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Record W1942087447 · doi:10.1111/dme.12857

Effects of acute caffeine supplementation on reducing exercise‐associated hypoglycaemia in individuals with Type 1 diabetes mellitus

2015· article· en· W1942087447 on OpenAlexafffund
Dessi P. Zaharieva, Lisa A. Miadovnik, Chip P. Rowan, Robert J. Gumieniak, Veronica Jamnik, Michael C. Riddell

Bibliographic record

VenueDiabetic Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsYork University
FundersMedtronic Canada
KeywordsMedicineBedtimeCaffeineInternal medicineDiabetes mellitusPlaceboEndocrinologyMorningBasal (medicine)Type 2 diabetesVO2 maxIngestionHeart rateBlood pressure

Abstract

fetched live from OpenAlex

AIM: To determine the effects of acute caffeine ingestion on glycaemia during moderate to vigorous intensity aerobic exercise and in recovery in individuals with Type 1 diabetes. METHODS: A total of 13 patients with Type 1 diabetes [eight women, five men: mean ± sd age 25.9 ± 8.8 years, BMI 71.9 ± 11.0 kg, maximal oxygen consumption 46.6 ± 12.7 ml/kg/min, body fat 19.9 ± 7.2%, duration of diabetes 14.4 ± 10.1 years and HbA1c 55 ± 8 mmol/mol (7.4 ± 0.8%)] were recruited. Participants ingested capsules that contained gelatin or pure caffeine (6.0 mg/kg body mass) and performed afternoon exercise for 45 min at 60% maximal oxygen consumption on two separate visits with only circulating basal insulin levels. RESULTS: The main finding was that a single caffeine dose attenuates the drop in glycaemia by 1.8 ± 2.8 mmol/l compared with placebo intake during exercise (P=0.056). Continuous glucose monitoring data, however, showed that caffeine was associated with elevated glycaemia at bedtime after exercise, compared with placebo, but lower glucose concentrations in the early morning the next day. CONCLUSIONS: Caffeine intake should be considered as another strategy that may modestly attenuate hypoglycaemia in individuals with Type 1 diabetes during exercise, but should be taken with precautionary measures as it may increase the risk of late-onset hypoglycaemia.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.150
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.023
GPT teacher head0.315
Teacher spread0.292 · 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

Citations26
Published2015
Admission routes2
Has abstractyes

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