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Record W3185869533 · doi:10.1177/10935266211033271

Vitelline Vessel Remnant-Derived Funisitis Is a Sensitive and Specific Predictor of Histological Evidence of Amniotic Fluid Infection

2021· article· en· W3185869533 on OpenAlexaff
John Kemuel De Guzman, Weiming Yu, Lawrence de Koning, Christopher Horn, James R. Wright

Bibliographic record

VenuePediatric and Developmental Pathology · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChorioamnionitisMedicineAmniotic fluidPlacentaPathologyUmbilical cordFetusPregnancyAnatomyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: 4-11% of umbilical cords contain vitelline vessel remnants (VVRs). A recent study has described neutrophilic inflammation arising from VVRs and suggested an association with amniotic fluid infection (AFI). METHODS: During routine placental pathology sign-out over a six month period, we identified 70 cords with VVRs. HE-stained sections were re-examined for "VVR-derived funisitis," which was classified as low or high grade/stage based upon whether neutrophils were present only in Wharton's jelly near the VVRs or whether neutrophils were also present near the cord's amniotic surface. The same placentas were also examined for histologic evidence of AFI (maternal response = acute chorionitis or chorioamnionitis vs. fetal response = chorionic vasculitis, umbilical vasculitis, or funisitis vs. both). RESULTS: Neutrophilic inflammation arising from VVRs was present in 54.3% (38/70); 15 and 23 lesions were low and high grade/stage, respectively. "VVR-derived funisitis" was strongly associated with histological evidence of AFI elsewhere in the placenta. Its overall sensitivity and specificity were 0.94 and 0.88; when VVR-derived funisitis was high grade/stage or diagnosed in the third trimester, specificity rose to 1.0. CONCLUSION: "VVR-derived funisitis" has a strong association with histological evidence of AFI.

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 score0.129
Threshold uncertainty score0.391

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 head0.033
GPT teacher head0.274
Teacher spread0.240 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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