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Record W4400354697 · doi:10.2196/54451

Early In-Bed Cycle Ergometry With Critically Ill, Mechanically Ventilated Patients: Statistical Analysis Plan for CYCLE (Critical Care Cycling to Improve Lower Extremity Strength), an International, Multicenter, Randomized Clinical Trial

2024· article· en· W4400354697 on OpenAlexafffundvenue
Diane Heels‐Ansdell, Laurel Kelly, Heather K. O’Grady, Christopher Farley, Julie C. Reid, Sue Berney, Amy M. Pastva, Karen E. A. Burns, Frédérick D’Aragon, Margaret S. Herridge, Andrew Seely, Jill Rudkowski, Bram Rochwerg, Alison Fox‐Robichaud, Ian Ball, François Lamontagne, Erick Duan, Jennifer Tsang, Patrick Archambault, Avelino C. Verceles, John Muscedere, Sangeeta Mehta, Shane English, Tim Karachi, Karim Serri, Brenda Reeve, Lehana Thabane, Michelle E. Kho

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsJoseph Brant HospitalUniversité de MontréalSinai Health SystemQueen's UniversityUniversité LavalNiagara Health SystemHamilton Health SciencesCentre intégré de santé et de services sociaux de Chaudière-AppalachesUniversity Health NetworkOttawa HospitalHôpital du Sacré-Cœur de MontréalUniversity of OttawaCentre Hospitalier Universitaire de SherbrookeUniversité de SherbrookeUniversity of TorontoWestern UniversitySt. Michael's HospitalSt. Joseph’s Healthcare HamiltonMcMaster UniversityImpact
FundersCanadian Institutes of Health Research
KeywordsCyclingCritically illPreprintRandomized controlled trialMedicinePhysical therapyCritical illnessPhysical medicine and rehabilitationIntensive care medicineSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Survivors of critical illness are at risk of developing physical dysfunction following intensive care unit (ICU) discharge. ICU-based rehabilitation interventions, such as early in-bed cycle ergometry, may improve patients' short-term physical function. OBJECTIVE: Before unblinding and trial database lock, we describe a prespecified statistical analysis plan (SAP) for the CYCLE (Critical Care Cycling to Improve Lower Extremity Strength) randomized controlled trial (RCT). METHODS: CYCLE is a 360-patient, international, multicenter, open-label, parallel-group RCT (1:1 ratio) with blinded primary outcome assessment at 3 days post-ICU discharge. The principal investigator and statisticians of CYCLE prepared this SAP with approval from the steering committee and coinvestigators. The SAP defines the primary and secondary outcomes (including adverse events) and describes the planned primary, secondary, and subgroup analyses. The primary outcome of the CYCLE trial is the Physical Function Intensive Care Unit Test-scored (PFIT-s) at 3 days post-ICU discharge. The PFIT-s is a reliable and valid performance-based measure. We plan to use a frequentist statistical framework for all analyses. We will conduct a linear regression to evaluate the primary outcome, incorporating randomization as an independent variable and adjusting for age (≥65 years versus <65 years) and center. The regression results will be reported as mean differences in PFIT-s scores with corresponding 95% CIs and P values. We consider a 1-point difference in PFIT-s score to be clinically important. Additionally, we plan to conduct 3 subgroup analyses: age (≥65 years versus <65 years), frailty (Baseline Clinical Frailty Scale ≥5 versus <5), and sex (male versus female). RESULTS: CYCLE was funded in 2017, and enrollment was completed in May 2023. Data analyses are complete, and the first results were submitted for publication in 2024. CONCLUSIONS: We developed and present an SAP for the CYCLE RCT and will adhere to it for all analyses. This study will add to the growing body of evidence evaluating the efficacy and safety of ICU-based rehabilitation interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03471247; https://clinicaltrials.gov/ct2/show/NCT03471247 and NCT02377830; https://clinicaltrials.gov/ct2/show/NCT02377830. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/54451.

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)0.042
metaresearch head score (Gemma)0.060
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.042
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.060
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.095
GPT teacher head0.535
Teacher spread0.440 · 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
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

Citations2
Published2024
Admission routes3
Has abstractyes

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