Acute ischemic stroke due to posterior cerebral artery P2 segment occlusion treated with mechanical thrombectomy
Bibliographic record
Abstract
Abstract Introduction: Mechanical thrombectomy (MT) has become part of the standard treatment for patients who have acute ischemic stroke due to large-vessel occlusion in the anterior cerebral circulation. But the safety and effectiveness of MT for posterior cerebral artery (PCA) is still controversial. Patient concerns: We report a 40-year-old man with a medical history of hypertension who was non-compliant with the treatment. He presented to the hospital with right extremity paralysis, aphasia, and left gaze paralysis due to the occlusion of left PCA P2 segment (National Institutes of Health Stroke Scale Score 16). Head computed tomography showed infarction area of left temporal lobe and occipital lobe. Diagnosis: A head computed tomography angiography examination showed left PCA P2 segment occlusion. Interventions: The patient underwent MT and subsequent angiography showed left PCA P2 segment occlusion was recanalized after MT. Outcomes: The patient's symptoms improved completely after MT. Conclusion: The clinical symptoms due to PCA P2 segment occlusion may be mistaken clinically for MCA stroke syndrome, which may lead to severe functional deficit. MT seems to be safe and effective in treating PCA P2 segment occlusion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".