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Record W1594825155 · doi:10.14288/hfjc.v5i1.123

Exercise Training in Oncology: Systematic Review and Clinical Practice Recommendations

2012· article· en· W1594825155 on OpenAlexaff
Lee W. Jones, Edith Pituskin, Cláudio L. Battaglini

Bibliographic record

VenueOpen Collections · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCardiorespiratory fitnessMedicinePhysical therapyPsychological interventionCancer-related fatigueQuality of life (healthcare)Clinical PracticeMEDLINEIntervention (counseling)CancerIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

Background: The emergence of exercise therapy as an important adjunct therapy following a cancer diagnosis dramatically increases the need for oncology professionals to inform and advise cancer patients on this modality. To guide clinical practice and ensure optimal safety and efficacy, oncology-specific evidence-based practice recommendations are required. Methods: We conducted a systematic review to identify all studies examining the effect of an exercise training intervention that included an objective measurement of cardiorespiratory fitness in adults diagnosed with cancer. Studies were assessed according to the Appraisal of Guidelines for Research and Evaluation (AGREE) II criteria. Despite considerable heterogeneity, structured exercise interventions significantly improved a variety of measures of cardiorespiratory fitness, body composition, global quality of life, fatigue, and depression. Results: Based on this evidence, we provide clinical practice exercise recommendations for curative-intent cancer patients both during and following adjuvant therapy. Conclusion: This summary provides important guidance to oncology and other health professionals giving exercise advice to individuals with cancer.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.348
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.109
GPT teacher head0.455
Teacher spread0.346 · 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
GenreOther

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

Citations3
Published2012
Admission routes1
Has abstractyes

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