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Record W4282929168 · doi:10.1093/jbcr/irac008

Clinical Practice Guideline: Early Mobilization and Rehabilitation of Critically Ill Burn Patients

2022· article· en· W4282929168 on OpenAlexaff
Robert Cartotto, Laura Johnson, Jody M Rood, David Lorello, Annette F. Matherly, Ingrid Parry, Kathleen S Romanowski, Shelley Wiechman, Amanda P Bettencourt, Joshua Carson, Henry Lam, Bernadette Nedelec

Bibliographic record

VenueJournal of Burn Care & Research · 2022
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMcGill UniversityHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRehabilitationGuidelineIntensive care unitIntensive care medicineIntervention (counseling)PopulationPhysical therapyNursing

Abstract

fetched live from OpenAlex

This Clinical Practice Guideline addresses early mobilization and rehabilitation (EMR) of critically ill adult burn patients in an intensive care unit (ICU) setting. We defined EMR as any systematic or protocolized intervention that could include muscle activation, active exercises in bed, active resistance exercises, active side-to-side turning, or mobilization to sitting at the bedside, standing, or walking, including mobilization using assistance with hoists or tilt tables, which was initiated within at least 14 days of injury, while the patient was still in an ICU setting. After developing relevant PICO (Population, Intervention, Comparator, Outcomes) questions, a comprehensive literature search was conducted with the help of a professional medical librarian. Available literature was reviewed and systematically evaluated. Recommendations were formulated through the consensus of a multidisciplinary committee, which included burn nurses, physicians, and rehabilitation therapists, based on the available scientific evidence. No recommendation could be formed on the use of EMR to reduce the duration of mechanical ventilation in the burn ICU, but we conditionally recommend the use of EMR to reduce ICU-acquired weakness in critically ill burn patients. No recommendation could be made regarding EMR's effects on the development of hospital-acquired pressure injuries or disruption or damage to the skin grafts and skin substitutes. We conditionally recommend the use of EMR to reduce delirium in critically ill burn patients 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.207
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.207
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.453
Teacher spread0.413 · 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 teacher head, not a consensus.

Study designObservational
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

Citations50
Published2022
Admission routes1
Has abstractyes

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