MétaCan
Menu
Back to cohort
Record W4387515852 · doi:10.1177/10935266231195750

Skeletal Growth Arrest Lines in Fetal Remains: Histopathology and Correlative Placental Pathology

2023· article· en· W4387515852 on OpenAlexaff
Tsz Wing Chu, Patrick Shannon, Tony Parks

Bibliographic record

VenuePediatric and Developmental Pathology · 2023
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsHistopathologyCorrelativePathologyFetusMedicineFetal growthBiologyPregnancy

Abstract

fetched live from OpenAlex

INTRODUCTION: Skeletal growth arrest lines (GAL) are transverse lines of metaphyseal radiodensity accompanying episodic severe physiological stress. They are poorly described in fetal remains. MATERIALS AND METHODS: We searched our autopsy practice for instances of fetal GAL in post mortem radiology, and correlated them with long bone histology and placental pathology. We describe the appearance, distribution, and pathology of GAL in a cohort of fetal autopsies, and compare the placental pathology accompanying GAL to the placental pathology of asymmetrical growth restriction (AGR) in the same time period. RESULTS: In 2108 consecutive fetal post mortems, we found 20 cases with GAL. About 16 were in singletons with AGR. In these 16, the distribution of placental pathologies was similar to a contemporaneous cohort of 113 cases with AGR. Of the remaining 4, two twins out of 9 sets of monochorionic twins with AGR demonstrated GAL. One case of GAL had symmetrical growth restriction with cytomegalovirus infection, and one case had no AGR and an old, unexplained retroplacental hemorrhage. On histology, GAL are characterized by a region of mineralized chondroid, which is variably incorporated into irregular trabecular bone. DISCUSSION: GALs accompany a variety of placental pathologies and twin-twin transfusion, suggesting episodic disease progression.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePediatric and Developmental PathologySame topicPregnancy and preeclampsia studiesFrench-language works237,207