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Record W4404446170 · doi:10.24908/pocus.v9i2.17451

Rare Cause of Pediatric Abdominal Pain Diagnosed on Point of Care Ultrasound (POCUS)

2024· article· en· W4404446170 on OpenAlexvenueno aff
C.M. Owens, Lindsey

Bibliographic record

VenuePOCUS Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiologyAbdomenHydronephrosisEmergency departmentAbdominal painDifferential diagnosisMagnetic resonance imagingRenal colicPelvisAppendicitisUltrasoundVaginaUrinary systemSurgeryAnatomyPathology

Abstract

fetched live from OpenAlex

An 11-year-old postmenarchal female presented to the pediatric emergency department (ED) with 2 days of periumbilical and right lower abdominal pain. Radiology-performed ultrasound (RADUS) did not visualize the appendix, and there was a plan for surgical consultation to decide between serial abdominal exams versus computed tomography (CT) scan. While awaiting consultation and to help further narrow the differential diagnosis, the emergency provider performed a point of care ultrasound (POCUS) of the urinary tract. This revealed several anomalies including a solitary left kidney with hydronephrosis, and a well-circumscribed, fluid-filled structure with mixed echogenicity posterior to the bladder and inferior to the uterus. Given these findings on POCUS, further imaging was pursued, including a RADUS of the pelvis followed by a magnetic resonance imaging (MRI) of the abdomen. Further imaging ultimately diagnosed a bicornuate uterus, septate vagina with hematocolpos and solitary left kidney consistent with Obstructed Hemivagina and Ipsilateral Renal Anomaly (OHVIRA) syndrome. This case is an illustration of how POCUS is an invaluable tool to narrow the differential diagnosis and guide advanced imaging or consultation for both common and rare causes of pediatric abdominal pain.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.280
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2024
Admission routes1
Has abstractyes

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