Delirium screening tools validated in the context of palliative care: A systematic review
Bibliographic record
Abstract
BACKGROUND: Delirium is a distressing neuropsychiatric disorder affecting patients in palliative care. Although many delirium screening tools exist, their utility, and validation within palliative care settings has not undergone systematic review. AIM: To systematically review studies that validate delirium screening tools conducted in palliative care settings. DESIGN: Systematic review with narrative synthesis (PROSPERO ID: CRD42019125481). A risk of bias assessment via Quality Assessment Tool for Diagnostic Accuracy Studies-2 was performed. DATA SOURCES: Five electronic databases were systematically searched (January 1, 1982-May 3, 2020). Quantitative studies validating a screening tool in adult palliative care patient populations were included. Studies involving alcohol withdrawal, critical or perioperative care were excluded. RESULTS: = 3496 patients). Data analyses revealed substantial heterogeneity in patient demographics and variability in screening and diagnostic practices that limited generalizability between study populations and care settings. A risk of bias assessment revealed methodological and reporting deficits, with only 3/17 studies at low risk of bias. CONCLUSIONS: The processes of selecting a delirium screening tool and determining optimal screening practices in palliative care are complex. One tool is unlikely to fit the needs of the entire palliative care population across all palliative care settings. Further research should be directed at evaluating and/or adapting screening tools and practices to fit the needs of specific palliative care settings and populations.
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 | 0.016 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".