Recanalization of the Chronically Occluded Internal Carotid Artery: Review of the Literature
Bibliographic record
Abstract
We reviewed the literature on interventions for patients with medically refractory chronically occluded internal carotid artery (COICA) to assess the risks and/or benefits after recanalization via an endovascular technique (ET) or hybrid surgery (HS, i.e., ET plus carotid endarterectomy). A systematic search of the electronic databases was performed. Patients with COICA were classified into 4 different categories according to Hasan et al classification. Eighteen studies satisfied the inclusion criteria. Only 6 studies involved an HS procedure. We identified 389 patients with COICA who underwent ET or HS; 91% were males. The overall perioperative complication rate was 10.1% (95% confidence interval [CI]: 7.4%–13.1%). For types A and B, the successful recanalization rate was 95.4% (95% CI: 86.5%–100%), with a 13.7% (95% CI: 2.3%–27.4%) complication rate. For type C, the success rate for ET was 45.7% (95% CI: 17.8%–70.7%), with a complication rate of 46.0% (95% CI: 20.0%–71.4%) for ET and for the HS technique 87.6% (95% CI: 80.9%–94.4%), with a complication rate of 14.0% (95% CI: 7.0%–21.8%). For type D, the success rate of recanalization was 29.8% (95% CI: 7.8%–52.8%), with a 29.8% (95% CI: 6.1%–56.3%) complication rate. Successful recanalization resulted in a symmetrical perfusion between both cerebral hemispheres, resolution of penumbra, normalization of the mean transit time, and improvement in Montreal Cognitive Assessment (MoCA) score (ΔMoCA = 9.80 points; P = 0.004). Type A and B occlusions benefit from ET, especially in the presence of a large penumbra. Type C occlusions can benefit from HS. Unfortunately, we did not identify an intervention to help patients with type D occlusions. A phase 2b randomized controlled trial is needed to confirm these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".