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Record W1978129913 · doi:10.1002/pd.2409

Assessing the role of placental trisomy in preeclampsia and intrauterine growth restriction

2009· article· en· W1978129913 on OpenAlexafffund
Wendy P. Robinson, Maria S. Peñaherrera, Ruby Jiang, Luana Avila, Jennifer L. Sloan, Deborah E. McFadden, Sylvie Langlois, Peter von Dadelszen

Bibliographic record

VenuePrenatal Diagnosis · 2009
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsTrisomyIntrauterine growth restrictionPreeclampsiaObstetricsPlacentaAneuploidyPregnancyBiologyFetusMedicineGynecologyAndrologyGeneticsChromosomeGene

Abstract

fetched live from OpenAlex

OBJECTIVE: Prenatally diagnosed confined placental trisomy is associated with increased risk for intrauterine growth restriction (IUGR) and preeclampsia. However, it is unclear how often this might underlie pregnancy complications. Our objective was to evaluate the frequency and distribution of trisomic cells in placentae ascertained for IUGR and/or preeclampsia. METHOD: Comparative genomic hybridization was applied to two uncultured biopsies from each of 61 placentae referred with maternal preeclampsia and/or IUGR, 11 cases with elevated maternal serum hCG and/or AFP but no IUGR or preeclampsia, and 85 control placentae. RESULTS: Trisomy was observed in four placentae among the IUGR group (N = 43) but in no case of preeclampsia in the absence of IUGR (N = 18). Trisomy was observed in 1 of the 11 cases ascertained for abnormal maternal serum screen. Each of these five cases was mosaic and not all sampled sites showed the presence of trisomy. None of the 84 control placentas showed mosaic trisomy, although 1 case of nonmosaic 47,XXX was identified in this group. CONCLUSION: In cases in which diagnosis of the cause of IUGR may provide some benefit, testing should be performed using uncultured cells from multiple placental biopsies for the accurate diagnosis of trisomy mosaicism.

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 score0.082
Threshold uncertainty score0.338

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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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

Citations92
Published2009
Admission routes2
Has abstractyes

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