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Record W1970272154 · doi:10.1210/jcem.85.8.6760

Impact of Time Interval from the Last Meal on Glucose Response to Exercise in Subjects with Type 2 Diabetes<sup>1</sup>

2000· article· en· W1970272154 on OpenAlexafffund
Paul Poirier, Angelo Tremblay, C Catellier, Gilles Tancrède, Caroline Garneau, André Nadeau

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2000
Typearticle
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsCentre hospitalier universitaire de QuébecJewish Rehabilitation HospitalUniversité LavalMontreal Heart Institute
FundersUniversité Laval
KeywordsMealInternal medicineEndocrinologyMedicineType 2 diabetesDiabetes mellitusVO2 maxAnimal scienceHeart rateBlood pressureBiology

Abstract

fetched live from OpenAlex

We evaluate the influence of the time interval from the last meal on the blood glucose response to exercise in men with type 2 diabetes. Nineteen men with type 2 diabetes participated in an exercise training program carried out at 60% of maximal oxygen uptake (VO2peak) for 1 h, 3 times a week. Capillary whole blood glucose was measured immediately before and after each exercise session, and the time interval from the last meal (breakfast, lunch, or dinner) was recorded. Seven time intervals were considered (fasted overnight and 0-1, 1-2, 2-3, 3-4, 4-5, and 5-8 h postmeal). A total of 1,045 exercise sessions were analyzed. There was no change in blood glucose levels when individuals were in the fasted state (mean +/- SE, 8.1 +/- 0.2 vs. 8.1 +/- 0.1 mmol/L; before vs. after, respectively). However, blood glucose decreased by 28 +/- 1% at 0-1 h, by 33 +/- 1% at 1-2 h, by 35 +/- 1% at 2-3 h, by 38 +/- 2% at 3-4 h, by 43 +/- 2% at 4-5 h, and by 23 +/- 3% at 5-8 h (all P < 0.001). These results demonstrate that 1 h of ergocycle exercise has no clinical impact on blood glucose when performed in the fasted state in men with type 2 diabetes, whereas a significant decrease in blood glucose should be expected when the same exercise is performed postprandially.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.369
Teacher spread0.340 · 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

Citations46
Published2000
Admission routes2
Has abstractyes

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