Orbital Complications and Cost Analysis of Enucleation by Myoconjunctival versus Conventional Techniques for Retinoblastoma
Bibliographic record
Abstract
Introduction: The aim of the study was to compare complication rates and hospital costs of myoconjunctival versus conventional enucleation techniques in retinoblastoma. Methods: This retrospective cohort and cost analysis reviewed patients with retinoblastoma treated by primary or secondary enucleation between 2003 and 2021 and a minimum 6-month follow-up. Cases were reviewed for three postsurgical complications: chronic conjunctivitis, implant exposure/extrusion, and cellulitis. Cases were excluded if surgery was performed elsewhere or documentation was incomplete. Treatment costs were estimated based on two sample cases billed in 2021 that manifested the studied complications and represented each of the two surgical techniques. Univariate and multivariate analyses were applied to compare complication rates and treatment costs. Results: Included were 180 eyes (179 patients); 239 eyes (227 patients) were excluded. Patients had median age of 18.9 (0–104.4) months at diagnosis, the majority were male (94, 52%), with unilateral (115, 64%) group D or E (163, 91%) eyes. Enucleation was performed by conventional techniques in 107 eyes (59%) and by myoconjunctival approach in 73 (41%). Orbital complications occurred in 61 eyes (34%) during a median follow-up of 7.9 (0.5–33.7) years, more frequently in the conventional technique group (p = 0.014). The myoconjunctival technique had significantly lower costs for implant price (p < 0.001) and estimated treatment cost, including complication management (p < 0.001). Conclusion: Enucleation by myoconjunctival technique showed significantly less complication burden and treatment cost, indicating advantages over conventional approaches. Study limitations include the retrospective nature, confounders’ complexity, and follow-up time variations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".