Ex Vivo Evaluation of a Pressure-Sensitive Device to Aid Big Bubble Intrastromal Dissection in Deep Anterior Lamellar Keratoplasty
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Bibliographic record
Abstract
Purpose: To develop and perform ex vivo testing for a device designed for semiquantitative determination of intracorneal dissection depth during big bubble (BB) deep anterior lamellar keratoplasty. Methods: A prototype device connected to a syringe and cannula was designed to determine depth of intrastromal placement based on air rebound pressure emitted by a software controlled generator. Ex vivo testing of the device was conducted on human corneas mounted on an artificial anterior chamber in three experiments: (1) cannula purposely introduced at different depths measured with anterior segment optical coherence tomography, (2) cannula introduced as per the BB technique, and (3) simulation of the BB technique guided by the device. Results: A positive pressure differential and successful BB were observed only when the cannula was positioned within 150 microns from the endothelial plane. In all successful BB cases (21/40), a repeatable increase in tissue rebound pressure was detected, which was not recorded in unsuccessful cases. The device was able to signal to the surgeon correct placement of the cannula (successful BB) in 16 of 17 cases and incorrect placement of the cannula (unsuccessful BB) in 8 of 8 cases (94.1% sensitivity, 100% specificity). Conclusions: In our ex vivo model, this novel medical device could reliably signal cannula positioning in the deep stroma for effective pneumatic dissection and possibly aid technical execution of BB deep anterior lamellar keratoplasty. Translational Relevance: A medical device that standardizes big bubble deep anterior lamellar keratoplasty could increase the overall success rate of the surgical procedure and aid popularization of deep anterior lamellar keratoplasty.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it