Can venous and arterial leg ulcers be differentiated by the characteristics of the pain they produce?
Bibliographic record
Abstract
AIM: To explore the characteristics of venous and arterial leg ulcer pain among people cared for in the community. BACKGROUND: There is little information available concerning the different characteristics of pain resulting from venous and arterial leg ulcers. The identification of clear differences in pain experience might aid recognition of arterial deterioration and provide a useful adjunct for existing diagnostic procedures. DESIGN: This was a prospective interview-based survey. METHOD: Structured interviews were conducted with each of the participants in their home. Ulcer history, pain (McGill pain questionnaire and verbal rating scale) and factors influencing pain were assessed. RESULTS: Fifty-two women and 27 men aged 77.7 (SD 8.9) took part. Pain scores for least, average, worst and present pain varied widely, and arterial ulcers were associated with the highest average pain scores. Pain tended to be worst at night and least in the afternoon; arterial ulcers were more painful than venous ulcers on lying down. Venous leg ulcers were frequently described as throbbing, burning and itchy, while arterial ulcer pain tended to be described as sharp and hurting. CONCLUSIONS: Some characteristics of pain appeared to be suggestive of the leg ulcer type. Differences were found in the words chosen to describe the pain as well as the temporal and postural aspects of arterial and venous leg ulcer pain. More research is needed to confirm these preliminary findings. RELEVANCE TO CLINICAL PRACTICE: Patients' descriptions of pain have the potential to supplement other methods of differentiating between types of leg ulcer and provide an early-warning indicator for transition from venous to arterial ulceration.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".