The Imaging Features of Nontuberculous Mycobacterial Immune Reconstitution Syndrome
Bibliographic record
Abstract
OBJECTIVE: The purpose was to characterize the spectrum of imaging findings of nontuberculous mycobacterial immune reconstitution syndrome in patients infected with the human immunodeficiency virus. METHODS: A retrospective review of 33 human immunodeficiency virus-infected patients with nontuberculous mycobacterial immune reconstitution syndrome was performed. Radiography, ultrasound, and computed tomography (CT) imaging was reviewed. RESULTS: Intrathoracic and intra-abdominal abnormalities were identified in 16 and 14 patients, respectively. Lymphadenopathy was detected on chest radiographs in 11 patients and on CT in 13. Focal consolidation (n = 8) and centrilobular nodularity (n = 8) were common CT findings. Lymphadenopathy was the predominant abdominal finding (n = 10). Splenomegaly (n = 9), ascites (n = 7), and multiple hypoattenuating splenic lesions (n = 6) were additional findings. Peripheral lymph node masses were detected in 7 patients. CONCLUSIONS: The most common manifestation of nontuberculous mycobacterial immune reconstitution syndrome is lymphadenopathy. Other common findings are pulmonary consolidation and centrilobular nodularity, ascites, splenomegaly, multiple hypoattenuating splenic lesions, and peripheral lymphadenopathy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".