Evaluation of the Incidence of Pressure Ulcers Using Hill-Rom VersaCare Surfaces
Bibliographic record
Abstract
OBJECTIVE: This study was conducted to: (1) determine the clinical effectiveness of a low-air-loss surface, VersaCare P500, in the prevention of pressure ulcers in surgical patients; (2) determine differences in the adjusted Braden scores between those using VersaCare and VersaCare P500 mattress surfaces; and (3) explore the demographic and therapeutic factors associated with the risk of skin breakdown as measured by Braden score. DESIGN: An open label quasi-experimental clinical trial was conducted. SETTING: A 540-bed acute care hospital. PATIENTS: A sample of 127 surgical patients admitted for elective orthopedic or neurologic surgery participated in the study. MAIN OUTCOME MEASURES: Decreased pressure ulcers. RESULTS: The sample was composed of 51 (51.5%) Hispanics, 38 (38.4%) Blacks, and 10 (10.1%) Whites. Both groups were not different in their demographic and therapeutic characteristics except with regard to their total number of bed-confinement days (t = -2.225; P = .028). Multivariate analysis demonstrated that only Black race (β = -.225; P = .03), days of bed confinement (β = -.257; P = .016), and bed type (β = .257; P = .013) were independently associated with skin integrity. CONCLUSION: The authors' findings suggest that the use of mircroclimate performance mattresses is associated with higher Braden scores, indicating a possible benefit with regard to protecting skin integrity and decreasing the risk of skin breakdown. Blacks were more likely to have lower Braden scores and "days of bed confinement" were negatively associated with the Braden score.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".