The 2023 World delirium awareness and quality Survey: A Canadian substudy
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the proportion of screened patients with delirium and the strategies used for its management in Canadian hospitals caring for critically ill children or adults. METHODS: This is a secondary analysis of a cross-sectional study completed on World Delirium Awareness Day (March 15, 2023). Respondents completed a 35-question survey on the proportion of screened patients with delirium (at 8:00 am and 8:00 pm), treatment, and management strategies employed. RESULTS: A total of 27 ICUs (22 adult and 5 pediatric) participated. Among adult ICU patients assessed for delirium, 18 % (n = 34/194) had delirium at 8:00 am and 18 % (32/181) had delirium at 8:00 pm. In pediatric ICUs, the proportion of screened patients with delirium was higher, with 50 % (n = 8/16) at 8:00 am and 44 % (n = 7/16) at 8:00 pm. Delirium management strategies varied: with non-pharmacological approaches such as multi-professional rounds (100 %), pain management (96 %), and mobilization (85 %) being most common. The most reported written delirium management protocols included spontaneous breathing trials in adult ICUs and physical restraint and sedation management in PICUs. Few ICUs reported written protocols for family engagement and empowerment. CONCLUSIONS: Delirium remains a prevalent issue in Canadian ICUs, with variability in assessment and management strategies. Gaps in family engagement and pediatric-specific protocols persist. Addressing barriers like staff shortages and lack of training is critical to improving care. IMPLICATIONS FOR CLINICAL PRACTICE: Improving delirium management requires standardized protocols, especially in PICUs, and better integration of family engagement in care. Addressing workforce challenges (e.g., staff shortages and educating new staff on delirium) will be crucial for enhancing delirium prevention and treatment in Canadian ICUs. Further research should focus on pediatric-specific interventions and pharmacological management.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".