Fixation of Extraocular Muscles to Porous Orbital Implants Using 2-Ocetyl-Cyanoacrylate Glue
Bibliographic record
Abstract
PURPOSE: To assess the efficacy of recti muscle fixation with 2-ocetyl-cyanoacrylate tissue glue to porous orbital implants in human subjects undergoing enucleation. METHODS: This was a prospective interventional study with a historical control group. Over a 1-year period, patients who received orbital implant fixation using 2-ocetyl-cyanoacrylate tissue glue were enrolled in the study. Functional assessment was carried out by measurement of implant motility at the 6-month postoperative period, which was compared with a historical control group of patients with sutured implants. Structural assessment was carried out with a random sample of orbital MRIs. RESULTS: Twelve patients received the glue-fixation technique. There were no intraoperative or immediate postoperative complications. There was no statistically significant difference between the glued and sutured groups' horizontal implant movement (7.0 mm ± 1.5 mm vs. 6.8 mm ± 1.8 mm, respectively; p = 0.85) or vertical implant movement (5.6 mm ± 1.7 mm vs. 5.0 mm ± 1.4 mm, respectively; p = 0.39). Sample orbital MRI demonstrated good muscle approximation to the implants as well as contrast enhancement suggestive of successful fibrovascular proliferation. CONCLUSIONS: Recti muscle fixation using 2-ocetyl-cyanoacrylate tissue glue to porous orbital implants appeared safe and produced good functional and structural results in this proof-of-concept study. This novel technique of implant fixation may offer benefits in terms of reduced operating room time and cost savings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".