Relevance of cervical internal carotid artery patency after thrombectomy in tandem occlusion. Are we missing an opportunity to revascularize?
Bibliographic record
Abstract
BACKGROUND: Treatment options for cervical internal carotid artery (c-ICA) occlusion in tandem occlusions (TOs) include emergent carotid artery stenting (eCAS) and angioplasty. We attempted to determine the impact of c-ICA reocclusion on the risk of recurrent ischemic stroke (IS) and stroke-related death, as well as functional independence. METHODS: Patients with TOs undergoing endovascular thrombectomy (EVT) from April 2016 to October 2024 were included. The primary outcome was the 90-day composite of recurrent IS and stroke-related death. Secondary outcomes included the rate of 90-day functional independence (modified Rankin Scale (mRS) 0-2) and mortality. We used binary logistic regression to explore the association between c-ICA reocclusion and the outcomes and to identify predictors of c-ICA reocclusion or future revascularization. RESULTS: We included 163 patients, 85.9% with successful recanalization. Angioplasty and eCAS were performed in 70% and 19%, respectively. c-ICA reocclusion occurred in 22% at a median of 3.5 (0-41.7) days. c-ICA reocclusion increased the odds of recurrent IS or stroke-related death (adjusted OR (aOR) 2.90, 95% CI 1.07 to 8.30, P=0.036) and was associated with lower rates of independence (aOR 0.18, 95% CI 0.05 to 0.58, P=0.004). Among patients who did not undergo eCAS, c-ICA angioplasty (aHR 0.28, 95% CI 0.09 to 0.86, P=0.026) and residual stenosis (aHR 1.04, 95% CI 1.02 to 1.07, P<0.001) were independent predictors of reocclusion or future revascularization. CONCLUSION: Maintaining c-ICA patency after EVT might be essential due to the association of reocclusion with recurrent IS, stroke-related death, and worse functional outcomes. Residual c-ICA stenosis and angioplasty are valuable predictors of c-ICA patency that can guide management during EVT.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".