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Record W4416344540 · doi:10.24908/pocusj.v10i02.18290

Can a POCUS Clinical Decision Rule Improve Reliability in the Diagnosis of Paediatric Transient Synovitis of the Hip? A Single Centre Pilot Study

2025· article· en· W4416344540 on OpenAlexvenueno aff
David McCreary, C.A. Hamilton

Bibliographic record

VenuePOCUS Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)SynovitisTransient (computer programming)LimpClinical PracticeClinical decision makingMedical diagnosis

Abstract

fetched live from OpenAlex

Objectives: : To describe how POCUS improves diagnostic reliability and reduces the need for further investigations for the child with atraumatic limp. Methods: We retrospectively applied a POCUS CDR to patients presenting to our paediatric emergency department (PED) with atraumatic limp over a 5-year period. This consisted of the following: ages 1 to 10 years old, able to weight bear, no history of fever, symptom duration for 7 days or less, and no pallor, lymphadenopathy, or hepatosplenomegaly. Results: A total of 77 out of 178 patients presenting to the PED with a diagnosis of TS underwent a POCUS examination during their clinical assessment. Of these, 67 patients had hip effusion on POCUS. Our CDR could be applied to correctly rule-in TS in 63 out of 67 patients. Ten patients did not have hip effusion; five of which were diagnosed with another cause for their limp and five were categorized as being possible TS. When POCUS was not utilised as part of clinical assessment, three cases included a misdiagnosis for children presenting with atraumatic limp. Conclusion: Our POCUS CDR could be applied to correctly rule-in TS in a very high proportion of cases. The integration of POCUS into the clinical assessment of children with atraumatic limp can reduce the need for unnecessary investigations while maintaining diagnostic reliability. We recognise that a large prospective study evaluating the role of a POCUS CDR is needed to further evaluate its reliability.

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)0.002
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 score0.078
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.321
Teacher spread0.298 · 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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