National screening for delirium in paediatric intensive care units: A quality improvement initiative
Bibliographic record
Abstract
BACKGROUND: Internationally, one in three children develop delirium during their intensive care stay. International guidelines strongly recommend twice-daily screening for paediatric delirium using validated instruments. In the United Kingdom and Ireland, delirium was assessed only when suspected and few intensive care units (ICUs) used validated instruments. AIM: This initiative aimed to implement a national screening strategy in 28 paediatric intensive care units (PICUs) across the United Kingdom and Ireland. STUDY DESIGN: The strategy involved: (a) rapidly reviewing, evaluating and ranking paediatric screening instruments for sensitivity, specificity, appropriateness and acceptability for national implementation; (b) achieving national agreement to implement a common tool; (c) creating and disseminating training materials while supporting training personnel in implementation; and (d) integrating delirium monitoring within the Paediatric Intensive Care Audit Network national database. RESULTS: Among seven validated instruments, the top ranked options (from 1, most applicable to 7, least applicable) were the Cornell Assessment of Pediatric Delirium (average rank 1.25) and the Sophia Observation withdrawal Symptoms-Paediatric Delirium scale (1.5). Twenty-three units voted for their preferred choice of instrument: fifteen preferred the Cornell instrument, eight favoured the Sophia instrument and five did not respond. Training and implementation began in November 2021 and by March 2023 18 of the 28 units (64%) had successfully implemented screening. The national database began actively collecting delirium data from units in January 2024. CONCLUSIONS: This initiative outlined critical steps for implementing and maintaining practice of delirium screening in PICUs. We provided clinicians with validated screening tools for detecting paediatric delirium and the necessary support and infrastructure to maintain screening. Embedding and sustaining screening is an ongoing challenge. RELEVANCE TO CLINICAL PRACTICE: Undertaking routine screening for all intensive care patients from admission to discharge using validated instruments will provide earlier detection and treatment for critically ill children. This strategy offers a model for standardized and effective implementation in clinical practice in ICUs.
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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 | 0.127 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".