Necrotizing fasciitis of the head and neck: Surgical follow up of 2 cases with the use of LRINEC score
Bibliographic record
Abstract
Abstract Necrotizing fasciitis of the head and neck is a rare, rapidly progressive infection involving the skin, subcutaneous tissue and fascia. We report two cases that presented at the otolaryngology department at our institute in 2016. Both patients presented with a history of diabetes and according to the LRINEC score they both showed a moderate risk of having the disease. LRINEC is a valuable tool in both diagnosing the case and can be used to follow up the case, as the first case showed a decrease in score during her stay in the hospital, the second case showed an increase in score. We advocate the importance of early detection, eradicating the source of infection followed by frequent, meticulous wound dressing and strict blood sugar control to obtain better outcomes in managing necrotizing fasciitis of the head and neck. Highlights
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".