Sputum Smear and Culture-negative Tuberculosis with Associated Pleural Effusion: A Diagnostic Challenge
Bibliographic record
Abstract
Tuberculosis (TB) is an important cause of morbidity and mortality in the United States. Due to the unpredictable or nonspecific nature of its clinical presentations, TB can be a diagnostic challenge for physicians. In 2013, 23% of reported TB cases were culture-negative in the United States; in New York City, this was approximately 27%. The increasing number of sputum smear- and culture-negative TB patients is a serious concern because misdiagnosis and delayed treatment can lead to increased morbidity and mortality and increased infectious transmission. We report a case of a 26-year-old-female recent immigrant, who was initially managed for community-acquired pneumonia but was later found to have TB with complicated pleural effusion, despite having multiple smear- and culture-negative sputum specimens, Xpert Mycobacterium tuberculosis (MTB)/resistance to rifampin (RIF) assay (real-time polymerase chain reaction (PCR)) and pleural fluid analysis. She improved clinically on anti-tuberculosis therapy and, later, the diagnosis was confirmed by pleural biopsy.
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 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 | 0.005 |
| 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".