Prevalence of Lower-Limb Ulceration: A Systematic Review of Prevalence Studies
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of leg ulcers reported in the literature. DESIGN: A systematic review of prevalence studies of lower-limb ulceration in the adult population was conducted. Critical appraisal of the research papers was guided by published standards for methodologic review of prevalence studies, which were modified to address the issues related to leg ulcers. MAIN RESULTS: Twenty-two reports of prevalence studies were identified. Eight population-based prevalence studies used clinical validation and reported prevalence rates of open ulcers ranging from 0.12% to 1.1% of the population; the prevalence rate of open or healed ulcers was reported to be 1.8%. Seven population-based studies without clinical validation reported prevalence rates of open ulcers ranging from 0.12% to 0.32% of the population. Differences in the populations studied, study design, ulcer definition, ulcer etiology, inclusion of foot ulcers, method of clinical assessment, and clinical validation of ulcer cases indicate that it is inappropriate to pool the estimates of prevalence. In most studies that considered age and sex, the prevalence of ulcers increased with age and was higher for women. CONCLUSIONS: Better-quality prevalence studies are needed. These studies should clearly define the populations being studied, include large numbers of individuals and total populations, provide a clear definition of an ulcer, describe case identification procedures, and clinically confirm the presence of 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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".