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Record W2148488543 · doi:10.5489/cuaj.2833

Isolated penile torsion in newborns

2015· article· en· W2148488543 on OpenAlexvenueno aff
Egemen Eroğlu, Gökhan Gündoğdu

Bibliographic record

VenueCanadian Urological Association Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicUrological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsTorsion (gastropod)MedicineTesticular torsionAnatomySurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: We reported on the incidence of isolated penile torsion among our healthy children and our approach to this anomaly. METHODS: Between 2011 and 2014, newborn babies with penile torsion were classified according to the angle of torsion. Surgical correction (penile degloving and reattachment for moderate cases and dorsal dartos flap technique in case of resistance) after 6 months was advised to the babies with rotations more than 45°. RESULTS: Among 1000 newborn babies, 200 isolated penile torsions were found, and among these, 43 had torsions more than 45°, and 4 of these had angles greater than 90°. The mean angle of the rotations was found 30.45° (median: 20°). In total, 8 children with 60° torsions were previously circumcised. Surgery was performed on 19 patients, with a mean patient age of 12 ± 2 months. Of these 19, 13 babies were corrected with degloving and reattachment. This technique was not enough on the remaining 6 patients; therefore, derotational dorsal dartos flap was added to correct the torsion. After a mean of 15.6 ± 9.8 months, residual penile rotation, less than 15°, was found only in 2 children. CONCLUSION: The incidence of isolated penile torsion is 20% in newborns. However, rotation more than 45° angles are seen in 4.3% of male babies. Correction is not necessary in mild degrees, and penile degloving with reattachment is enough in most cases. If the initial correction is insufficient, dorsal dartos flap rotation is easy and effective. Prior circumcision neither disturbs the operative procedure nor affects the outcomes.

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 score0.065
Threshold uncertainty score0.678

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)0.0010.000

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

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