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Record W3159594340 · doi:10.24908/pocus.v6i1.14760

Surgeon Performed Ultrasound for Diagnosis of Intussusception - A Pilot Study

2021· article· en· W3159594340 on OpenAlexvenueno aff
Soundappan SV Soundappan, Albert Lam, Lawrence Lam, Danny Cass, A.J.A. Holland, Jonathan Karpelowsky

Bibliographic record

VenuePOCUS Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntussusception (medical disorder)UltrasoundEmergency departmentRadiologySurgeryNursing

Abstract

fetched live from OpenAlex

Aim: To study the diagnostic accuracy of surgeon performed ultrasound (SPU) in the diagnosis of children presenting with clinical suspicion of intussusception to a tertiary paediatric facility in NSW, Australia. Methods: Children under the age of 16 presenting to the emergency department with clinical features suggestive of intussusception were recruited. After obtaining consent SPU was performed by a Paediatric surgeon. All patients subsequently had an ultrasound performed in radiology department (RPU) on which management was based. Diagnosis and images of SPU were reviewed by an independent radiologist blinded to results of the formal study. Results: Of 7 children enrolled 5 were male. Age ranged from 3 months to 7 years (mean 2.64, SD 2.282), weight from 5.2kgs to 25.2kgs (mean 13.69, SD 6.721). Five out of the 7 children presented during day hours i.e. 8a.m.-5 p.m. (mean 12.72, SD 4.049). Mean time to SPU was 6.3 hours (SD7.1) and RPU was 8.3 hours (SD 7.6). SPU was earlier by 2 hours and correlation between SPU and RPU was 100 percent. Conclusion: SPU for intussusception can be performed early and accurately. Surgeons should train and use ultrasound as a reliable tool in evaluating the child with suspected intussusception.

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)0.001
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 score0.012
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.043
GPT teacher head0.311
Teacher spread0.268 · 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
Published2021
Admission routes1
Has abstractyes

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