The Delirium Drug Scale is associated to delirium incidence in the emergency department
Bibliographic record
Abstract
ABSTRACTBackground:The Delirium Drug Scale (DDS) is an evaluation scale developed to assess a patient's drug burden for delirium. The primary goal is to validate the association between the DDS score and the incidence of delirium. METHODS: This study was an observational retrospective cross-sectional chart review study in patients aged 75 years and older. It was carried out in three emergency departments of a tertiary care university health center. Patients were included if a medication list was available. Delirium present upon admission was assessed during the first five days of admission. RESULTS: A total of 1,205 subjects were included in the analysis. The mean age was of 83.4 years, and 62.4% were female. The prevalence of delirium was 19.1%. A total of 745 patients (62%) were exposed to DDS medication. The relative risk for the low (1-2) and high (>2) exposure group according to the DDS score was of 1.26 (CI: 0.95; 1.66) and 2.18 (CI: 1.61; 2.96) compared to a score of 0. In the multivariate analysis, dementia, anxiety, insomnia, history of delirium, infection, and acute kidney failure were significantly associated to delirium. When adjusted for confounding variables, the DDS score was associated with the incidence of delirium with an odd ratio (OR) of 1.29 (CI: 1.16; 1.44). CONCLUSIONS: This study found that DDS score was associated with delirium incidence. The association persisted in the multivariate analysis adjusted for 26 known risks and precipitating factors for delirium.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".