Medical Management for the Treatment of Nontuberculous Mycobacteria Infection of the Parotid Gland: Avoiding Surgery May Be Possible
Bibliographic record
Abstract
Infection with nontuberculous mycobacteria (NTM) is uncommon in the head and neck; therefore there is no clear consensus on treating these infections. Our objective was to report our experience with a unique case of NTM infection of the parotid in an immunocompetent patient, in order to determine appropriate management through our experience with this pathology. A 57-year-old man, known for numerous comorbid diseases, presented to our institution complaining of right parotid swelling and pain. A computed tomography (CT) of the neck showed a multiloculated collection in the inferior portion of the right parotid gland, compatible with abscess formation. This abscess was drained by interventional radiology (IR) but required repeat drainage twice due to lack of initial improvement. He was treated with several antibiotics as culture results initially indicated Gram-positive bacilli and then Mycobacterium species, with final identification by a reference laboratory as Mycobacterium abscessus. Imipenem was initiated with amikacin and clarithromycin. His infection clinically and radiologically resolved after 5 months of antibiotherapy. In our case, the patient improved following intravenous antibiotic therapy. Our experience demonstrates that appropriate antibiotherapy can lead to resolution of Mycobacterium abscessus infection in the parotid without the risks associated with surgical intervention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".