Clinical pathway development to standardize pharmacological medication management of agitation in pediatric inpatient settings.
Bibliographic record
Abstract
Objective: Acute agitation in pediatrics is commonly encountered in hospital settings, can contribute to significant physical and psychological distress, and management is highly varied in practice. As such, the development of a standardized pharmacologic guideline is paramount. We aimed to develop a novel clinical pathway (CP) for management of acute agitation for all hospitalized pediatric patients in Canada. Methods: Healthcare professionals in Canada with expertise in treating and managing pediatric agitation formed a working group and developed a CP through conducting a literature review, engaging key partners, and obtaining interdisciplinary consensus (iterative real-time discussions with content experts). Once developed, the preliminary CP was presented to additional internal and external partners via multiple grand rounds and a webinar; feedback from participants guided final CP revisions. Results: The working group created a pediatric inpatient CP to guide pharmacologic management of agitation and serve as an easy-to-use clinical and educational resource with three complementary sections including: 1) a treatment algorithm, 2) a quick reference medication chart, and 3) two supporting documents, which provide a general overview of non-pharmacologic strategies prior to CP implementation and an illustrative scenario to accompany the medication chart to ensure effective utilization. Conclusions: This is the first CP to standardize pharmacological treatment and management of acute agitation in children in inpatient settings in Canada. Although further research is warranted to assess implementation and support process improvement, the CP can be adapted by individual institutions to assist in prompt pharmacological management of pediatric agitation to potentially improve outcomes for patients, families, and healthcare professionals.
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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 | 0.018 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
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".