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Record W4401028602 · doi:10.1177/10935266241264161

Umbilical Cord Hemangiomas: A Multi-Institutional Case Series With Literature Review

2024· review· en· W4401028602 on OpenAlexaff
Elizabeth O. Ferreira, Camelia Stefanovici, Stefan Kostadinov, Virginia E. Duncan

Bibliographic record

VenuePediatric and Developmental Pathology · 2024
Typereview
Languageen
FieldMedicine
TopicUrinary and Genital Oncology Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsUmbilical cordMedicineSeries (stratigraphy)PathologyAnatomyBiology

Abstract

fetched live from OpenAlex

Umbilical cord hemangiomas are rare lesions, for which data on pregnancy outcome is lacking. This study combines a multi-institution 4-case series with a systematic literature search (n = 52) to determine possible pathologic lesion parameters which may have an effect on pregnancy outcome. Of all 56 pregnancies, lesion size ranged from 0.2 to 23.0 cm with pregnancy outcomes ranging from healthy liveborns (58.9%), liveborns with severe complications largely due to prematurity and/or fluid overload (12.5%), intrauterine/neonatal demise (25.0%), and pregnancy termination (3.6%). Of the 52 cases included for statistical analysis, there was no significant association between fetal outcome and vascular lesion location ( P = .12) or fetal outcome and single umbilical artery involvement versus involvement of other vasculature ( P = .29). The mean length of vascular lesions that resulted in healthy liveborns did not significantly differ from those resulting in severe fetal complications and/or demise ( P = .72). Cases resulting in severe complications and/or demise were significantly earlier at delivery than those resulting in healthy liveborns ( P < .001). Combined findings suggest that functional lesion characteristics, such as the degree of turbulent flow generated, have more significance than size, especially in early gestation losses. Moving forward, standardized reporting of pathologic lesion characteristics is paramount to better predict pregnancy prognosis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.434
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.344
Teacher spread0.301 · 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.

Study designCase report
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

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