Clinical Practice Guideline: Early Mobilization and Rehabilitation of Critically Ill Burn Patients
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".