Exploration of pressure ulcer and related skin problems across the spectrum of health care settings in Ontario using administrative data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This is a prospective cohort study using population-level administrative data to describe the scope of pressure ulcers in terms of its prevalence, incidence risk, associating factors and the extent to which best practices were applied across a spectrum of health care settings. The data for this study includes the information of Ontario residents who were admitted to acute care, home care, long term care or continuing care and whose health care data is contained in the resident assessment instrument-minimum data set (RAI-MDS) and the health outcomes for better information and care (HOBIC) database from 2010 to 2013. The analysis included 203 035 unique patients. The overall prevalence of pressure ulcers was approximately 13% and highest in the complex continuing care setting. Over 25% of pressure ulcers in long-term care developed one week after discharge from acute care hospitalisation. Individuals with cardiovascular disease, dementia, bed mobility problems, bowel incontinence, end-stage diseases, daily pain, weight loss and shortness of breath were more likely to develop pressure ulcers. While there were a number of evidence-based interventions implemented to treat pressure ulcers, only half of the patients received nutritional interventions.
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.
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 | 0.004 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it