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Record W2102525801 · doi:10.5489/cuaj.1027

Investigation and management of antenatally detected hydronephrosis

2013· article· en· W2102525801 on OpenAlexaffvenueabout
Karen Psooy, John Pike

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsChildren's Hospital of Eastern OntarioChildren's Hospital of Winnipeg
Fundersnot available
KeywordsHydronephrosisMedicineInternal medicineUrinary system

Abstract

fetched live from OpenAlex

All ANH should be investigated with a post-natal RUS.2 Level 1 Evidence: Grade A Recommendation The role of prophylactic antibiotics initiated at birth is controversial. Grade D Recommendation The need to further investigate mild postnatal hydronephrosis (SFU 0–II) with a VCUG is controversial, and depends on the physician’s attitude toward diagnosing asymptomatic VUR. Grade D Recommendation The need to reassess mild postnatal hydronephrosis with a second RUS is unclear, but does provide reassurance to the physician and parent if the ANH remains stable or improves. Level 4 Evidence: Grade C Recommendation Persistent moderate or severe hydronephrosis (SFU III–IV) should be investigated with a VCUG, followed by diuretic renography if the hydronephrosis cannot be explained by VUR.1 Level 4 Evidence: Grade C Recommendation A summary flow chart is provided (Fig. 1). To assist in the decision-making of controversial areas, members of the Pediatric Urologists of Canada were surveyed in 2007 to determine most common practice patterns. The results, based on the responses of 15 Canadian members, are included in the flow chart. Fig 1 Summary flow chart of Levels of Evidence and Grade recommendations for evaluating antenatal hydronephrosis. *93% would not order a voiding cystourethrogram (VCUG) if Society of Fetal Urology (SFU) 0; 80% would not order a VCUG for SFU I; 73% would order ... Footnotes This article has been peer reviewed. Competing interests: None declared.

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 score0.019
Threshold uncertainty score0.266

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 head0.012
GPT teacher head0.199
Teacher spread0.188 · 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

Citations43
Published2013
Admission routes3
Has abstractyes

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