Tuberculosis the great mimicker: Five unusual cases
Bibliographic record
Abstract
Background: There are wide varieties of clinical manifestations of Tuberculosis (TB). Extrapulmonary tuberculosis (EPTB) patients usually come with an atypical presentation, are difficult to suspect, and frequently involve sites that are very hard to access, and invasive procedures are usually required for diagnosis. We are presenting five cases of atypical presentations of TB here. Case reports: The first case presented acute flaccid paraparesis with right loin pain, ultimately diagnosed as tubercular psoas abscess inducing acute inflammatory demyelinating polyneuropathy. The second case presented with hematemesis, dysphagia, weight loss, and a rare case of esophageal TB was diagnosed. The third case presented with painful multiple bony lytic lesions and was diagnosed as a case of multifocal skeletal TB. The fourth case presented multiple abscesses at different skin sites, leading to a diagnosis of metastatic tubercular abscesses. The fifth case was an elderly female who presented with right hip joint pain, eventually diagnosed as tubercular hip arthritis. Conclusion: EPTB is a great mimicker and has been a challenging medical condition due to the divergence of presentations. High clinical suspicion and vigilance can lead to an early diagnosis and survival of patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".