Economic evaluations of interventions for the prevention and treatment of pressure ulcers: an umbrella review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this review is to synthesize the findings of economic evaluations of preventing or treating pressure ulcers. INTRODUCTION: Pressure ulcers are one of the most common preventable complications characterized by local tissue injury. Pressure ulcers increase mortality rates, impair quality of life, increase the length of hospital stay, and alter overall health outcomes. Published studies have found higher costs associated with treating pressure ulcers than preventing them, with treatment cost varying based on the pressure ulcer category (the greater the category, the higher the cost). We will systematically review the evidence on preventing or treating pressure ulcers from an economic perspective. INCLUSION CRITERIA: We will include systematic reviews that investigate both the cost and outcomes associated with the prevention or treatment of pressure ulcers. Systematic reviews dealing with economic evaluation of wound care or management will be excluded if they have not provided separate information for pressure ulcers. METHODS: Epistemonikos, MEDLINE, NHS Economic Evaluation Database, and the Canadian Agency for Drugs and Technologies in Health (CADTH) website will be searched for relevant systematic reviews from inception and without any language restrictions. Titles and abstracts will be screened at the initial stage, followed by full-text screening. Quality assessment will be done using the standard JBI critical appraisal instrument for systematic reviews and research syntheses. Article screening, data extraction, and quality assessment will be performed by two reviewers independently. All economic health outcomes will be considered under the primary outcomes of the study. SYSTEMATIC REVIEW REGISTRATION NUMBER: Open Science Framework (https://osf.io/9y2a7/).
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 | 0.090 | 0.106 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.096 | 0.018 |
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".