Multiple cutaneous fistula after titanium dental implant: A case report
Bibliographic record
Abstract
BACKGROUND: Dental implants allow functional and aesthetic reestablishment. Titanium (Ti) implants emerge as the preferred choice because Ti is considered an inert material, highly resistant to corrosion. However, virtually no material can be considered universally biocompatible and this includes titanium. PURPOSE: To report an unusual presentation of inflammatory reaction after a Ti dental implant. MATERIALS AND METHODS: The patient presented to a dermatology clinic to evaluate lesions on her face. She reported the placement of dental implants 2 years earlier, one of which evolved with inflammatory signs and instability a few days after the procedure. As anti-inflammatory and antibiotic therapy were fruitless, after 3 months the implant was removed, but the inflammation persisted. On physical examination, painful erythematous-papule-nodular lesions were found on the left mandibular and submandibular region. RESULTS: Culture tests for microorganisms were negative and histopathological examination revealed a chronic fistula with a foreign body reaction. Using X-ray fluorescence, Ti particles were found along the fistula wall. CONCLUSIONS: Professionals should be aware of complications arising from dental implants, including Ti implants. Detailed anamnesis and laboratory investigation can assure diagnosis for specific therapeutic approaches.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".