Early Mobilization Protocols in Critically Ill Pediatric Patients: A Scoping Review of Strategies, Tools and Perceived Barriers
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: We will describe the early mobilization protocols applied to critically ill pediatric patients in PICUs, analyzing the strategies employed, the tools used, and the barriers perceived by the healthcare team during their implementation. METHODS: The scoping review followed the guidelines established by PRISMA-ScR. A search was conducted across five electronic databases: PubMed, Scopus, Web of Science, Dimensions AI, and ScienceDirect. Articles published in English that focused on pediatric patients aged 0 to 18 years were included. RESULTS: A total of 3508 records were initially identified, of which 3422 articles were evaluated after duplicate removal. Subsequently, 12 studies that met the inclusion criteria were included. The methodological quality of the studies was mostly adequate, with 71.43% achieving scores between eight and nine on the Newcastle-Ottawa scale and 50% of the randomized clinical trials obtaining the maximum score of 7/7 on the Jadad scale. The interventions analyzed, including active bed mobility, bed cycling, and virtual reality, showed positive results in terms of feasibility and safety. The most frequently reported barriers to mobilization were hemodynamic instability, excessive sedation, pain, and lack of personnel and equipment. CONCLUSIONS: Early mobilization in pediatric PICUs is linked to improvements in mobility, reduced hospital stays, and shorter mechanical ventilation duration. However, its implementation is limited by barriers such as hemodynamic instability, excessive sedation, and lack of personnel and equipment. Further research is needed to establish uniform protocols, reduce these barriers, and optimize their effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".