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Record W2326955026 · doi:10.1177/1753495x14528487

Clinical predictors for diabetes screening in the first year postpartum after gestational diabetes

2014· article· en· W2326955026 on OpenAlexafffund
Patricia Peticca, Baiju R. Shah, Alison K. Shea, Heather D. Clark, Janine Malcolm, Mark Walker, Alan Karovitch, Pauline Brazeau-Gravelle

Bibliographic record

VenueObstetric Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoSunnybrook Health Science CentreHealth Sciences CentreOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative SciencesCanadian Diabetes Association
KeywordsMedicineGestational diabetesDiabetes mellitusObstetricsPregnancyDiabetes in pregnancyPostpartum periodOutpatient clinicPrenatal careGestationInternal medicinePopulationEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Postpartum screening for diabetes in women with gestational diabetes (GDM) improves with use of reminder systems. Our primary objective was to identify predictors of diabetes screening in the first year after delivery. METHODS: A retrospective study was performed of 556 women with GDM who received outpatient prenatal care between 2007 and 2009. A mailed reminder system was utilized at two sites. Rates of postpartum glucose testing at 6 and 12 months postpartum were measured. RESULTS: Site of care and non-smoking status were identified as the only predictors of postpartum diabetes screening (p<0.001 and p = 0.02, respectively). Rates of OGTT completion at one year (38% vs. 19% p<0.001) were higher in women who attended clinics with postpartum reminders. CONCLUSIONS: The site of diabetes care in pregnancy is a major predictor of adherence to diabetes screening postpartum. Health care delivery should be considered in the development of strategies to increase screening rates.

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 score0.077
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
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.318
Teacher spread0.288 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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