Combination of modified carbapenem inactivation method (mCIM) and EDTA-CIM (eCIM) for phenotypic detection of carbapenemase-producing Enterobacteriaceae
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Carbapenemase-resistant Enterobacteriaceae (CRE) cause many serious infections resulting in increasing treatment cost, prolonged hospitalization, and mortality rate. Reduced expression and/or mutations of porins and the presence of carbapenemase promote Enterobacteriaceae survival under carbapenem treatments. Development of accurate methods for the detection of antimicrobial resistance is required not only for therapy but also to monitor the spread of resistant bacteria or resistance genes throughout the hospital and community. In this study, we aimed to evaluate the phenotypic methods, Modified Hodge test (MHT), modified carbapenem inactivation method (mCIM), and EDTA-CIM (eCIM) for the detection of carbapenemase-producing Enterobacteriaceae (CPE). RESULTS: The results showed that mCIM had a sensitivity of 100% and a specificity of 100%, whereas the MHT had a sensitivity of 84.8% and a specificity of 97.8% for the 195 CRE isolates tested (105 CPE and 90 non-CPE isolates). The sensitivity of the mCIM/eCIM to detect metallo-carbapenemases in this study was 89.3% and the specificity was 98.7% as compared to the genotypic PCR detection. CONCLUSIONS: These findings indicate that the mCIM combined with eCIM is useful for detecting and distinguishing different types of carbapenemase in Enterobacteriaceae.
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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 it