Influencing factors of PH2 intracranial hemorrhage after endovascular treatment in acute ischemic stroke: analysis of 64 cases
Bibliographic record
Abstract
Objective To investigate the influencing factors of intracranial hemorrhage (ICH) of parenchymal hemorrhage type 2 (PH2) after endovascular treatment (EVT) in patients with acute ischemic stroke (AIS). Methods A total of 64 AIS patients who were admitted to the First Affiliated Hospital of Army Medical University and received endovascular treatment from April 1, 2020 to December 31, 2020 were enrolled in this study, and the presence of PH2 ICH was determined by cranial CT scanning within 72 h after operation. The clinical data of the patients were collected and retrospectively reviewed, including age, gender, hypertension, diabetes, hyperlipidemia, coronary heart disease, atrial fibrillation, stroke history, National Institutes of Health Stroke Scale (NIHSS) score, blood pressure, blood glucose, glycosylated hemoglobin, platelet, international normalized ratio (INR), cardiogenic embolism, preoperative antithrombotic therapy, preoperative intravenous thrombolysis, and Alberta Stroke Program Early CT Score (ASPECTS). Results Among all the 64 patients, 28 cases (28/64, 43.8%) were diagnosed with ICH within 72 h after surgery, among which 9 cases (9/64, 14.1%) had PH2 ICH. In the PH2 group, the median blood glucose (7.50 vs 6.58, P=0.039), proportion of women (77.8% vs 38.2%, P=0.035), and proportion of cardiogenic embolism (88.9% vs 49.1%, P=0.033) were significantly higher, whereas the median ASPECTS (6 vs7, P=0.026) and proportion of ASPECTS >6 (22.2% vs 63.6%, P=0.029) were greatly lower than those of the non-PH2 group. In addition, the increased blood glucose presented as a risk factor for the occurrence of PH2 ICH (OR=1.48, 95%CI: 1.00~2.18). Conclusion Elevated blood glucose may increase the risk of developing PH2 ICH after EVT in patients with AIS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".