Assessment of Delirium in the Intensive Care Unit: Nursing Practices And Perceptions
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Despite practice guidelines promoting delirium assessment in intensive care, few data exist regarding current delirium assessment practices among nurses and how these practices compare with those for sedation assessment. OBJECTIVES: To identify current practices and perceptions of intensive care nurses regarding delirium assessment and to compare practices for assessing delirium with practices for assessing sedation. METHODS: A paper/Web-based survey was administered to 601 staff nurses working in 16 intensive care units at 5 acute care hospitals with sedation guidelines specifying delirium assessment in the Boston, Massachusetts area. RESULTS: Overall, 331 nurses (55%) responded. Only 3% ranked delirium as the most important condition to evaluate, compared with altered level of consciousness (44%), presence of pain (23%), or improper placement of an invasive device (21%). Delirium assessment was less common than sedation assessment (47% vs 98%, P < .001) and was more common among nurses who worked in medical intensive care units (55% vs 40%, P = .03) and at academic centers (53% vs 13%, P < .001). Preferred methods for assessing delirium included assessing ability to follow commands (78%), checking for agitation-related events (71%), the Confusion Assessment Method for the Intensive Care Unit (36%), the Intensive Care Delirium Screening Checklist (11%), and psychiatric consultation (9%). Barriers to assessment included intubation (38%), complexity of the tool for assessing delirium (34%), and sedation level (13%). CONCLUSIONS: Practice and perceptions of delirium assessment vary widely among critical care nurses despite the presence of institutional sedation guidelines that promote delirium assessment.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it