Turning for Ulcer ReductioN: A Multisite Randomized Clinical Trial in Nursing Homes
Bibliographic record
Abstract
OBJECTIVES: To determine optimal repositioning frequency of nursing home (NH) residents at risk for pressure ulcers (PrUs) when cared for on high-density foam mattresses. DESIGN: Multisite, randomized, clinical trial, known as Turning for Ulcer ReductioN (TURN Study). SETTINGS: NHs in the United States (n = 20) and Canada (n = 7) using high-density foam mattresses. PARTICIPANTS: Consenting residents (N = 942) aged 65 and older without PrUs at moderate (scores 13-14) or high (scores 10-12) risk of PrUs according to the Braden Scale. INTERVENTION: Participants were randomly allocated using risk stratification (moderate vs high) to a repositioning schedule (2, 3, or 4 hour) for 3 weeks. Blinded assessors assessed skin weekly. MEASUREMENTS: PrU incidence (coccyx or sacrum, trochanter, heels). RESULTS: Participants were mostly female (77.6%) and Caucasian (80.5%) and had a mean age of 85.1 ± 7.7. The most common diagnoses were cardiovascular (76.9%) and dementia (72.5%). Nineteen (2.0%) participants developed superficial PrUs. There was no significant difference (Wilcoxon test for ordered categories) in PrU incidence (P = .68) according to repositioning group (2 hour, 8/321, 2.5%; 3 hour, 2/326, 0.6%; 4 hour, 9/295, 3.1%), nor was there a statistically significant difference in the incidence of PrU between the high and moderate-risk groups (P = .79). Also, PrU incidence was not statistically significantly different between high-risk participants based on repositioning schedule (6/325, 1.8%, P = .90) or between moderate-risk participants based on repositioning schedule (13/617, 2.1%, P = .68). CONCLUSION: There was no difference in PrU incidence over 3 weeks of observation between those turned at 2-, 3-, or 4-hour intervals in this population of residents using high-density foam mattresses at moderate and high risk of developing PrUs when they were repositioned consistently and skin was monitored. This finding has major implications for use of nursing staff and cost of NH care.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".