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Record W2789259940 · doi:10.14740/jocmr3382w

Exercise Therapy for Patients With Type 2 Diabetes: A Narrative Review

2018· review· en· W2789259940 on OpenAlexvenueno aff
Hidekatsu Yanai, Hiroki Adachi, Yoshinori Masui, Hisayuki Katsuyama, Akiko Kawaguchi, Mariko Hakoshima, Yoko Waragai, Tadanao Harigae, Hidetaka Hamasaki, Akahito Sako

Bibliographic record

VenueJournal of Clinical Medicine Research · 2018
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineType 2 diabetesGlycemicDiabetes mellitusExercise prescriptionComorbidityPhysical therapyInternal medicinePhysical activityEndocrinology

Abstract

fetched live from OpenAlex

To achieve excellent glycemic control in patients with type 2 diabetes, an adequate prescription of exercise therapy is required. The meta-analyses proposed that high-intensity training improves metabolic parameters in patients with pre-diabetes or type 2 diabetes and low physical activity is associated with an increased risk of incident type 2 diabetes. Here, we would introduce literatures about effects of physical activity on mortality, cardiovascular events, and metabolic parameters, to encourage understanding of exercise therapy, and then describe how to prescribe exercise therapy for patients with type 2 diabetes. We also show the usefulness of non-exercise activity thermogenesis for diabetic patients who cannot perform volitional sporting-like exercise because of diabetic complication and/or comorbidity, by presenting results of our previous studies.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.400
GPT teacher head0.619
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2018
Admission routes1
Has abstractyes

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