Wound outcomes in patients with advanced illness
Bibliographic record
Abstract
A prospective case series was studied to assess the potential for complete healing of wounds among patients with advanced illness referred to a regional palliative care program in Toronto, Canada. Two hundred and eighty-two patients, of which 148 were primarily diagnosed with cancer and 134 with non cancer advanced illness, were assessed and followed until their deaths. On the baseline initial referral date, 823 wounds were documented. The wound classes assessed included pressure ulcers, malignant wounds, skin tears, venous leg ulcers, diabetic foot ulcers and arterial leg/foot ulcers. Proportions of patients showing complete healing of at least one wound were calculated, stratified by patient's survival time post-baseline (1 week, 1 month, 3 months and 6 months). Proportions of patients showing complete healing of at least one wound increased the longer patients lived and ranged between 12·9% and 43·5% for stage I pressure ulcers, 0% and 60% for stage II pressure ulcers, 2·4% and 100% for skin tears, 10% and 100% for venous leg ulcers and 0% and 50% for diabetic foot ulcers. Only one person showed complete healing of a stage III pressure ulcer and no complete healing was observed with stage IV pressure ulcers, unstageable pressure ulcers, malignant wounds and arterial leg/foot ulcers.
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 | 0.002 |
| 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 | 0.001 | 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".