EVALUATAION OF THE DIABETIC FOOT – WHY, WHEN AND HOW?
Bibliographic record
Abstract
The diabetic foot syndrome consists of a heterogenous group of pathological conditions caused bydiabetes such as: somatic and autonomous neuropathy, diabetic micro and macroangiopathy, structural injuriesof the bones and their lesions, wounds (ulcers) and skin lesions of the foot, as well as various combinations ofall of the aforementioned symptoms. Treatment of the ulcers of the diabetic foot is the leading cause for hospitaladmittance in these patients. Amputations in diabetes ill patients are 25 times more often compared to others,and 85% of them begin with foot ulcers. The peripheral neuropathy and arterial disease are the most commonreasons for diabetic foot occurrence. Early detection in these patients through programmed clinicalexaminations, control of vascular status with doppler and duplex sonography, detection of reduced and lostprotective sensibility with 10 gram Semmes – Weinstein 5,07 monofilament, assessment of the vibratorysensitivity with biothesiometer or vibrating tuning fork, enabling categorization, and risk stratification fordiabetic foot. Patients that step inadequately, had previous amputations or there is suspicion of congenitaldeformities of the feet should undergo tests such as podoscopy, podometry, which will detect parts of the footthat are under the biggest pressure, and are potential areas for future ulcers. These techniques are useful indetermining which insoles should be used to compensate the appropriate malformation. All these paremetersenable categorization and diagnosing patients with low, medium, high or very high risk for foot ulcers. Based onthis stratification, with protocol is conducted adequate prevention and therapy. There are brochures that informpatients about the type of the disease, the harm of the disease, possible complications and ways to prevent them.Experiences in Canada and Australia have confirmed that routine examinations and risk stratification reduce thenumber of amputations in the period of 10 years for about 50%. Considering that this preventive program inMacedonia is not routinely conducted , there are actions that need to be implemented in order to manage thisprogram and improve the status of the patients with diabetic foot who till now have lost precious time from oneto other clinic before appropriate diagnostic and therapy is made. Program that covers the forming of a centerfor diabetic foot, creating a database of patients with diabetic foot, compulsory preventive examinations, riskcategorization for foot ulcers, education of patients and printing leaflets and brochures for informing, with thegoal to reduce the forming of ulcers and amputations in the diabetic foot, which would contribute this categoryof patients to live a long life with no complications and handicap.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".