Evaluation of the rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test for rapid colistin resistance detection in lactose non-fermenting Gram-negative bacteria
Bibliographic record
Abstract
Introduction. Colistin is one of the last-resort antibiotics for treating multidrug-resistant (MDR) or extensively drug-resistant (XDR) lactose non-fermenting Gram-negative bacteria such as Pseudomonas aeruginosa and Acinetobacter baumannii . Gap Statement. As the rate of colistin resistance is steadily rising, there is a need for rapid and accurate antimicrobial susceptibility testing methods for colistin. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test has recently been developed for rapid detection of colistin resistance in P. aeruginosa and A. baumannii . Aim. The present study aimed to evaluate the performance of the Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test in comparison with the reference broth microdilution (BMD) method. Methodology. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test was performed using a total of 135 P . aeruginosa (17 colistin-resistant and 118 colistin-susceptible) and 66 A. baumannii isolates (32 colistin-resistant and 34 colistin-susceptible), in comparison with the reference BMD method. Results. The categorical agreement of the Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test with the reference BMD method was 97.5 % with a major error rate of 0 % (0/152) and a very major error (VME) rate of 10.2 %. The VME rate was higher (23.5 %) when calculated separately for P. aeruginosa isolates. The overall sensitivity and specificity were 89.8 and 100 %, respectively. Conclusion. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test performed better for A. baumannii than for P. aeruginosa .
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How this classification was reachedexpand
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 | 0.004 | 0.009 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".