No significant retinal damage induced by major orthopedic surgery - a pilot study
Bibliographic record
Abstract
BACKGROUND: Perioperative visual loss is one of the rare but devastating complications of anesthesia and surgery. The incidence of less severe or even subclinical postoperative visual dysfunction is unknown. Therefore, we decided to perform a pilot prospective observational clinical study to evaluate whether structural changes of the retina can be detected in patients undergoing elective orthopaedic surgery by optical coherence tomography (OCT). METHODS: Adult patients indicated for elective knee replacement surgery with the absence of known retinal or optic nerve disease were included. Each patient underwent baseline OCT examination of the eyes one day before surgery and it was repeated 4-7 days after the surgery. The surgery was done under general and epidural anesthesia. RESULTS: A total of 18 patients (6 men and 12 women) at the age of 70.8±7.1 years were enrolled. We found statistically significant changes in the Macular central thickness and in a few areas of the Retinal Nerve Fiber Layer between the baseline and postoperative measurements. CONCLUSIONS: Even though we found significant changes in some parameters, we did not confirm that general anesthesia and/or surgical damage causes significant damage of the retina using OCT measurement. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04311801).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".