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Record W2023621375 · doi:10.1097/mej.0000000000000158

The accuracy of renal point of care ultrasound to detect hydronephrosis in children with a urinary tract infection

2014· article· en· W2023621375 on OpenAlexaff
Romain Guedj, Simon Escoda, P. Blakime, G. Patteau, Françis Brunelle, G. Chéron

Bibliographic record

VenueEuropean Journal of Emergency Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMedicineHydronephrosisRenal pelvisConfidence intervalUltrasonographyUrinary systemEmergency departmentUltrasoundEchogenicityUrologyRadiologyInternal medicine

Abstract

fetched live from OpenAlex

The objective of this study was to investigate the accuracy of renal point of care ultrasound (POCUS) for the detection of hydronephrosis in children with a urinary tract infection (UTI). We prospectively included all patients with a final diagnosis of UTI who visited our pediatric emergency department between November 2009 and April 2011. Emergency physicians were encouraged to perform a renal POCUS during these visits, and a follow-up renal ultrasonography was performed by a radiologist who was blinded to the results of POCUS. We calculated the accuracy of POCUS to detect hydronephrosis (renal pelvis enlargement ≥10 mm). We included 433 UTI visits, and 382 (88.2%) POCUS were performed. The sensitivity and the specificity were 76.5% (95% confidence interval: 58.1-94.6%) and 97.2% (95.2-99.2%), respectively. The positive and the negative predictive values were 59.1% (36.4-79.3%) and 98.8% (97.7-99.9%), respectively. Renal POCUS might be used to rule out hydronephrosis in pediatric UTI.

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)0.002
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 score0.019
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.015
GPT teacher head0.277
Teacher spread0.262 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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