Delirium Severity Trajectories in Critically Ill Adults Using the Intensive Care Delirium Screening Checklist: A Population-Based Cohort
Bibliographic record
Abstract
OBJECTIVES: The delirium course of critically ill adults can be classified into trajectories based on the severity and duration of delirium as shown by a recent study. It is unknown whether these trajectories and associated outcomes are reproducible. We aimed to define delirium severity trajectories using the Intensive Care Delirium Screening Checklist (ICDSC) and delirium duration and evaluate the association of trajectory membership with clinical characteristics and 30-day post-discharge mortality. DESIGN: Population-based retrospective cohort. SETTING: Fourteen medical-surgical ICUs in Alberta, Canada from January 1, 2014, to December 21, 2019. PATIENTS: We included adult patients (≥ 18 yr old) with an ICU length of stay of greater than or equal to 24 hours, an ICDSC score indicating delirium (≥ 4), and 30-day follow-up data were included. Group-based trajectory modeling identified trajectories over a 7-day period with SAS v9.4 (SAS Institute, Cary, NC). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Demographic (age, sex) and clinical data (2 × d ICDSC score, comorbidities, illness severity, admission reason, procedures, length of stay, in-hospital, and 30-d post-discharge mortality) were captured from electronic medical records. In total, 21,071 patients were included, with a median age of 59 years (interquartile range, 46-70 yr), 59% male ( n = 12,547), and 3% died at 30 days ( n = 541). The five-trajectory model was selected. These trajectories followed previously defined patterns: 1) Mild-Brief (19.4%); 2); Severe-Rapid Recovers (18.5%); 3) Severe-Slow Recovers (31%); 4) Mild-Accelerating (14.1%); and 5) Severe-Nonrecovers (16.9%). Trajectory membership was not significantly associated with 30-day post-discharge mortality; however, clinically relevant trends were observed. CONCLUSIONS: The current study substantiates the proof-of-concept model of five delirium severity trajectories. Trajectory membership did not predict 30-day post-discharge mortality. Further research is needed to understand the associations between trajectory membership, biological-based biomarkers, and patient-relevant outcomes.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".