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Record W4405590089 · doi:10.2196/64905

Prehabilitation Exercise Training to Target Improved Muscle Strength in Pretransplant Patients Diagnosed With Multiple Myeloma: Protocol for a Pilot Randomized Controlled Trial

2024· article· en· W4405590089 on OpenAlexvenueno aff
Amber J. Normann, Clifton C. Mo, Rebekah L. Wilson, M. Pérez, Corey Cutler, Hajime Uno, LaDora V. Thompson, Tina L. Skinner, Paul G. Richardson, Catherine R. Marinac, Christina M. Dieli‐Conwright

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMedicinePrehabilitationPhysical therapyCardiorespiratory fitnessRandomized controlled trialAerobic exerciseMultiple myelomaClinical trialStrength trainingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Muscle mass and strength are severely compromised in patients diagnosed with multiple myeloma, such that the risk of poor overall survival increases as the prevalence of low muscle mass, also known as sarcopenia, increases. Additionally, at the time of autologous stem cell transplant (ASCT), 51% of patients experience low muscle mass and strength, which can prolong hospitalization and lead to increased risk of obesity, insulin resistance, lowered physical function, and poor quality of life. OBJECTIVE: The PROTECT (Prehabilitation Exercise Training in Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation) trial will examine the preliminary effects of digitally supervised prehabilitative aerobic and resistance exercise on muscle strength in patients with multiple myeloma scheduled for ASCT. METHODS: This prospective, 2-armed single-center randomized controlled trial will recruit 30 patients with multiple myeloma, aged 18 years and older, planning to receive ASCT. Individuals will be assigned to either the exercise or the waitlist control group. The 8-week exercise intervention is home-based and digitally supervised by a clinical exercise trainer. The frequency of the exercise intervention is 3 times per week consisting of aerobic exercise on a cycle ergometer and resistance exercises, which are individually tailored based on patient health status. The waitlist control group maintains normal daily activities of living and is offered the intervention within 6 months from ASCT. The primary outcome is lower limb muscle strength, measured using the 10-repetition maximum leg press or extensor strength. Additional outcomes include physical and cardiorespiratory function, patient-reported outcomes, cardiometabolic health outcomes, and clinical outcomes. RESULTS: The trial was funded in the fall of 2022 and recruitment began in June 2023. As of August 2024, a total of 3 participants have consented and been randomized (n=1, exercise group; n=2, waitlist control group). Trial completion and start of data analysis is expected in July 2025 with expected results to be published in early winter of 2026. CONCLUSIONS: We expect exercise to improve lower limb muscle strength and overall health outcomes compared to the waitlist control group. Results will contribute foundational knowledge needed to conduct larger-phase clinical trials testing the clinical benefits of prehabilitation exercise in this patient population. This study will provide insight into a prehabilitative exercise intervention designed to support patient prognosis. TRIAL REGISTRATION: ClinicalTrials.gov NCT05706766; https://clinicaltrials.gov/study/NCT05706766. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64905.

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)0.024
metaresearch head score (Gemma)0.020
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.059
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.020
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0120.006
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0590.008

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 head0.104
GPT teacher head0.470
Teacher spread0.366 · 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
GenreProtocol

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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

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