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Record W2581066027 · doi:10.1186/s12882-017-0454-4

A prospective 2-site parallel intervention trial of a research-based film to increase exercise amongst older hemodialysis patients

2017· article· en· W2581066027 on OpenAlexafffund
Pia Kontos, Shabbir M.H. Alibhai, Karen‐Lee Miller, Dina Brooks, Romeo Colobong, Trisha Parsons, Sarbjit V. Jassal, Alison Thomas, Malcolm A. Binns, Gary Naglie

Bibliographic record

VenueBMC Nephrology · 2017
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsBaycrest HospitalSt. Lawrence CollegeSt. Michael's HospitalQueen's UniversityUniversity of TorontoUniversity Health NetworkUniversity of New BrunswickCanada Research ChairsToronto Rehabilitation Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineHemodialysisNephrologyIntervention (counseling)Internal medicinePhysical therapyProspective cohort studyIntensive care medicineEmergency medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence suggests that exercise training for hemodialysis patients positively improves morbidity and mortality outcomes, yet exercise programs remain rare and are not systematically incorporated into care. We developed a research-based film, Fit for Dialysis, designed to introduce, motivate, and sustain exercise for wellness amongst older hemodialysis patients, and exercise counseling and support by nephrologists, nurses, and family caregivers. The objective of this clinical trial is to determine whether and in what ways Fit for Dialysis improves outcomes and influences knowledge/attitudes regarding the importance of exercise for wellness in the context of end-stage renal disease. METHODS/DESIGN: This 2-site parallel intervention trial will recruit 60 older hemodialysis patients from two urban hospitals. The trial will compare the film + a 16-week exercise program in one hospital, with a 16-week exercise-only program in another hospital. Physical fitness and activity measures will be performed at baseline, 8 and 16 weeks, and 12 weeks after the end of the program. These include the 2-min Walk Test, Grip Strength, Duke Activity Status Index, and the Timed Up-and-Go Test, as well as wearing a pedometer for one week. Throughout the 16-week exercise program, and at 12 weeks after, we will record patients' exercise using the Godin Leisure-time Exercise Questionnaire. Patients will also keep a diary of the exercise that they do at home on non-dialysis days. Qualitative interviews, conducted at baseline, 8, and 16 weeks, will explore the impact of Fit for Dialysis on the knowledge/attitudes of patients, family caregivers, and nephrology staff regarding exercise for wellness, and in what ways the film is effective in educating, motivating, or sustaining patient exercise during dialysis, at home, and in the community. DISCUSSION: This research will determine for whom Fit for Dialysis is effective, why, and under what conditions. If Fit for Dialysis is proven beneficial to patients, nephrology staff and family caregivers, research-based film as a model to support exercise promotion and adherence could be used to support the National Kidney Foundation's guideline recommendation (NKF-KDOQI) that exercise be incorporated into the care and treatment of dialysis patients. TRIAL REGISTRATION: NCT02754271 (ClinicalTrials.gov), retroactively registered on April 21, 2016.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.029
GPT teacher head0.339
Teacher spread0.310 · 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 designRandomized trial
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

Citations13
Published2017
Admission routes2
Has abstractyes

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