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Record W4220888068 · doi:10.1016/j.ajmo.2022.100011

Peak performance: Putting type 1 diabetes management recommendations for athletes to the test

2022· article· en· W4220888068 on OpenAlexaffabout
Bradley Grightmire, Wajd Alkabbani, John‐Michael Gamble

Bibliographic record

VenueAmerican Journal of Medicine Open · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAthletesType 2 diabetesTest (biology)Physical therapyPsychologyMedicineDiabetes mellitusBiologyEndocrinology

Abstract

fetched live from OpenAlex

Background: Athletes with type 1 diabetes (T1D) face unique challenges to maintain optimal glucose levels and therefore require tailored guidance from their healthcare providers. Herein, we aim to summarize and compare recommendations targeted at T1D management in athletes in commonly used clinical practice guidelines and topical position statements. The objective is to assess if the available recommendations are comprehensive enough for athletes to apply to high-performance sport. Methods: From seven clinical practice guidelines and positions statements, we identified recommendations relevant to athletes with T1D, based on a specific hierarchy. For included recommendations, we extracted relevant information including the year of publication, author(s), chapter name or number, text for the recommendation, and level of evidence. Based, on the clinical topic covered, we grouped included recommendations to five themes. Results: = 18). The 2018 Diabetes Canada and 2021 American Diabetic Association guidelines linked recommendations directly with levels and grades of evidence. None of the recommendations had level 1 or grade A evidence. Three recommendations from Diabetes Canada reported level 2, grade B evidence. American Diabetic Association reported 1 recommendation with grade B evidence, and 2 recommendations with grade C evidence. Conclusions: There is an opportunity for expansion of clinical practice guidelines to increase the depth and breadth of recommendations for high performance athletes with T1D.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.671
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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 designNot applicable
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

Citations2
Published2022
Admission routes2
Has abstractyes

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