Common foot examination features of 247 Iranian patients with diabetes
Bibliographic record
Abstract
BACKGROUND: Iran is a Middle Eastern country with a 70 million population. There are 3 million Iranians with diabetes mellitus (DM) and there is a high incidence of non traumatic amputation in this population. Amputation is often preceded by foot deformity or ulceration. We evaluated the routine foot examination of persons with diabetes (PWD) attending an outpatient Diabetic Clinic to identify the clinical characteristics that might be early warning signs of individuals at a high risk of developing a foot ulcer or having a subsequent non traumatic amputation. METHODS: A prospective, descriptive, clinic-based study was conducted on 247 patients with diabetes mellitus in 2005. The objectives of the study were to define the abnormal features of the foot examination in PWD which could be risk factors for ulceration or amputation. RESULTS: The mean age of patients with diabetes was 52 +/- 12. The prevalence of callus in the enrolled patients was 12% and heel fissures were noted in 50%. There was a significant relationship between callus formation and the absence of tibialis posterior pulse (odds ratio 5), the presence of the hammer toe deformity (odds ratio 4), and foot ulceration (odds ratio 3). The prevalence of foot ulcers in PWD was 4%. CONCLUSION: A diabetic screening program identifying callus formation, absent pulses, and hammer toe are important early signs of individuals at an increased risk for foot ulcers. This program will facilitate early treatment to decrease the loss of limbs.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".