Health status utilities and the impact of pressure ulcers in long-term care residents in Ontario
Bibliographic record
Abstract
PURPOSE: To estimate health status utilities in long-term care (LTC) residents in Ontario, both with and without pressure ulcers (PUs), and to determine the impact of PU on health-related quality of life (HRQOL). METHODS: A retrospective population-based study was carried out using Minimum Data Set (MDS) health assessment data among all residents in 89 LTC homes in Ontario who had a full MDS assessment between May 2004 and November 2007. The Minimum Data Set-Health Status Index (MDS-HSI) was used to measure HRQOL. A stepwise regression was used to determine the impact of PU on MDS-HSI scores. RESULTS: A total of 1,498 (9%) of 16,531 LTC residents had at least one stage II PU or higher. The mean +/- SD MDS-HSI scores of LTC residents without PU and those with PU were 0.36 +/- 0.17 and 0.26 +/- 0.13, respectively (p < 0.001). Factors associated with lower MDS-HSI scores included: older age; being female; having a PU; recent hip fracture; multiple comorbid conditions; bedfast; incontinence; Changes in Health, End-stage disease and Symptoms and Signs; clinically important depression; treated with a turning/repositioning program; taking antipsychotic medications; and use of restraints. CONCLUSIONS: LTC residents with PU had slightly though statistically significantly lower HRQOL than those without PU. Comorbidity contributed substantially to the low HRQOL in these populations. Community-weighted MDS-HSI utilities for LTC residents are useful for cost-effectiveness analyses and help guide health policy development.
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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".