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Record W2801387696 · doi:10.1007/s00125-018-4613-3

Community-based pre-pregnancy care programme improves pregnancy preparation in women with pregestational diabetes

2018· article· en· W2801387696 on OpenAlexaff
Jennifer M. Yamamoto, Deborah J. Hughes, Mark L. Evans, Karunakaran Vithian, J. David Clark, Nicholas J. Morrish, Gerry Rayman, Peter Winocour, Clare Hambling, Amanda W. Harries, Michael Sampson, Helen Murphy

Bibliographic record

VenueDiabetologia · 2018
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of Calgary
FundersMedical Research CouncilCambridge University HospitalsUniversity of CambridgeNorfolk and Norwich University Hospitals NHS Foundation TrustWellcome TrustDiabetes UKDiabetes Research and Wellness FoundationNational Institute for Health and Care ResearchJuvenile Diabetes Research Foundation United States of America
KeywordsMedicinePregnancyType 2 diabetesGestational diabetesDiabetes mellitusObstetricsFamily medicineGestationEndocrinology

Abstract

fetched live from OpenAlex

Women with diabetes remain at increased risk of adverse pregnancy outcomes associated with poor pregnancy preparation. However, women with type 2 diabetes are less aware of and less likely to access pre-pregnancy care (PPC) compared with women with type 1 diabetes. We developed and evaluated a community-based PPC programme with the aim of improving pregnancy preparation in all women with pregestational diabetes. This was a prospective cohort study comparing pregnancy preparation measures before and during/after the PPC intervention in women with pre-existing diabetes from 1 June 2013 to 28 February 2017. The setting was 422 primary care practices and ten National Health Service specialist antenatal diabetes clinics. A multifaceted approach was taken to engage women with diabetes and community healthcare teams. This included identifying and sending PPC information leaflets to all eligible women, electronic preconception care templates, online education modules and resources, and regional meetings and educational events. Key outcomes were preconception folic acid supplementation, maternal HbA1c level, use of potentially harmful medications at conception and gestational age at first presentation, before and during/after the PPC programme. A total of 306 (73%) primary care practices actively participated in the PPC programme. Primary care databases were used to identify 5075 women with diabetes aged 18–45 years. PPC leaflets were provided to 4558 (89.8%) eligible women. There were 842 consecutive pregnancies in women with diabetes: 502 before and 340 during/after the PPC intervention. During/after the PPC intervention, pregnant women with type 2 diabetes were more likely to achieve target HbA1c levels ≤48 mmol/mol (6.5%) (44.4% of women before vs 58.5% of women during/after PPC intervention; p = 0.016) and to take 5 mg folic acid daily (23.5% and 41.8%; p = 0.001). There was an almost threefold improvement in ‘optimal’ pregnancy preparation in women with type 2 diabetes (5.8% and 15.1%; p = 0.021). Women with type 1 diabetes presented for earlier antenatal care during/after PPC (54.0% vs 67.3% before 8 weeks’ gestation; p = 0.003) with no other changes. A pragmatic community-based PPC programme was associated with clinically relevant improvements in pregnancy preparation in women with type 2 diabetes. To our knowledge, this is the first community-based PPC intervention to improve pregnancy preparation for women with type 2 diabetes. Further details of the data collection methodology, individual clinic data and the full audit reports for healthcare professionals and service users are available from https://digital.nhs.uk/data-and-information/clinical-audits-and-registries/our-clinical-audits-and-registries/national-pregnancy-in-diabetes-audit .

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 score0.185
Threshold uncertainty score0.800

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 head0.021
GPT teacher head0.304
Teacher spread0.283 · 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

Citations54
Published2018
Admission routes1
Has abstractyes

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