ABSTRACT 19
Bibliographic record
Abstract
Background and aims: Early mobilization of critically ill adults appears to be safe, feasible, and improves patient outcomes. In contrast, there is a paucity of research in pediatrics. Aims: Our objective in this prospective cohort study was to evaluate the safety and feasibility of early rehabilitation in the pediatric critical care unit (PCCU) setting, using a combination of individualized mobility interventions. Methods: This study was IRB approved. We applied either a passive (cycle ergometer) and/or active (interactive video-gaming) mobility interventions to hemodynamically stable PCCU patients aged 3–18 years. Interventions were applied based on their functional and cognitive ability, i.e. unconscious or non-cooperative patients received cycle-ergometry, while video-gaming was applied once the patient could cooperate. Each intervention was applied for a maximum of 2 days. Primary outcomes were feasibility and safety. Results: We enrolled 25 patients between June 2012–2013, 13 (52%) of whom were male. 21 (84%) received cycle ergometry and 16% participated with video-gaming. 52% patients were mechanically ventilated during the intervention. Cardiorespiratory parameters remained stable during the interventions. There were no accidental tube dislodgements, reported changes in pain or sedation requirements, or other adverse events during the study period. One patient with stimulus sensitive seizures on continuous electroencephalographic monitoring did not experience any seizures, while another with intracranial pressure (ICP) monitoring, did not exhibit ICP changes, during the intervention. Conclusions: This pilot study suggests that it is feasible to apply these novel methods of early mobilization in the PCCU setting, without evidence of adverse events.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.405 | 0.245 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".