Evaluation of Clinical and Microbiological Characteristics of Foot Infections of Patients With Diabetes: Does Antibiotic Susceptibility Change?
Bibliographic record
Abstract
Background: The aim of the present study was to evaluate microorganisms isolated from foot ulcers of patients with diabetes, resistance profile and establish their relationship with amputation. Methods: The study included 51 patients with diabetes who were admitted due to foot ulcer. The ulcers were evaluated according to the Wagner-Meggitt classification system. The specimens obtained by deep-tissue biopsy, aspiration biopsy and/or samples of pus from purulent lesions were sent for culture. Empiric antibiotic was started after collection of samples for culture. Antibiotic therapy was modified according to antibiotic susceptibility test results. The data were analyzed using the SPSS 20 software. Results: Twelve females and 39 males were included in the study. The mean age of the patients was 63.1 ± 10.9 years, and duration of diabetes was 16.9 ± 6.9 years. Forty-six patients underwent amputation. The rate of amputation increased with the increasing Wagner grade (P = 0.002). Neuropathy was found in 98% of the patients and in all patients that underwent amputation. About 97% of patients with osteomyelitis had undergone amputation, and these relationships were significant statistically (P = 0.022). The most commonly isolated bacteria were as follows in order of frequency: E. faecalis 28 (13.5%); S. aureus 23 (11%); S. epidermidis 18 (8.6%). Poly microbial infection was detected in 54 of a total of 138 episodes of our patients. The rate of ciprofloxacin resistance was 35% in S. aureus and 40-74% in Gram-negative bacteria. The rate of clindamycin resistance was 47% in S. aureus. Conclusions: In our study, the most commonly isolated microorganisms exhibited a high rate of antibiotic resistance. J Endocrinol Metab. 2018;8(5):100-105 doi: https://doi.org/10.14740/jem525w
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".