Risk factors for delirium in adult patients receiving specialist palliative care: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Delirium is common and distressing for patients receiving palliative care. Interventions targetting modifiable risk factors in other settings have been shown to prevent delirium. Research on delirium risk factors in palliative care can inform context-specific risk-reduction interventions. AIM: To investigate risk factors for the development of delirium in adult patients receiving specialist palliative care. DESIGN: Systematic review and meta-analysis (PROSPERO CRD42019157168). DATA SOURCES: CINAHL, Cochrane Database of Systematic Reviews, Embase, MEDLINE and PsycINFO (1980-2021) were searched for studies reporting the association of risk factors with delirium incidence/prevalence for patients receiving specialist palliative care. Study risk of bias and certainty of evidence for each risk factor were assessed. RESULTS: Of 28 included studies, 16 conducted only univariate analysis, 12 conducted multivariate analysis. The evidence for delirium risk factors was limited with low to very low certainty. POTENTIALLY MODIFIABLE RISK FACTORS: Opioids and lower performance status were positively associated with delirium, with some evidence also for dehydration, hypoxaemia, sleep disturbance, liver dysfunction and infection. Mixed, or very limited, evidence was found for some factors targetted in multicomponent prevention interventions: sensory impairments, mobility, catheter use, polypharmacy (single study), pain, constipation, nutrition (mixed evidence). NON-MODIFIABLE RISK FACTORS: Older age, male sex, primary brain cancer or brain metastases and lung cancer were positively associated with delirium. CONCLUSIONS: Findings may usefully inform interventions to reduce delirium risk but more high quality prospective cohort studies are required to enable greater certainty about associations of different risk factors with delirium during specialist palliative care.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.045 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".