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Record W4408556735 · doi:10.1186/s13054-025-05297-8

Early exercise therapy in patients with severe traumatic spinal cord injury: is it feasible in the ICU?

2025· letter· en· W4408556735 on OpenAlexaff
Antoine Dionne, David S.K. Magnuson, Andréane Richard‐Denis, Yvan Petit, Dorothy Barthélemy, Françis Bernard, Jean‐Marc Mac‐Thiong

Bibliographic record

VenueCritical Care · 2025
Typeletter
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineCentre for Interdisciplinary Research in RehabilitationÉcole de Technologie SupérieureHôpital du Sacré-Cœur de MontréalUniversité de Montréal
FundersCraig H. Neilsen Foundation
KeywordsMedicineSpinal cord injuryTraumatic brain injuryEmergency medicineIntensive care medicinePhysical therapySpinal cord

Abstract

fetched live from OpenAlex

Following traumatic spinal cord injury (SCI), patients remain immobilized in the intensive care unit (ICU) and the wards for several weeks before they are transferred to rehabilitation [ 1 ]. Unfortunately, this places them at high risk for deconditioning and developing immobility-associated complications [ 2 ]. In addition, immobility during the acute stages after TSCI could potentially hinder adaptive neuroplasticity and limit long-term neurological recovery, while early mobilization/exercise could improve outcomes [ 3 ]. Until now, early exercise therapy (EET) had never been attempted in humans due to practical obstacles for bedridden patients and potential concerns for safety, especially for patients in the ICU. In this context, the PROMPT-SCI trial is the first trial designed to evaluate the safety and feasibility of EET in patients with acute severe TSCI (ClinicalTrials.gov: NCT04699474) [ 4 ]. In this Correspondence, we aim to report specifically on our patients who were hospitalized in the ICU.

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)0.001
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.029
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0290.016
Insufficient payload (model declined to judge)0.0050.002

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 head0.076
GPT teacher head0.411
Teacher spread0.335 · 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 designObservational
Domainnot available
GenreCommentary

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

Citations3
Published2025
Admission routes1
Has abstractno

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