Exophthalmos following mechanical thrombectomy for anterior circulation stroke: A retrospective study and review of literature
Bibliographic record
Abstract
BACKGROUND: Anecdotal cases of exophthalmos after acute mechanical thrombectomy have been described. We sought to estimate the incidence in a large cohort of patients with acute anterior circulation stroke treated with mechanical thrombectomy. Secondarily, we aimed to evaluate the underlying mechanism and to differentiate it on imaging from other pathology with similar clinical orbital features. METHODS: Between November 2016 and November 2018, we performed a retrospective single-center study of 250 patients who underwent anterior circulation mechanical thrombectomy. Development of exophthalmos was independently evaluated by two readers on preprocedure and 24-h postprocedure non-contrast cerebral CT. RESULTS: In the mechanical thrombectomy cohort, six individuals (2.4%) developed interval ipsilateral exophthalmos at 24 h. Of these, at least two patients developed clinical symptoms. There was almost perfect agreement between assessments of the two readers (Cohen's kappa = 0.907 (95% confidence interval: 0.726, 1.000)). In two patients, there was delayed ophthalmic artery filling on digital subtraction angiography. None of the patients had features of a direct carotid-cavernous fistula. CONCLUSIONS: Exophthalmos is not uncommon after mechanical thrombectomy (2.4%). The underlying mechanism is difficult to confirm, but it is most likely due to orbital ischemia from hypoperfusion or distal emboli.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".