GR.5 Incidence of orbital infarction syndrome following endovascular thrombectomy
Bibliographic record
Abstract
Background: Orbital infarction syndrome (OIS) is a rare entity defined as acute ischemia of intraorbital structures. Three case reports of OIS post-endovascular thrombectomy (EVT) have recently been published, two demonstrating absent choroid blush (CB) on digital subtraction angiogram (DSA). Our goals are to determine the true incidence of OIS post-EVT and to identify imaging findings (e.g. CB) that may alert neurologists to potential cases. Methods: A retrospective cohort study including all EVT patients from Health Sciences Center (HSC), Winnipeg in 2019-20 was performed. Patient charts were reviewed to determine the incidence of OIS. Pre- and post-EVT DSA images were reviewed, and the sensitivity and specificity of absent CB for OIS was calculated. Results: Out of 248 patients, 13 were excluded for incomplete charts, and 4 cases (1.7%) of OIS were discovered. During sensitivity/specificity analysis of absent CB for OIS, 51 patients were excluded for inadequate imaging. There were 4 true positives, 0 false-negatives, 113 true-negatives, and 67 false-positives; resulting in a sensitivity of 100% and worst-case scenario specificity of 63% (assuming all 51 indeterminate cases were false positives). Conclusions: OIS is rare post-EVT with an incidence of 1.7%. Absent CB is very sensitive for diagnosing OIS with lower specificity.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".