Reducing the use of dynamic mattress systems in clinical practice using the TREZZO HS advanced system
Bibliographic record
Abstract
Background: This study aimed to determine whether the TREZZO HS advanced foam mattress system could reduce the use of dynamic mattress systems (Alternating and Constant Low Pressure) in patients on vascular and stroke wards. Methods: TREZZO HS mattresses were evaluated in a vascular and stroke wards over a 6-week period with respect to the outcome of reduction in the need for dynamic mattress use and any effect on skin integrity. Data was compared with corresponding retrospective data from the previous year in which high-specification pressure-reducing foam mattresses were available. Mean length of patient stay on both types of mattresses, and the dynamic mattress was evaluated. Cox semiparametric time-to-event methods were used to assess the hazard of patient transfer to a dynamic mattress in patients positioned on TREZZO HS, rather than the previously used foam mattress. Results: Use of the TREZZO system reduced the mean length of stay on a dynamic mattress by 70% over both wards; from 41.0 days to 12.6 days. The proportion of patient-days spent on dynamic mattress systems decreased from 47.8% to 7.1%. Mattress type was significantly associated with the event (p=0.036); hazard ratio 0.328 (95% confidence interval 0.116 to 0.929). Ward type was not significantly associated with the event (p=0.333). Conclusion: The TREZZO HS system has been shown to substantially reduce the use of dynamic mattress usage and may be a cost-effective way of reducing the likelihood of pressure ulceration in vascular and stroke patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".