Molecular epidemiology of Clostridium difficile infection in Iranian hospitals
Bibliographic record
Abstract
Clostridium difficile infection (CDI) is known as one of the most important causes of nosocomial infections. The main objective of this study was to evaluate the presence of Clostridium difficile in the stool of hospitalized patients with diarrhea as well as in their environments. C. difficile isolates were characterized according to the presence of toxin genes and antibiotic resistance. Multilocus Sequence Typing Analysis (MLST) was applied for finding the genetic polymorphism and relationship among strain lineages. A total of 821 samples (574 stools and 247 swabs) were collected between April 2015 and May 2017. The prevalence of C. difficile isolates was 28.6% (164/574) in patients and 19% (47/247) in swabs taken from medical devices, hands of healthcare workers and skin patient sites. Finally, 11.5% (66/574) toxigenic C. difficile strains isolated from stool samples of inpatients and 4.4% (11/247) from hands of healthcare workers and skin patient sites. All the toxigenic isolates were inhibited by a low concentration of vancomycin (MIC < 0.5 μg/ml). About 43% (33/77) and 39% of isolates were resistant to Clindamycin and moxifloxacin respectively. All isolates were susceptible to metronidazole. Toxigenic C. difficile strains were analyzed by MLST and were divided into 4 different STs. The detected types were ST-54 (57.9%), followed by ST-2 (31.6. %), ST-15 (5.3%) and ST-37 (5.3%), while none of the isolates were identified as ST-1 or ST-11. Significant risk factors for CDI appear to be advanced age, undergoing chemotherapy, previous surgery, and residence in the nursing home. CDI is common in Iran and further studies are recommended to monitor its epidemiological variations. Moreover, greater attempts must be made to encourage antibiotic stewardship by healthcare workers and the public.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".