Mixed nontuberculous mycobacteria in an immunocompromised patient with probable progressive multifocal leukoencephalopathy
Bibliographic record
Abstract
• Concurrent pulmonary and disseminated nontuberculous mycobacteria (NTM) disease can involve multiple species. • Line probe assays may fail to detect NTM mixtures from pulmonary specimen cultures. • Mixed NTM infections can be either pathogenic or non-pathogenic. • Multi-target amplicon sequencing is better for detecting NTM mixtures. • Dual NTM treatment is complex, requiring a personalized regimen and expert input. Nontuberculous mycobacteria (NTM) are increasingly recognized opportunistic pathogens found ubiquitously in the environment. The presence of multiple NTM species at the site of disease complicates diagnosis and treatment. A 40-year-old patient who tested positive for HIV, with an absolute clusters of differentiation 4+ T-cell count of 3 cells/µl and cryptococcaemia, presented with hemoptysis, productive cough, and weight loss. Mixed NTM species, including Mycobacterium kansasii and Mycobacterium chelonae, were detected by the GenoType Mycobacterium Common Mycobacteria line probe assay from respiratory specimens, with Mycobacterium avium bacteremia also identified in the same month. An empirical regimen of azithromycin, ethambutol, isoniazid, and rifabutin was initiated to address recurrent positive cultures with M. kansasii and the NTM bacteremia. Despite this treatment, the patient experienced neurologic deterioration, was diagnosed with probable progressive multifocal leukoencephalopathy, and subsequently died. Advanced diagnostic techniques, including Sanger sequencing, Deeplex Myc-TB in combination with short-read next-generation sequencing, and targeted amplicon-based Oxford Nanopore Technologies long-read sequencing, revealed the presence of mixed NTM species in two retrospective stored cultures, with variations in primer binding affinity among the M. kansasii and M. avium . This case highlights the individualized considerations required to manage a patient with mixed NTM infection and the need for multi-target diagnostic approaches.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".