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Record W2039907821 · doi:10.1139/h08-018

A walking intervention improves capillary glucose control in women with gestational diabetes mellitus: a pilot study

2008· article· en· W2039907821 on OpenAlexaffvenue
Margie H. Davenport, Michelle F. Mottola, RUTH MCMANUS, Rob Gratton

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsGestational diabetesMedicineInsulinDiabetes mellitusBody mass indexPregnancyInternal medicineEndocrinologyCohortGestationObstetricsBiology

Abstract

fetched live from OpenAlex

Exercise prescriptions that can be translated into clinical recommendations are clearly needed for women with gestational diabetes mellitus (GDM). A pilot project was developed to document the effectiveness of a structured low-intensity walking protocol on capillary glucose control in GDM women. Ten GDM women followed conventional management of diet and insulin therapy, plus a low-intensity walking program (W) from diagnosis to delivery. Capillary glucose concentrations, insulin requirements, and pregnancy outcomes were compared with a matched cohort by body mass index (BMI), age, and insulin usage (20 GDM women who followed conventional management alone (C)). Baseline capillary glucose concentrations were not significantly different between the W and C groups. The W group had an average acute drop in capillary glucose concentration from pre- to post-exercise of 2.0 mmol x L(-1). In addition, the W group had significantly lower mean glucose concentrations in the fasted state and 1 h after meals than the C group in the week prior to delivery. These lower glucose concentrations were achieved while requiring fewer units of insulin per day (C, 0.50 +/- 0.37 U x kg(-1); W, 0.16 +/- 0.13 U x kg(-1); p < 0.05), injected less frequently. These results suggest an effective role in glucose regulation for this structured walking program.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.508

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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

Citations93
Published2008
Admission routes2
Has abstractyes

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