Laboratory Detection of Enterobacteriaceae That Produce Carbapenemases
Bibliographic record
Abstract
A study was designed to evaluate the modified Hodge test (MHT), Mastdiscs ID inhibitor combination disks (MDI), Rosco Diagnostica Neo-Sensitabs (RDS), metallo-β-lactamase (MBL) Etest, and in-house multiplex PCR for the detection of well-characterized carbapenemase-producing Enterobacteriaceae. One hundred forty-two nonrepeat clinical isolates of carbapenemase-producing Enterobacteriaceae (including Klebsiella spp., Escherichia coli, Citrobacter freundii, and Enterobacter spp.) obtained from the SMART worldwide surveillance program during 2008 to 2009 were included. These included 49 KPC-, 27 NDM-, 19 VIM-, 14 OXA-48-like enzyme-, and 5 IMP-producing isolates and 28 carbapenem-resistant, carbapenemase-negative isolates. The manufacturer's instructions were followed for MDI, RDS, and MBL Etest and CLSI guidelines for MHT. A multiplex PCR was designed to detect KPC, NDM, VIM, IMP, and OXA-48-like carbapenemases. Overall, the sensitivity and specificity were 78% and 93% for MDI, 80% and 93% for RDS, 58% and 93% for MHT, and 55% and 100% for MBL Etest, respectively. The PCR had 100% sensitivity and specificity. MDI and RDS performed well for the detection of KPCs and NDMs but poorly for VIMs, IMPs, and OXA-48-like enzymes. MHT performed well for KPCs and OXA-48-like enzymes but poorly for NDMs, VIMs, and IMPs. MDI and RDS were easy to perform and interpret but lacked sensitivity for OXA-48-like enzymes, VIMs, and IMPs. MHT and MBL Etest were often difficult to interpret. We recommend using molecular tests for the optimal detection of carbapenemase-producing Enterobacteriaceae.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".