Molecular epidemiology of Acinetobacter baumannii in central intensive care unit in Kosova teaching hospital
Bibliographic record
Abstract
Infections caused by bacteria of genus Acinetobacter pose a significant health care challenge worldwide. Information on molecular epidemiological investigation of outbreaks caused by Acinetobacter species in Kosova is lacking. The present investigation was carried out to enlight molecular epidemiology of Acinetobacter baumannii in the Central Intensive Care Unit (CICU) of a University hospital in Kosova using pulse field gel electrophoresis (PFGE). During March - July 2006, A. baumannii was isolated from 30 patients, of whom 22 were infected and 8 were colonised. Twenty patients had ventilator-associated pneumonia, one patient had meningitis, and two had coinfection with bloodstream infection and surgical site infection. The most common diagnoses upon admission to the ICU were politrauma and cerebral hemorrhage. Bacterial isolates were most frequently recovered from endotracheal aspirate (86.7%). First isolation occurred, on average, on day 8 following admission (range 1-26 days). Genotype analysis of A. baumannii isolates identified nine distinct PFGE patterns, with predominance of PFGE clone E represented by isolates from 9 patients. Eight strains were resistant to carbapenems. The genetic relatedness of Acinetobacter baumannii was high, indicating cross-transmission within the ICU setting. These results emphasize the need for measures to prevent nosocomial transmission of A. baumannii in ICU.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".