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Record W4403129814 · doi:10.1016/j.jsampl.2024.100075

Effect of supervised exercise training on objectively measured physical activity in patients during anthracycline therapy

2024· article· en· W4403129814 on OpenAlexaff
Caroline Schneider, Laura Stuetz, A Dierks, Kristin L. Campbell, Matthias Wilhelm, Prisca Eser

Bibliographic record

VenueJSAMS Plus · 2024
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsUniversity of British Columbia
FundersSwiss Cancer Research FoundationInselspital, Universitätsspital Bern
KeywordsPhysical therapyAnthracyclinePhysical medicine and rehabilitationMedicineExercise therapyTraining (meteorology)PsychologyInternal medicineRandomized controlled trial

Abstract

fetched live from OpenAlex

It is unknown what the benefits of cardio-oncologic rehabilitation programmes on cardiorespiratory fitness and cancer fatigue during anthracycline-based chemotherapies (AC) are with supervised exercise training (ET), compared to PA advice and tracking only. Patients with breast cancer or lymphoma were recruited from four cancer centres and randomly assigned to three months supervised ET during (EXduringAC) or after (EXpostAC) AC. All patients were counselled on physical activity (PA) and PA was objectively measured with an activity tracker. Primary endpoints were peak VO 2 , fatigue and quality of life (QoL) after AC (AC-end) and at follow-up (3 months after completion of AC). Secondary endpoints were daily PA and daily steps during AC and follow-up phase, which were compared between days with and without centre-based training sessions. All analyses were performed by linear mixed models. Fifty-seven patients (median [1st and 3rd quartiles] age 47 years [38, 57 years]; 95 ​% women) consented to participate, of whom data from 51 patients were available. Despite the fact that PA on days with centre-based training sessions was 28 (95 ​% confidence interval 24–32) min higher with 4382 (3995–4768) more steps, neither PA nor steps differed between groups in neither AC nor follow-up phase, nor were there between group differences in peak VO 2, QoL or fatigue at any time point. In physically active patients with cancer, PA advice and using an activity tracker was equally effective on changes in peak VO 2 , fatigue, or QoL as enrolling in centre-based ET performed during or after AC. NCT03850171, February 21, 2019.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.302
Teacher spread0.278 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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