The Role of Point-of-Care Ultrasound in Pilonidal Sinus Disease
Why this work is in the frame
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Bibliographic record
Abstract
Pilonidal sinus is a common problem encountered in proctology clinics. It has a wide spectrum of clinical picture ranging from a single asymptomatic pit to a more complex disease with multiple sinuses and secondary openings. Hence, the treatment options could range from observation or simple excision to a more radical approach like flap surgeries. Ultrasonographic assessment could help in mapping the extent of the pilonidal sinus. It can also identify whether the sinus is infected or has formed an abscess. With the above-mentioned information provided by the point of care ultrasound, the surgeon can tailor the surgical approach to each individual case and improve the overall outcome. In this article, we are highlighting some examples of cases managed in our proctology unit where ultrasound was done preoperatively and guided the management.
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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 | 0.000 |
| 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) | 0.001 | 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 it