Detection of a Case of Cysticercosis of the Breast: A Case Report
Bibliographic record
Abstract
Aims: Cysticercosis is a zoonotic disease caused by encysted larvae of the nematode Taenia solium. It can have variable clinical presentations, neurocysticercosis being the most common among them. Extraneural cysticercosis is relatively rare. Among them, isolated cysticercosis of the breast is extremely rare and medical literature in its entirety describes but a few cases of isolated cysticercosis of the breast. They can be easily mistaken for a fibroadenoma or breast malignancy. This may lead to an undue psychological burden on patients. Hence, properly diagnosing cysticercosis of the breast is essential in alleviating this burden to some extent. We encountered one such case when a patient presented with multiple painless lumps in the right breast. Presentation of Case: A 57-year-old female presented with multiple painless lumps in the right breast. On clinical examination, she was suspected to have numerous small fibroadenomas. She was sent for mammography in which two lesions showed features suggestive of fibroadenoma and the third, of an inflammatory abscess or inflammatory malignancy. She subsequently underwent a core biopsy and the histopathology report revealed that she had cysticercosis of breast. Discussion: Cysticercosis is a parasitic infection caused by the pork tapeworm.This case highlights the rarity and significance of properly diagnosing cysticercosis of breast. Mammography, high-resolution ultrasound or MRI can aid in the diagnosis. Definitive diagnosis is established by histopathological examination. Conclusion: Cysticercosis is a major public health problem, especially in the developing world. It must be given due consideration as a possible differential diagnosis in patients presenting with breast lumps in areas of high prevalence.
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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 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| 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".