Bacteriological profiles of diabetic ulcers in cases of major limb amputation: insights from Solomon Islands
Bibliographic record
Abstract
Objective: Solomon Islands, a Western Pacific nation, faces a growing burden of type II diabetes amid chronic healthcare shortages. Surgeons report increased incidence of diabetic amputations; however, data on infection rates and pathology remain scarce. This study describes the microbiology of diabetic ulcers in cases of major limb amputation. Method: Demographic, microbiological and outcome data were extracted from records of patients with diabetes who underwent major limb amputation from 2018–2023 in Solomon Islands. Results: Among 356 adults who underwent major limb amputation, microbiological data were available for 113 (32%). Pus and tissue cultures identified 20 bacterial species—predominantly Pseudomonas aeruginosa (n=27; 24%), mixed enteric organisms (n=25; 23%) and Klebsiella pneumoniae (n=18; 16%). Meticillin-resistant Staphylococcus aureus was identified in one patient. Antibiotic resistance was observed in 62 (55%) cultures, with the highest resistance rates against: ampicillin (31 cases); amoxicillin (31 cases); gentamicin (21 cases); and trimethoprim/sulfamethoxazole (21 cases). Escherichia coli, Klebsiella pneumoniae and Enterococcus spp. were significantly associated with resistance. Conclusion: The bacterial diversity and high resistance rates identified in this study are concerning given limited access to next-generation antibiotics in Solomon Islands. Further research is needed to evaluate infection management, resistance drivers and clinical outcomes of antibiotic-resistant infections in Solomon Islands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".