Radiological findings in patients with isolated acute-onset ocular motility disorders
Bibliographic record
Abstract
To image or not to image is a critical question in patients with isolated acute-onset ocular motility disorders (AOMD), without any neurological symptoms/signs. Imaging may help in diagnosis; but is associated with risks and costs. The study aimed to evaluate radiological findings in patients with apparently isolated AOMD on clinical exam, and identify patient/disease characteristics more likely to be associated with positive imaging. A retrospective review of patient charts with isolated AOMD (< 3 months onset), who were examined by an ophthalmologist and had imaging at a tertiary-care center over a period of 18 months, was conducted. Ophthalmology exam and diagnostic imaging findings were recorded. Radiological findings were classified as “clinically relevant”, “non-relevant”, and “normal/no positive” findings. 46 patients were included (3-91 years; 27 males, 19 females). 19 were clinically classified as nerve palsy (1 third, 10 fourth, and 8 sixth nerve), 14 acute-onset esotropia, 3 acute-onset exotropia, 7 acute-onset vertical strabismus inconsistent with nerve palsy, and 3 limitation of elevation/suspected dorsal midbrain syndrome. We found 8/46 (17%) with clinically relevant imaging findings; of these, 5/46 (11%) had positive neuro-imaging findings (mass, malformation, aneurysm, infarct) and 3/46 (7%) had positive orbital imaging findings (thyroid eye disease). Positive neuro-imaging was more common in patients with certain symptoms (headache), in certain clinical diagnostic entities (dorsal midbrain syndrome spectrum, acute-onset esotropia), and in younger patients (<40 years). Positive neuro-imaging findings may be seen even in patients with apparently isolated ocular symptoms/signs on clinical exam. This data may help institutions with decision-making and policy formulation for imaging patients with isolated AOMD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".