DIABETIC FOOT ULCERS MICROBIOLOGICAL STUDY
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES \nInfections of all types are more common in patients with diabetes, on the basis of outcome of retrospective study in Canada. \nMany types of infections are very common in diabetic than non-diabetic patients. Foot is the most common site. Diabetic foot \ninfections range from mild infections to limb threatening conditions. Most require emergency medical attention. Diabetic foot \ninfection is a global burden and projected to increase from 246 million people to over 380 million people by the year 2025. \nMany people with diabetes develop complications that seriously affect their quality and length of life. Lower limb complications \nare common, particularly foot ulcers and gangrene. Development of these complications is attributed to individual risk factors, \npoverty, racial and ethnic differences, and quality of local and national health care systems. The wide variations noted suggest \nthat best practices in low incidence areas could easily be adapted in high incidence areas to reduce the burden of complications. \nAlmost every infection begins in a wound, often as neuropathic ulceration or a traumatic break in the skin. Infections that \nbegin as a small problem may progress to involve soft tissue, bones and joints. \nBecause of these morbidity and occasional mortality by these foot infections several authoritative groups have recently \ndeveloped guidelines for assessing and treating diabetic foot. \nMETHODOLOGY \n100 Diabetic patients with foot ulcers were admitted and wounds were classified using wagner’s classification. Pus was sent \nfor culture and sensitivity and treated accordingly. \nRESULTS \nIn our study the most common organism cultured from the wound with diabetes mellitus was staphylococcus. The most \nsensitive drug for these organisms was found to be chloramphenicol on most occasions. \nCONCLUSION \nThe rationale of pus culture and sensitivity is not only to definitively treat the diabetic wound after the culture sensitivity report \nis available, but also to treat the wounds in places where the culture sensitivity facilities are not available or delayed. So as to \ntarget commoner organisms with the drugs which are sensitive on more occasions so as to avoid drug resistance and in a cost \neffective manner. \n
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".