Partnering With Family Members to Detect Delirium in Critically Ill Patients*
Bibliographic record
Abstract
OBJECTIVES: To evaluate the diagnostic accuracy of family-administered tools to detect delirium in critically ill patients. DESIGN: Diagnostic accuracy study. SETTING: Large, tertiary care academic hospital in a single-payer health system. PATIENTS: Consecutive, eligible patients with at least one family member present (dyads) and a Richmond Agitation-Sedation Scale greater than or equal to -3, no primary direct brain injury, the ability to provide informed consent (both patient and family member), the ability to communicate with research staff, and anticipated to remain admitted in the ICU for at least a further 24 hours to complete all assessments at least once. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Family-administered delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily. A board-certified neuropsychiatrist and team of ICU research nurses conducted the reference standard assessments of delirium (based on Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition, criteria) once daily for a maximum of 5 days. The mean age of the 147 included patients was 56.1 years (SD, 16.2 yr), 61% of whom were male. Family members (n = 147) were most commonly spouses (n = 71, 48.3%) of patients. The area under the receiver operating characteristic curve on the Family Confusion Assessment Method was 65.0% (95% CI, 60.0-70.0%), 71.0% (95% CI, 66.0-76.0%) for possible delirium (cutpoint of 4) on the Sour Seven and 67.0% (95% CI, 62.0-72.0%) for delirium (cutpoint of 9) on the Sour Seven. These area under the receiver operating characteristic curves were lower than the Intensive Care Delirium Screening Checklist (standard of care) and Confusion Assessment Method for ICU. Combining the Family Confusion Assessment Method or Sour Seven with the Intensive Care Delirium Screening Checklist or Confusion Assessment Method for ICU resulted in area under the receiver operating characteristic curves that were not significantly better, or worse for some combinations, than the Intensive Care Delirium Screening Checklist or Confusion Assessment Method for ICU alone. Adding the Family Confusion Assessment Method and Sour Seven to the Intensive Care Delirium Screening Checklist and Confusion Assessment Method for ICU improved sensitivity at the expense of specificity. CONCLUSIONS: Family-administered delirium detection is feasible and has fair, but lower diagnostic accuracy than clinical assessments using the Intensive Care Delirium Screening Checklist and Confusion Assessment Method for ICU. Family proxy assessments are essential for determining baseline cognitive function. Engaging and empowering families of critically ill patients warrant further study.
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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 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".