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Record W2019330641 · doi:10.1016/s0029-7844(00)01208-4

Rescue by birth: defective placental maturation and late fetal mortality

2001· article· en· W2019330641 on OpenAlexaff
Thomas Stallmach

Bibliographic record

VenueObstetrics and Gynecology · 2001
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineFetusPlacentaPregnancyPopulationObstetricsGestationIncidence (geometry)ParenchymaGynecologyAndrologyPathologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To estimate the incidence and lethality of placental maturation defect, and to determine the impact of the pattern of placental dysfunction on the risk of recurrent stillbirth or maternal disease in later life. METHODS: Questionnaire and archival analysis of fetal deaths from placental dysfunction at 32-42 weeks (1975-1995 in Zurich), classified as chronic (parenchyma loss) or acute (maturation defect of the terminal chorionic villi). Population survey of 17,415 consecutive unselected singleton placentas (1994-1998 in Berlin). RESULTS: Of the 71 stillbirths, 34 were due to parenchyma loss and 37 to maturation defect. Parenchyma loss predominated in the first pregnancy (73.5% compared with 43.2%; P <.05). The risks of recurrent stillbirth and subsequent childlessness did not differ between the two groups. Eleven percent of mothers whose placenta had maturation defect had diabetes in the index pregnancy; none of the other women in the group developed diabetes over the 5-20-year observation period. In the population survey, incidence of maturation defect was 5.7%, and was associated with fetal death in 2.3% of cases. Normal placentas were associated with fetal death in 0.033%. CONCLUSION: Placental maturation defect can be a cause of fetal hypoxia. Although the risk of stillbirth is 70-fold that of a normal placenta, few affected fetuses actually die. The risk of recurrent stillbirth is tenfold above baseline and occurs mostly after 35 weeks' gestation.

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 score0.034
Threshold uncertainty score0.367

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)0.0000.000

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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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

Citations126
Published2001
Admission routes1
Has abstractyes

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