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Record W2026019084 · doi:10.1515/jpm.2010.084

Does very advanced maternal age, with or without egg donation, really increase obstetric risk in a large tertiary center?

2010· article· en· W2026019084 on OpenAlexaff
Alon Shrim, Ishai Levin, Angela Mallozzi, Richard Brown, Kareima Salama, Ronni Gamzu, Benny Almog

Bibliographic record

VenueJournal of Perinatal Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineAdvanced maternal ageObstetricsPregnancyGestational ageRespiratory distressDiabetes mellitusPediatricsFetusSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: to assess complications of very advanced maternal age (VAMA) pregnancies ≥ 45 years with and without egg donation (ED). STUDY DESIGN: obstetric and neonatal complications were studied in 20,659 singleton pregnancies according to three maternal age groups: 20-39, 40-44 [advanced maternal age (AMA)] and ≥ 45 years (VAMA). Twenty pregnancies within the AMA/LAMA group that were achieved with ED were compared with age-matched controls. RESULTS: AMA mothers were more likely to have higher rates of preterm deliveries (OR 1.25), cesarean sections (OR 1.84) hypertension (OR 1.71) and diabetes (OR 2.45). Their newborns were more frequently small for gestational age (OR 1.30), and were more likely to have high rates of respiratory distress syndrome (OR 1.66), neonatal intensive care admission (OR 1.40) and perinatal/neonatal mortality (OR 1.83). VAMA pregnancies had >50% cesarean section rate and a high rate of diabetes (OR 2.29), hypertension (OR 1.54) and postpartum hemorrhage (OR 5.38). Congenital anomalies were more common among ED pregnancies. CONCLUSIONS: the higher rate of pregnancy complications for women ≥ 40 years is not further increased after 45 years of age.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.006
GPT teacher head0.269
Teacher spread0.264 · 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

Citations30
Published2010
Admission routes1
Has abstractyes

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