MétaCan
Menu
Back to cohort
Record W2982232716 · doi:10.3389/fneur.2019.01176

Methodology and Implementation of a Randomized Controlled Trial (RCT) for Early Post-concussion Rehabilitation: The Active Rehab Study

2019· article· en· W2982232716 on OpenAlexaff
Johna K. Register‐Mihalik, Kevin M. Guskiewicz, Stephen W. Marshall, Karen McCulloch, Jason P. Mihalik, Martin Mrázik, Ian Murphy, Dhiren Naidu, Shabbar I. Ranapurwala, Kathryn Schneider, Paula Gildner, Michael McCrea

Bibliographic record

VenueFrontiers in Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryUniversity of Alberta
FundersNational Center for Injury Prevention and ControlInjury Prevention Research CenterCenters for Disease Control and Prevention
KeywordsRandomized controlled trialConcussionPhysical therapyPhysical medicine and rehabilitationRehabilitationMedicinePsychologyPoison controlInjury preventionSurgeryMedical emergency

Abstract

fetched live from OpenAlex

Background: Sports-related concussion is a complex injury with heterogeneous presentation and management. There are few studies that provide guidance on the most effective and feasible strategies for recovery and return to sports participation. Furthermore, there have been no randomized studies of the feasibility, safety and efficacy of early rehabilitation strategies across multiple sports and age groups. This international cluster-randomized pragmatic trial evaluates the effectiveness of early multi-dimensional rehabilitation integrated with the current return to sport strategy vs. the current return to sport strategy alone. Methods: The study is a cluster-randomized pragmatic trial enrolling male and female athletes from 28 sites. The sites span three countries, and include multiple sports, levels of play (high school, college and professional), and levels of contact. The two study arms are Enhanced Graded Exertion (EGE) and Multidimensional Rehabilitation (MDR). The EGE arm follows the current return to sport strategy and the MDR arm integrates early, multidimensional rehabilitation strategies in the context of the current return to sport strategy. Each arm employs a post-injury protocol that applies to all athletes from that site in the event they sustain a concussion during their study enrollment. Participants are enrolled at pre-season baseline. Assessment timepoints include pre-season baseline, time of injury (concussion), 24-48 hours post-injury, asymptomatic, and 1-month post-injury. Symptoms and activity levels are tracked post injury through the return to play process and beyond. Injury and recovery characteristics are obtained for all participants. Primary endpoints include time to medical clearance for full return to sport and time to become asymptomatic. Secondary endpoints include symptom, neurocognitive, mental status, balance, convergence insufficiency, psychological distress, and quality of life trajectories post-injury. Discussion: Outputs from the trial are expected to inform both research and clinical practice in post-concussion rehabilitation across all levels of sport and extend beyond civilian medicine to care for military personnel. Ethics and Dissemination: The study is approved by the data coordinating center Institutional Review Board and registered at clinicaltrials.gov. Dissemination will include peer-reviewed publications, presentation to patients and public groups, as well as dissemination in other healthcare and public venues of interest.

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)0.133
metaresearch head score (Gemma)0.158
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: Methods · Consensus signal: none
Teacher disagreement score0.133
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1330.158
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0140.010
Bibliometrics0.0040.005
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0220.003

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 head0.033
GPT teacher head0.384
Teacher spread0.350 · 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
GenreMethods

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

Citations16
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicTraumatic Brain Injury ResearchFrench-language works237,207