Nontuberculous Mycobacterial Breast Implant Infections
Bibliographic record
Abstract
BACKGROUND: For reasons that are unclear, the incidence of nontuberculous mycobacterial disease is increasing worldwide. Periprosthetic nontuberculous mycobacterial infections following augmentation mammaplasty and breast reconstruction have been reported previously in the form of case reports. METHODS: This retrospective case series examines periprosthetic nontuberculous mycobacterial infections in two western Canadian cities (Edmonton, Alberta, and Vancouver, British Columbia) over a 10-year time period. RESULTS: Ten patients were identified, four of whom had bilateral infections. The most common isolate was Mycobacterium fortuitum. Clinical features were similar to nonmycobacterial periprosthetic infections. The median time to onset of symptoms was 4.5 weeks and the median time to culture an organism was 5.4 weeks. The median duration of antibiotic therapy was 22 weeks. Patients required a mean of three additional operations after diagnosis. Nine patients underwent explantation of the involved implant(s). Reimplantation was performed in six patients a median of 11.5 months after explantation. All cases of reimplantation were successful. CONCLUSIONS: Experience with this postoperative complication is limited, as nontuberculous mycobacteria represent a minority of the pathogens responsible for periprosthetic infections. In the absence of specific features with which to identify patients at risk, the surgeon must be aware of the possibility of this infection. To achieve earlier diagnosis, the clinician should have a high index of suspicion in a patient with delayed onset of symptoms, negative preliminary cultures, and a periprosthetic infection that fails to resolve following a course of conventional antimicrobial treatment. With appropriate treatment, nontuberculous mycobacterial periprosthetic infections can be managed successfully.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".