Comparative study of direct mechanical thrombectomy and bridging therapy for acute anterior circulation large-artery occlusive stroke
Bibliographic record
Abstract
Objective To comparatively analyze the safety and efficacy of direct mechanical thrombectomy and bridging therapy for patients with acute anterior circulation large-artery occlusive stroke. Methods A total of 116 patients with acute anterior circulation large-artery occlusive stroke, admitted to our hospitals from October 2015 to March 2018, were chosen in our study; their clinical data were analyzed retrospectively. Among them, 63 patients accepted direct mechanical thrombectomy and 53 accepted bridging therapy. The preoperative baseline data and the diagnoses and treatments of the two groups were analyzed; the degrees of modified thrombolysis in cerebral infarction (mTICI), incidences of hemorrhage transformation and symptomatic intracranial hemorrhage, and modified Rankin scale (mRS) scores and mortality rate 90 d after operation were compared between the two groups. Results The preoperative Alberta stroke program early CT scale (ASPECTS) and Glasgow Coma Scale (GCS) scores of the direct mechanical thrombectomy group were significantly lower than those of the bridge therapy group (P 0.05). Conclusion The clinical efficacy and safety of direct mechanical thrombectomy and bridging therapy for patients with acute anterior circulation large-artery occlusive stroke are similar. Key words: Ischemic stroke; Anterior circulation; Mechanical thrombectomy; Intravenous thrombolysis; Bridging therapy
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".