Therapeutic effect of pre-operative tirofiban on patients with acute ischemic stroke with mechanical thrombectomy within 6–24 hours
Bibliographic record
Abstract
Objective The objective of this study was to investigate and discuss the therapeutic effect of pre-operative tirofiban on patients with acute ischemic stroke (AIS) with mechanical thrombectomy (MT) within 6–24 h. Patients and methods We retrospectively queried our AIS database from January to November 2018, and selected 99 patients with AIS within 6–24 h and evidence of proximal large vessel occlusion who were suitable for MT. They were divided into two groups, group A (with tirofiban, n = 56) and group B (without tirofiban, n = 43), according to whether they were intravenously infused with tirofiban before MT. The baseline characteristics and outcomes of patients were subjected to statistical analysis, including age, gender and risk factors, occlusion site, the time from onset to door, time of door to puncture, baseline National Institutes of Health Stroke Scale (NIHSS), pre-operative Alberta stroke programme early CT (ASPECT) score, angioplasty/stenting, modified Rankin Scale score 0–2 at 3 months, symptomatic haemorrhage and mortality, the time of door to recanalization, endovascular procedure time, 7-day (7d) NIHSS score, and a modified treatment in cerebral infarction (m-TICI) grade of 2b or 3. All of the thrombi were analysed by histopathology. Results The differences in the time of door to recanalization, endovascular procedure time, 7d NIHSS score and the m-TICI were significantly different between groups ( P < 0.05). The other agents were not significantly different between groups ( P > 0.05 each). Histopathological analysis showed that all thrombi contained different amounts of platelets, fibrinogen, Haemamoebas and red blood cells. Conclusion The use of tirofiban before MT can shorten the procedure time and improve the recanalization rate of occluded vessels in AIS patients.
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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 | 0.000 |
| 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".