Identification of Pediatric Retrocecal Appendicitis Using Point of Care Ultrasound (POCUS)
Bibliographic record
Abstract
Acute appendicitis is the most common pediatric surgical emergency. Diagnosis may be made by targeted point of care ultrasound (POCUS) of the right lower quadrant (RLQ) abdomen. This can be performed by trained emergency physicians and has similar accuracy to ultrasound performed by radiology technologists and interpreted by radiologists (RADUS) [1,2]. Pediatric patients with appendicitis may present without classical clinical signs and symptoms. Retrocecal appendicitis is often diagnosed late at perforation due to the anatomical position limiting diagnosis with ultrasound, despite the high prevalence of retrocecal appendix as an anatomic variation (up to 65%). Given the limited sensitivity for ultrasound in the diagnosis of appendicitis in patients with retrocecal appendix, these patients often undergo advanced imaging with computed tomography (CT) or magnetic resonance imaging (MRI), especially when increased abdominal wall thickness and/or high Body Mass Index (BMI) further limit the ultrasound examination [4-6]. We present a case series of retrocecal appendicitis imaged and diagnosed with POCUS, using novel transducer and patient positioning. In addition to standard graded compression of the RLQ with POCUS, this technique may add to the diagnostic accuracy of patients presenting atypically with anatomic variants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".