Changes in Management Strategies After Spontaneous Migration of a Retained Intraorbital Metallic Foreign Body
Bibliographic record
Abstract
PURPOSE: Because of the controversial biologic tolerance and management, retained intraorbital metallic foreign body (RIMFb) poses a formidable challenge to surgeons. Besides location of the foreign body, indications for surgical management include neurologic injury, mechanical restriction of the eye movement, and development of local infection or draining fistula. The authors describe an unusual case of spontaneous migration of a RIMFb. METHODS: A 26-year-old man had a gunshot injury on the left orbit. The patient was initially managed conservatively because of the posterior position of the bullet fragment. Thereafter, because of the clinical impairments and anterior migration of projectile, surgical treatment was considered. RESULTS: Spontaneous anterior migration has led to mechanical disturbances and inflammatory complications that comprise explicit surgical indications for removal. The patient underwent surgery with complete relief of symptoms. We suppose that extrinsic ocular muscles might play a role in shifting large RIMFb over time, leading to change in the management strategies. CONCLUSIONS: Spontaneous migration of RIMFb is a rare clinical situation that can lead to pain, local deformity, as well as changes in the management strategies of the affected patients even in the late phase of follow-up.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".