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Record W4389886769 · doi:10.1139/apnm-2023-0266

A very low carbohydrate diet for minimising blood glucose excursions during ultra-endurance open-water swimming in type 1 diabetes: a case report

2023· article· en· W4389886769 on OpenAlexaffvenue
S Smee, Rebecca Johnson, Amy Rush, Raymond J. Davey

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2023
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsJuvenile Diabetes Research Foundation
Fundersnot available
KeywordsCarbohydrateMedicineType 1 diabetesDiabetes mellitusType 2 diabetesContinuous glucose monitoringLow carbohydrateEndocrinologyInternal medicinePhysiologyPhysical therapyIntensive care medicineObesityWeight loss

Abstract

fetched live from OpenAlex

Carbohydrate-restricted diets are used by people with type 1 diabetes (T1D) to help manage their condition. However, the impact of this strategy on blood glucose responses to exercise is unknown. This study describes the nutritional strategies of an athlete with T1D, who follows a very low carbohydrate diet to manage her condition during an ultra-endurance open-water swimming event. The athlete completed the 19.7 km distance in 6 h 43 min. She experienced minimal disruptions to glycaemia, reduced need for supplemental carbohydrate, and no episodes of symptomatic hypoglycaemia. This case report will hopefully encourage further experimental studies that inform and expand current clinical practice guidelines.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.276
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations1
Published2023
Admission routes2
Has abstractyes

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