Ceftazidim-avibactam susceptibility of carbapenemase producing enterobacterales in an OXA-48 endemic area
Bibliographic record
Abstract
Carbapenem-resistant Enterobacterales (CRE) are included in the critical priority pathogens by WHO. OXA-48 is the predominating carbapenemase in Türkiye, in where carbapenem resistance rates are high, particularly in Klebsiella pneumoniae isolates. Ceftazidime-Avibactam (CAZ-AVI) has been used successfully in CRE infections in recent years, but resistance is reported to be on the rise. To evaluate the susceptibility to CAZ-AVI in CRE isolates and association of CAZ-AVI resistance and carbapenemase genes. CRE isolates from various clinical samples between January 2022 and June 2024 were included in the study. The isolates were identified by VITEK-MS(bioMerieux, France) system. Antibiotic susceptibilities were determined by VITEK COMPACT 2(BioMerieux, France) and CAZ-AVI susceptibility was evaluated by disk diffusion method(Oxoid, Thermo Fisher Scientific, Canada) according to EUCAST criteria. Carbapenemase genes were investigated in 324 representative isolates using Biospeedy Carbapenem-Resistance qPCR kit(Bioeksen, Türkiye). The study included 429 CRE isolates. The distribution of CAZ-AVI susceptibility of CRE isolates according to sample type and clinics is shown in Table 1 and Table 2. CAZ-AVI susceptibility of isolates according to carbapenemase genes is presented in Table 3. In total, CAZ-AVI susceptibility of CRE isolates was 76%, while it was 99.5% in non-metallo-beta-lactamase (MBL) producers and 100% in only OXA-48-like producers. Despite the increasing resistance in CRE isolates, CAZ-AVI is still a good option for treatment. CAZ-AVI was found to be highly effective particularly in isolates with non-MBL carbapenemase genes. Early detection of carbapenemase type is important in predicting CAZ-AVI susceptibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".