Bilateral Hydrocele of the Canal of Nuck in an Adult Female: A Case Report
Bibliographic record
Abstract
Bilateral hydrocele of the canal of Nuck (HCN) is very rare, in adult females. Primary care physicians can misdiagnose this pathology without diagnostic imaging. A 37-year-old female complained of right lower quadrant (RLQ) pain, for a few months, reported to the emergency room. A non-reducible bulging protrusion was visualized in the RLQ. After performing the necessary blood work, the emergency physician ordered an emergent sonogram and computed tomography (CT). A transvaginal sonogram was performed to exclude gross adnexal masses, in the RLQ. An HCN canal was suspected in the right inguinal region. A non-contrast CT demonstrated a bilateral HCN, with the left significantly smaller than the right. In this case, a bilateral surgical excision of the hydrocele was recommended. Owing to the recurrence of the HCN, a cyst aspiration was not suggested. Physicians should consider the diagnosis of HCN in any female presenting with inguinolabial swelling. Sonography, CT, and magnetic resonance imaging (MRI) are the three diagnostic imaging techniques commonly used to diagnose this pathology. A multimodality approach is sometimes necessary when the sonography diagnosis is no definitve.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".