Reperfusion strategies in stroke due to isolated cervical internal carotid artery occlusion: systematic review and treatment comparison
Bibliographic record
Abstract
INTRODUCTION: Despite intravenous thrombolysis (IVT) and endovascular treatment (EVT) have been demonstrated effective in acute ischemic stroke (AIS) due to large vessel occlusions, there are still no conclusive data to guide treatment in stroke due to cervical internal carotid artery (ICA) occlusion. We systematically reviewed available literature to compare IVT, EVT, and bridging (IVT + EVT) and define optimal treatment. METHODS: Systematic review followed predefined protocol (Open-Science-Framework osf.io/bfykj ). MEDLINE, EMBASE, and Cochrane CENTRAL were searched. Results were restricted to studies in English, with sample size ≥ 10 and follow-up ≥30 days. Primary outcomes were favorable outcome (mRS ≤ 2), mortality, and symptomatic intracerebral hemorrhage(sICH), defined according to study original report. Newcastle-Ottawa scale was used for bias assessment. RESULTS: Seven records of 930 screened were included in meta-analysis. Quality of studies was low-to-fair in 5, good in 2. IVT (n = 450) did not differ for favorable outcome and mortality compared to EVT (n = 150), though having lower rate of sICH (OR = 0.4, 95% CI 0.2-0.8). Compared to IVT, bridging (IVT + EVT) was associated with higher rate of favorable outcome (OR = 2.2, 95% CI 1.3-3.7). Compared to EVT, bridging (IVT + EVT) provided higher rate of favorable outcome (OR = 1.9, 95% CI 1.1-3.4), with a marginally increased risk of sICH (OR = 2.1, 95% CI 1-4.4) but similar mortality rates. CONCLUSIONS: Our systematic review highlights that, in acute ischemic stroke associated with isolated cervical ICA occlusion, bridging (IVT + EVT) might lead to higher rate of functional independence at follow-up, without increasing mortality. The low quality of available studies prevents from drawing firm conclusions, and randomized-controlled clinical trials are critically needed to define optimal treatment in this AIS subgroup.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.014 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".