Permanent unilateral visual loss and orbital compartment syndrome following unilateral frontal craniotomy: illustrative case
Bibliographic record
Abstract
BACKGROUND: Vision loss following supine craniotomy is an unexpected and devastating complication for the patient and the operating team. Postoperative vision loss (POVL) is commonly associated with cardiac, spinal, neck, and prone head surgeries, as they share common risk factors, such as a prone position, intraoperative hypotension, a longer anesthesia duration, and the use of vasopressors. Herein, the authors report a case of irreversible vision loss following a frontal craniotomy in the supine position together with a review of the literature. All published cases in the literature since the first reported case in 1970 are summarized. Possible etiologies and proposed preventive measures are discussed. OBSERVATIONS: Different pathologies, such as vascular, intra-axial, and extra-axial lesions, are associated with POVL and have similar clinical courses and nonrecovery rates, which raises the question of whether POVL begins during the exposure part of these surgeries. LESSONS: Preventive measures could include avoiding direct ocular pressure during flap reflection, the use of elastic bands or fishhooks to avoid stretching the orbital contents and impairing venous outflow, and a careful review of the venous drainage of frontal tumors, which could help avoid unnecessary large venous thrombi or waxing. The role of intraoperative visual neurophysiological monitoring in predicting POVL requires further exploration. https://thejns.org/doi/10.3171/CASE2434.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".