Factors Associated with Pressure Ulcers in Adults in Acute Care Hospitals
Bibliographic record
Abstract
OBJECTIVES: To identify and describe the relationship of factors associated with pressure ulcers in adults in acute care hospitals. DESIGN: Cross-sectional prevalence studies. SETTING: University teaching hospital. PATIENTS: Prevalence studies conducted from 1993 to 1995 with a total of 1992 subjects served as the derivation sample and a 1996 prevalence study with 581 subjects served as the validation sample. MAIN OUTCOME MEASURES: Pressure ulcers and the Braden risk assessment subscale scores. DATA ANALYSIS: Logistic regression analysis was used to derive a model that fit the data and performed well at identifying factors associated with pressure ulcers. Performance of the model, in terms of calibration, was statistically evaluated using the Hosmer-Lemeshow goodness-of-fit test. The effectiveness of the model, in terms of discrimination, was assessed by considering the cut-off values using 2 by 2 classification tables to measure the overall percentage of subjects correctly classified in the validation sample. MAIN RESULTS: Factors associated with pressure ulcers in adults in acute care hospitals were identified as age, male gender, sensory perception, moisture, mobility, nutrition, and friction/shear. Three interactions were also found to be associated with pressure ulcers; 2 interactions (age and sensory perception and moisture and sensory perception) were negatively associated and 1 interaction (nutrition and gender/male) was positively associated with pressure ulcers. The Hosmer-Lemeshow goodness-of-fit test for the derivation sample (.76) and the validation sample (.79) indicated that the model was well calibrated and a good fit. The overall percentage of subjects correctly classified using the validation sample was 88%, indicating that the model performed well. CONCLUSIONS: : This study enhances the knowledge of the relationship of factors associated with pressure ulcers in adults in acute care populations and enhances the use and relative importance of particular Braden Scale sub-scales.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".