The effectiveness of pressure ulcer risk assessment instruments and associated intervention protocols remains uncertain
Bibliographic record
Abstract
Commentary on: Chou R, Dana T, Bougatsos C, et al. Pressure ulcer risk assessment and prevention: a systematic comparative effectiveness review. Ann Intern Med 2013;159:28–38.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Pressure ulcers affect up to three million adults in the USA and are associated with deterioration in quality of life and overall prognosis, and substantial increases in resource utilisation and costs. Prevention is likely more effective and less costly than treatment of pressure ulcers once they have developed,1 ,2 so is a priority for health systems. The study set out to ascertain four things: (1) whether the use of risk assessment tools was effective in reducing the incidence or severity of pressure ulcers; (2) whether the effectiveness of these risk assessment tools varied according to setting of care or patient characteristics; (3) the effectiveness of a variety of preventive interventions in at-risk patients and (4) whether there is … [1]: {openurl}?query=rft.jtitle%253DAnn%2BIntern%2BMed%26rft.volume%253D159%26rft.spage%253D28%26rft_id%253Dinfo%253Adoi%252F10.7326%252F0003-4819-159-1-201307020-00006%26rft_id%253Dinfo%253Apmid%252F23817702%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.7326/0003-4819-159-1-201307020-00006&link_type=DOI [3]: /lookup/external-ref?access_num=23817702&link_type=MED&atom=%2Febmed%2F19%2F3%2F93.atom [4]: /lookup/external-ref?access_num=000321516200004&link_type=ISI
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.092 | 0.587 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.009 | 0.003 |
| Research integrity | 0.016 | 0.014 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".