Sonographic Features of a Tuberculous Cold Abscess: A Case Report and Literature Review
Bibliographic record
Abstract
The use of point of care ultrasound (POCUS) to aid diagnosis of tuberculosis has been investigated in countries where concomitant endemic prevalence of HIV increases the incidence of extrapulmonary tuberculosis (EPTB). In such cases, using a focused assessment with sonography for HIV-associated tuberculosis (FASH) scan has found to be immensely advantageous as a rapid diagnostic tool in low resource settings where other imaging modalities are scarce. The prevalence of EPTB in immunocompetent patients in industrialised countries is growing. Since EPTB can manifest itself in almost any part of the human body, symptomatic patients present with constitutional and non-specific symptoms. In our case, a 44-year-old male presented to the emergency department (ED) with a 3-month history of left-sided chest pain and swelling of the chest wall. Clinical examination revealed a swollen and tender lump above the left first rib. Palpation of the thoracic (T7) vertebral body demonstrated localised pain. POCUS showed a collection of heterogenous material with fluid content and specks of hyperechoic 'ring-like' structures. Further investigations led to the diagnosis of EPTB. The patient was admitted and treated for EPTB where he went on to make a full recovery. This case report highlights the role of integrating POCUS in clinical examination of patients with suspected EPTB, which can expedite its diagnosis and management.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".