EXTERNAL VERSUS INTERNAL APPROACH TO THE REMOVAL OF METALLIC INTRAOCULAR FOREIGN BODIES
Bibliographic record
Abstract
OBJECTIVE: To review the management of metallic intraocular foreign bodies (IOFB) at a single institution and to compare the use of internal and external approaches for their removal. SUBJECTS AND METHODS: A retrospective review was conducted on 70 eyes from 70 patients who underwent surgical removal of a metallic IOFB with either an internal (vitrectomy followed by forceps or internal magnet use) or external approach (large electromagnet) by seven vitreoretinal surgeons at a single institution between 1973 and 1996. Visual acuity and complications occurring with the two approaches were the main outcome measures studied. RESULTS: Overall, patients showed significant improvement in visual acuity following surgical intervention (P < 0.001) despite widely varying surgical techniques. When the authors compared patients treated with an external versus an internal approach they found no statistically significant difference with regard to visual outcome and a trend toward a higher rate of postoperative endophthalmitis in the external approach group. CONCLUSION: Surgical removal of metallic IOFB results in significant visual improvement. The external approach to the removal of magnetic metallic IOFB remains a viable treatment option in select cases.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".