The CAM-ICU-7 and ICDSC as measures of delirium severity in critically ill adult patients
Bibliographic record
Abstract
BACKGROUND: In clinical practice, a dichotomous approach to delirium identification may no longer be relevant when existing delirium screening tools measure a range of scores. The objective of this study was to compare the Confusion Assessment Method for the Intensive Care Unit 7-item (CAM-ICU-7) and the Intensive Care Delirium Screening Checklist (ICDSC) as measures of the spectrum of delirium severity in critically ill adult patients. METHODS: In this cross-sectional study, 218 patients underwent 641 paired assessments by bedside nurses (ICDSC, as per usual care) and trained research assistants (CAM-ICU-7). Correlation between the CAM-ICU-7 and ICDSC scores was evaluated. Logistic regression was used to explore associations between CAM-ICU-7 or ICDSC score and length of ICU stay and mechanical ventilation (receipt, ≥96 hours). RESULTS: Delirium prevalence evaluated by the CAM-ICU-7 and ICDSC were 46.3% (95% CI:39.7-53.0) and 34.4% (95% CI:28.3-41.0). Prevalence of less than clinical threshold symptoms of delirium evaluated by the CAM-ICU-7 (score: 1-2) and ICDSC (score: 1-3) were 30.3% (95%CI:24.5-36.7) and 50.9% (95%CI:44.3-57.6). The CAM-ICU-7 and ICDSC had significant positive correlation (0.58, p<0.001). Agreement between the tools as measures of delirium was moderate (kappa = 0.51) and as measures of less than clinical threshold symptoms of delirium was fair (kappa = 0.21). Less than clinical threshold symptoms of delirium identified by the ICDSC, not CAM-ICU-7, were associated with prolonged length of ICU stay (≥7 days) in patients <65 years of age [Odds Ratio (OR) 9.2, 95% CI:2.5-34.0] and mechanical ventilation (receipt: OR 2.8, 95% CI:1.3-6.4; ≥96 hours: OR 6.6, 95% CI:1.9-22.9), when compared to patients with no delirium. CONCLUSIONS: The CAM-ICU-7 and ICDSC are measures of the spectrum of delirium severity that are closely correlated. Less than clinical threshold symptoms of delirium measure by the ICDSC is a better predictor of outcomes, when compared with the CAM-ICU-7.
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How this classification was reachedexpand
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 | 0.068 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".