Impact of Family Presence on Delirium in Critically Ill Patients: A Retrospective Cohort Study
Bibliographic record
Abstract
Delirium, an acutely disturbed state of consciousness, manifests as a collection of symptoms such as confusion. There is potential for family members of critically ill patients to assist in non-pharmacological delirium prevention and management (e.g., re-orientation). Despite this, there are few studies on the impact of Intensive Care Unit (ICU) family presence on delirium. To bridge these knowledge gaps, our study employed a population-based retrospective cohort design to explore the association between family presence and both the incidence and duration of delirium in critically ill patients. The electronic health records of consecutive adult patients admitted to any of 14 adult medical-surgical adult ICUs in Alberta, Canada between January 1, 2014 and December 30, 2018 were examined. Family presence in the ICU (exposure), was extracted using a validated algorithm (1. family physically present, 2. family phone call only, 3. no family presence or call [reference group]). Delirium was measured using the Intensive Care Delirium Screening Checklist (ICDSC). Incident delirium was quantified (primary outcome) using an ICDSC cut-off of ≥4 points, after family presence (yes/no). Duration of delirium (secondary outcome) was measured as the total number of ICU days (24-hour periods) with a positive ICDSC score (≥4 points). Multivariable mixed-effects logistic and linear regression models (accounting for clustering by patient re-admission and ICU site, where appropriate) were used to evaluate the association between family member presence and the incidence and duration of delirium in critically-ill patients in the ICU, respectively. All regression models were adjusted for relevant covariates (e.g., ICU admission type, Glasgow Coma Scale [GCS]). We included 25,537 patients. Family presence in the ICU was associated with lower incidence of delirium during elective-surgical admissions in patients with intact GCS (OR 0.60, 95%CI:0.39-0.97, p=0.02) as compared to patients in the reference group. Family presence in the ICU decreased duration of delirium (adjusted mean difference -1.87 days, 95%CI: -2.01 to -1.81, p<0.001) as compared to patients in the reference group. Family presence in the ICU may decrease the incidence of delirium in patients admitted for elective-surgical reasons with intact GCS and duration of delirium in all patients by up to 2 days.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".