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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".