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Record W4410122211 · doi:10.24908/pocusj.v10i01.17744

Identification of Pediatric Retrocecal Appendicitis Using Point of Care Ultrasound (POCUS)

2025· article· en· W4410122211 on OpenAlexvenueno aff
Carl Kaplan, Raizada Vaid, Michael Secko

Bibliographic record

VenuePOCUS Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsAppendicitisMedicineRadiologyUltrasoundAppendixPerforationAbdomenMagnetic resonance imagingPoint of care ultrasoundGeneral surgery

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.304
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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