2±13.1 years and 469 (48.1%) were women. The median NIHSS was 16 (13–18) and Alberta Stroke Program Early CT 9 (8–10). In 420 patients (43.1%), modified Rankin Scale was favorable (0–2) and mortality was observed in 234 (24%) patients at the end of the third month. Patients with high diastolic blood pressure ( P<.05) had significantly higher SICH. SICH was significantly higher in those with high NIHSS scores ( P<.001), high blood glucose ( P<.001), and leukocyte count at admission ( P<.05). Diabetes mellitus (DM) (OR 1.90; P<.001), NIHSS (OR 1.07; P<.05), adjuvant intra-arterial thrombolytic therapy (IA-rtPA) (OR, 1.60; P<.05), and puncture-recanalization time (OR 1.01; P<.05) were independent factors of SICH. Higher baseline NIHSS score, longer procedure time, multiple thrombectomy maneuvers, administration of IA-rtPA, and the history of DM are independent predictors of SICH in anterior circulation occlusion.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".