Prevalence, risk factors and management of pressure injuries and their implications for palliative care: A rapid overview of reviews
Bibliographic record
Abstract
INTRODUCTION: Evidence around pressure injuries in palliative care settings is limited and fragmented. AIM: To synthesize systematic review evidence regarding prevalence, risk factors, prevention and treatment of pressure injuries in non-acute care settings, and evaluate implications for specialist palliative care. DESIGN: A rapid overview of reviews following the Cochrane guidance for overviews. DATA SOURCES: We searched four databases (MEDLINE, Cochrane Database of Systematic Reviews, JBI EBM Reviews, and CINAHL) from inception to October 2024. We included systematic reviews on adult patients in inpatient Palliative Care Units or settings likely involving end-of-life care. RESULTS: = 5,856,293) were included. Thirteen of the reviews were high quality. Only one low-quality review specifically addressed palliative care, focusing on prevalence and risk factors. Interventions were categorized into nutritional, physical (e.g. repositioning, tilt strategies), topical/dressing-based, electrical stimulation and organizational approaches. Frequent repositioning and certain nutritional interventions may reduce incidence or surface area of pressure ulcers; however, certainty remains very low. Frequent repositioning, specific tilt strategies and specific nutritional interventions may help reduce the incidence of pressure injuries and decrease injury surface area; however certainty is very low. Other interventions have limited and inconclusive evidence and were rated low to very low certainty according to GRADE criteria due to poor trial design and population and setting variations. CONCLUSIONS: The evidence base remains weak and largely indirect, offering insufficient guidance for clinical practice in palliative care. High-quality, targeted research is needed to inform effective pressure injury prevention and management in this population.
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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 | 0.018 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".