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The reproductive health of daughters of pregestational diabetic women: Medical Birth Registry of Norway

2002· article· en· W1970863256 on OpenAlexaff
Grace M. Egeland, Rolv Skjærven, Lorentz M. Irgens

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2002
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineDiabetes mellitusObstetricsPregnancyDemographySingletonDaughterReproductive healthPopulationEndocrinologyEnvironmental health

Abstract

fetched live from OpenAlex

Maternal diabetes may have an impact upon a daughter's reproductive health through genetic influences, an altered fetal metabolic environment or both. We examined the reproductive health of daughters of diabetic women using linked generation data from the Medical Birth Registry of Norway. Among all female births between 1967 and 1982 (n = 459182), 739 had a mother with registered pregestational diabetes, a rate of 1.6 per 1000 deliveries. A total of 142904 daughters delivered at least one child by 1998. After taking into account differences in survival, we observed no differences in the percentage of childbearing and in the average number of children born by 1998 between daughters with and without a diabetic mother in age-stratified analyses. In analyses limited to singleton deliveries and stratified by mothers' and daughters' diabetic status, we found a threefold excess stillbirth delivery rate among women who had either a mother with pregestational diabetes (2.6%) or pregestational diabetes themselves (2.6%) compared with the stillbirth delivery rate observed in non-diabetic women with no maternal history of diabetes (0.8%). These findings were unaltered in multivariable analyses adjusting for daughters' maternal age and registered obstetric risk factors. Our results indicate that pregestational diabetes remains a health care challenge in Norway and that further evaluation of the reproductive health of daughters of diabetic pregnancies is warranted.

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.315
Teacher spread0.287 · 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

Citations8
Published2002
Admission routes1
Has abstractyes

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