Feasibility and acceptability of family administration of delirium detection tools in the intensive care unit: a patient-oriented pilot study
Bibliographic record
Abstract
Background: Family-administered delirium detection tools may serve as valuable diagnostic adjuncts because family caregivers may be better able than providers to detect changes in patient cognition and behaviour from pre-illness levels of functioning. The aim of this pilot study was to assess the feasibility and acceptability of family-administered tools to detect delirium in critically ill patients. Methods: In this single-centre pilot tool validation study conducted in August and September 2017, eligible family caregivers used the Family Confusion Assessment Method (FAM-CAM) and the Sour Seven questionnaire to detect delirium during the patient’s intensive care unit (ICU) stay. We calculated descriptive statistics for all study variables. Patients and family caregivers were involved as research partners throughout the study. A patient-orient research approach was taken, engaging patients and family caregivers as full partners. Results: Of 141 patients admitted to the ICU, 75 were eligible, of whom 53 were approached; 21 patients (40%), 23/38 family caregivers (60%) and 17/38 dyads (i.e., patient and family caregiver enrolled together) (45%) consented to participate. The most common reason for nonenrolment was refusal by the family, who commonly reported feeling overwhelmed. The completion rate for the FAM-CAM and Sour Seven questionnaire was 74% (17/23). Among 13 dyads, family caregivers detected delirium in 5 patients (38%) using the FAM-CAM, and delirium or possible delirium in 8 patients (62%) using the Sour Seven questionnaire, whereas trained research assistants detected delirium in 8 patients (62%) using the Confusion Assessment Method for the Intensive Care Unit 7 and the Richmond Agitation–Sedation Scale (κ coefficient for agreement between the former and the FAM-CAM and Sour Seven questionnaire 0.62 and 0.85, respectively). Interpretation: Administration of the FAM-CAM and Sour Seven questionnaire by family caregivers to detect delirium in the ICU is feasible and acceptable, although, as with most family engagement strategies, it was not desired by all. Results from this pilot study support a definitive study with a larger sample to enable calculation of inferential statistics, but additional recruitment strategies are necessary to improve the response rate. Trial registration:Clinicaltrials.gov, no. NCT03379129.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".