Changing Trends in Hyperacute Stroke Treatment and Early Clinical Outcomes Reflecting Recent Improvement in Endovascular Thrombectomy Techniques
Bibliographic record
Abstract

 
 
 Objective: Ischemic stroke is a major disease causing death and permanent neurological disability with the mainstay treatment being to re-established blood flow as quickly as possible. Recent changes in the efficiency of endovascular devices performing thrombectomies have led to it now being considered the gold standard. Nevertheless, successful endovascular thrombectomy (EVT) requires access to many resources and expertise which may impact its effectiveness. The objective of the current study is to describe the application and utility of EVT in the clinical treatment of ischemic stroke at a single tertiary care hospital.
 Methods: This is a descriptive retrospective cohort study from a stroke database. A total of 548 patients diagnosed with an ischemic stroke affecting large cerebral arteries between January 2010 and June 2016 were included. National Institute of Health Stroke Scale (NIHSS) score was used to evaluate stroke severity upon admission. Modified Ranking Scale was used to determine the functional status of patients upon discharge. Successful reperfusion defined as a TICI score of 2B or 3, age, thrombolytic use and time- to-treatment were all considered for analysis.
 Results: Thrombectomies became more frequent (p<0.001) with shorter time-to-treatment in recent years (p=0.001). A successful thrombectomy has significantly improved functional status at discharge (p<0.001), even when thrombolytics were not given (p=0.003) or when patients were over 80 years old (p=0.021).
 Conclusion: The current work provides evidence that this single hospital has increased its frequency of application of EVT for ischemic stroke, leading to a better functional outcome at discharge independent of prior thrombolysis or age. 
 
 
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".