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Record W2985728425 · doi:10.2337/dc19-1908

Dietary Patterns of Insulin Pump and Multiple Daily Injection Users During Type 1 Diabetes Pregnancy

2019· letter· en· W2985728425 on OpenAlexafffund
Sandra Neoh, Jennifer M. Yamamoto, Denice S. Feig, Helen Murphy, Jeannie Grisoni, Carolyn Byrne, Katy Davenport, Lois Donovan, Claire Gougeon, Carolyn Oldford, Catherine A. Young, Stephanie A. Amiel, Katharine F. Hunt, Louisa Green, Helen Rogers, Benedetta Rossi, Barbara Cleave, Michelle Strom, Alberto de Leiva, Juan M. Adelantado, Ana Chico, Diana Tundidor, Janine Malcolm, Kathy Henry, Damian Morris, Gerry Rayman, Duncan Fowler, Susan L. Mitchell, Josephine Rosier, Rosemary Temple, Jeremy Turner, Gioia Canciani, Niranjala Hewapathirana, Leanne Piper, Ruth McManus, Anne Kudirka, Margaret Watson, Matteo Bonomo, Basilio Pintaudi, Federico Bertuzzi, Giuseppina Daniela Corica, Elena Mion, Julia Lowe, Ilana Halperin, Anna Rogowsky, Sapida Adib, Robert S. Lindsay, David Carty, Isobel Crawford, Fiona Mackenzie, Therese McSorley, John N. Booth, Natalia McInnes, Ada Smith, Irene Stanton, Tracy Tazzeo, John Weisnagel, Peter Mansell, Nia Jones, Gayna Babington, Dawn Spick, Malcolm MacDougall, Sharon Chilton, Terri Cutts, Michelle Perkins, Eleanor Scott, Del Endersby, Anna R. Dover, Frances Dougherty, Susan Johnston, Simon Heller, Peter Novodorsky, Sue Hudson, Chloe Nisbet, Thomas Ransom, Jillian Coolen, Darlene Baxendale, Richard I. G. Holt, Jane Forbes, Nicki Martin, Fiona Walbridge, Fidelma Dunne, Sharon Conway, Aoife M. Egan, Collette Kirwin, Michael Maresh, Gretta Kearney, Juliet Morris, Susan J. Quinn, Rudy Bilous, Rasha Mukhtar, Ariane Godbout, Sylvie Daigle, Alexandra Lubina Solomon, Margaret Jackson, Emma Paul, Julie Taylor, Robyn L. Houlden, Adriana Breen, Anita Banerjee, Anna Brackenridge, Annette Briley, Anna Reid, Claire Singh, Jill Newstead-Angel, J. Baxter, Sam Philip, Martyna Chlost, Lynne Murray, Kristin Castorino, Lois Jovanovič, Donna Frase, Sonya Mergler, Kathryn Mangoff, Johanna Sanchez, Gail Klein, Katrina J. Ruedy, Craig Kollman, Olivia Lou, Marlon Pragnell

Bibliographic record

VenueDiabetes Care · 2019
Typeletter
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of TorontoMount Sinai HospitalAlberta Children's HospitalLunenfeld-Tanenbaum Research InstituteUniversity of Calgary
FundersBreakthrough T1D CanadaNational Institute for Health and Care Research
KeywordsMedicineInsulin pumpPregnancyGlycemicType 1 diabetesInsulinDiabetes mellitusType 2 diabetesRandomized controlled trialInternal medicineObstetricsEndocrinology

Abstract

fetched live from OpenAlex

Insulin pump therapy offers theoretical advantages over multiple daily injections (MDI) for fine-tuning insulin dose adjustment. However, evidence regarding the effectiveness of pump compared with MDI on glycemic control during pregnancy is conflicting. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) was a randomized trial of continuous glucose monitoring (CGM) before and during pregnancy (1). A secondary analysis found that pregnant women using pumps had suboptimal midgestation glycemic control compared with women using MDI (2). CGM measures demonstrated comparable time in range (TIR) 63–140 mg/dL at 12 and 34 weeks but 5% lower TIR in pump users at 24 weeks (48% vs. 53%), meaning that pump users spent, on average, 1 h 15 min per day less time in the glucose target range. There are several potential explanations for this, including baseline differences in women using pump or MDI, differences in insulin dose adjustment, and differences in dietary intake. Women using pumps have more dietary flexibility with no additional injections required for snacks. Through the use of prospectively collected dietary data from U.K. and Irish CONCEPTT participants, our objective was to examine the dietary patterns of women using insulin pumps and MDI during pregnancy. Details of the main CONCEPTT, pump versus MDI, and diet studies were previously published (1–3). All U.K. participants ( n = 113) were invited to participate in the CONCEPTT diet …

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.247
Teacher spread0.229 · 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

Citations17
Published2019
Admission routes2
Has abstractyes

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