Coralline Hydroxyapatite Orbital Implant (Bio-Eye): Experience with 158 Patients
Bibliographic record
Abstract
PURPOSE: To assess the problems seen in 158 patients with coralline hydroxyapatite (HA) orbital implants (Bio-Eye). METHODS: A consecutive case series of 170 patients receiving coralline HA implanted by two surgeons over a 5-year period were reviewed. The authors analyzed age, type of surgery, implant size, peg system, follow-up duration, time of pegging, problems encountered, and treatment. RESULTS: Twelve patients were lost to follow-up after 5 months, leaving 158 patients who were followed from 6 to 130 months (average, 39 months). Problems in unpegged implants occurred in 36 (22.8%) patients. Discharge occurred in 18 (11.4%) patients, implant exposure in 12 (7.6%), socket discomfort in 1 (0.6%), conjunctival thinning in 3 (1.9%), chronic conjunctival swelling in 2 (1.3%), and implant infection in 3 (1.9%). Problems after pegging occurred in 68 (50.7%) of 134 patients: discharge in 27 (20.1%), pyogenic granuloma in 24 (17.9%), conjunctiva overgrowing the peg in 4 (3.0%), implant exposure around the sleeve in 5 (3.7%), clicking in 6 (4.5%), peg on an angle in 2 (1.5%), loose sleeve in 1 (0.7%), peg falling out in 18 (13.4%), popping peg in 1 (0.7%), poor transfer of movement in 3 (2.2%), pain with movement in 1 (0.7%), and implant infection in 2 (1.5%). CONCLUSIONS: The Bio-Eye orbital implant represents a porous orbital implant that is biocompatible with orbital tissues and allows fibrovascular ingrowth and improved motility when coupled to the overlying artificial eye. It is more expensive than other commercially available porous orbital implants, such as synthetic FCI3 HA, porous polyethylene (Medpor), and aluminum oxide (Bioceramic) implant. Problems encountered with its use are similar to those problems seen in patients with the synthetic FCI3 hydroxyapatite and aluminum oxide orbital implants.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".