The effect of pressure‐relieving surfaces on the prevention of heel ulcers in a variety of settings: a meta‐analysis
Bibliographic record
Abstract
This meta-analysis investigated the effectiveness of a pressure-relieving intervention on the incidence of heel pressure ulcers in a variety of settings. Literature searches of Cumulative Index to Nursing and Allied Health Literature, MEDLINE, PubMed, EMBASE and Cochrane databases were conducted for English-language articles that investigated the effect of pressure relief interventions with or without concurrent prevention programs on the number of heel ulcers occurring on adult humans in a controlled clinical design. Full articles were selected from citations based upon consensus between at least two independent reviewers. Methodological quality of each study was assessed using the Jadad and PEDro scales. A quantitative analysis was performed to determine and compare relative risk (RR) between pressure relief programs/devices that were classified according to similarity of interventions. Fourteen studies that involved a total of 1457 subjects were selected from a total of 105 full articles reviewed. Pressure-reducing/relieving surfaces were associated with a significantly lower incidence of heel ulcers compared with standard hospital mattresses (RR = 0.50, 95% CI = 0.26-0.93, P < 0.03). Foam mattresses also significantly reduced the risk of developing heel ulcers. There is evidence to support the use of certain air or foam mattresses/overlays in the prevention of heel pressure ulcers when compared with a standard hospital mattress. There is insufficient research available at this time to determine if heel-protective devices can prevent heel pressure ulcers. These results need to be interpreted with caution given the relatively low number and poor quality of research articles available to date.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.058 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".