The characteristics of wound pain associated with diabetes-related foot ulcers: A pilot study
Bibliographic record
Abstract
There is increasing evidence that people with diabetes-related foot ulcers (DRFU) can experience pain related to their wound. A cross-sectional pilot study was conducted to examine and compare the prevalence, intensity and nature of DRFU pain in people with neuropathic, neuroischaemic and ischaemic wound aetiologies. A questionnaire incorporating pain assessment tools, the Short-form McGill Pain Questionnaire and the Short-form Brief Pain Inventory was used to interview 15 patients with DRFU. Descriptive analyses were conducted. The mean age was 64 years, 60% had neuropathic ulcers and 40% had neuroischaemic ulcers. No ischaemic DRFU were observed in the study sample. Formal assessment tools had a higher reported pain prevalence (53%) compared with a single question asked by the researcher (33%). Low scores for pain intensity and effect of pain on health-related quality of life were reported for both aetiologies. This study indicates people with DRFU can experience wound pain, despite analgesia usage. It also highlights that clinical pain assessment and management techniques appear inadequate. A larger study is warranted to investigate characteristics of DRFU pain, to determine if statistical differences in pain experiences exist between wound aetiologies and to develop guidelines for assessment and management of wound pain.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".