Cervicothoracic Extensive Odontogenic Necrotizing Fasciitis, a Serious Disease:？Cases Reports
Bibliographic record
Abstract
Background: Necrotizing fasciitis is a severe, rapidly progressing infection of soft tissues that spreads along fascial planes, characterized by extensive necrosis and intense systemic signs.While these conditions are rare in developed countries, they unfortunately remain prevalent in our developing nations.We present the follow-up of two cases of cervicothoracic necrotizing fasciitis.Methods: Two patients were followed for cervithoracic necrosis following cellulitis of dental origin.Results: The first case involved a 63-year-old, long-term corticosteroid-treated smoker, admitted for cervicothoracic inflammatory swelling, following dental pain.Explorations concluded with a diagnosis of necrotizing fasciitis, leading to surgical debridement and tooth extraction.The resulting tissue loss initially underwent honey-directed healing and subsequently a split-thickness skin graft.The patient's condition improved favorably.The second case was a 57-year-old poorly managed diabetic female presenting cervicothoracic inflammatory swelling due to dental issues, where necrotizing fasciitis was suspected.Surgical debridement, incision, drainage, and tooth extraction were performed.The resulting tissue loss underwent honeydirected healing with a positive outcome.Conclusions: Necrotizing fasciitis remains widespread, and involvement of the cervicothoracic regions can have a dramatic course.Despite limited resources, the complex management of these cases can yield satisfactory results.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".