Impact of general anesthesia on feline aqueous tear production and the feline corneal epithelium
Bibliographic record
Abstract
Objectives The aim of the present study was to identify the prevalence of corneal injury in cats undergoing general anesthesia (GA) while receiving prophylactic ocular lubrication, identify risk factors for corneal injury and quantify the effect of GA on tear production in cats. Methods A total of 42 cats undergoing GA for non-ophthalmic procedures were included. Before GA, an ocular examination including a Schirmer tear test-1 (STT-1) and fluorescein stain (FS) was performed. Prophylactic lubrication was administered at the time of anesthetic induction and repeated every 15 mins until extubation. At 1 h after extubation, STT-1 and FS were performed and repeated hourly for 4 h. A Shapiro–Wilk test and paired t -test compared STT-1 results before and after GA. Logistic regression was used to analyze corneal injury and possible risk factors for corneal injury. Results No cats developed FS uptake consistent with corneal ulceration. In total, 14 cats and 23 (27.4%) eyes developed corneal erosion at all time points. There was a significant decrease in tear production at all four time points after GA. Pre-medication opioid choice and corneal exposure were identified as significant risk factors for corneal injury. Conclusions and relevance Corneal ulceration did not develop after GA in this study. There was a significant decrease in tear production in cats for at least 4 h after GA. Cats appear to have a higher prevalence of corneal injury after GA compared with dogs. Frequent eye lubrication is recommended for feline patients during and after GA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".