Abscess Formation as a Complication of Injectable Fillers
Bibliographic record
Abstract
Importance: Dermal filler use in aesthetic clinics, are now widespread and although complications are rare, the formation of granulomas or abscesses and subsequent defects can be devastating to the patient. Design: Retrospective chart review of 4 cases over the period of 10 years, from 2002-2012 were examined from The Nasal and Facial Plastic Cosmetic Surgery Institute. Results: Four female patients experienced delayed onset reactions (>2 weeks) with sterile abscess formation and eventual resolution with serial drainage and macrolide antibiotics were observed over a prolonged period until resolution occurred. Only 1 case identified an organism (streptococci) on culture after 8 months, however, the initial culture still showed only sterile abscess. All 4 had a history of previous injectable fillers, 2 patients had evidence of pre existing autoimmune disorders. Conclusions and Relevance: Since the treatment of all of these patients, there is new evidence that infections may present as delayed onset sterile abscesses due to biofilm formation. Fluorescent in situ hybridization (FISH) test has shown to be as specific in identifying responsible organisms in biofilm infections as simple culture but is more sensitive; thus preventing misdiagnosis of sterile abscess. Counter intuitively steroid injection may promote abscesses, while hyaluronidase may be useful.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".