<i>In Vitro</i> Activity of Sulbactam-Durlobactam against Global Isolates of <i>Acinetobacter baumannii</i> - <i>calcoaceticus</i> Complex Collected from 2016 to 2021
Bibliographic record
Abstract
activity of sulbactam-durlobactam was maintained across individual ABC species, years, global regions of collection, specimen sources, and resistance phenotypes, including MDR and extensively drug-resistant (XDR) isolates. At 4 μg/mL (preliminary sulbactam-durlobactam susceptible MIC breakpoint), sulbactam-durlobactam inhibited 98.3% of all ABC isolates and >96% of sulbactam-, imipenem-, ciprofloxacin-, amikacin-, and minocycline-non-susceptible isolates; as well as colistin-resistant, MDR, and XDR isolates. Most imipenem-non-susceptible ABC isolates (96.8%, 2,488/2,570) were carbapenem-resistant A. baumannii (CRAB); 96.9% (2,410/2,488) of CRAB isolates were sulbactam-durlobactam-susceptible. More than 80% of ABC isolates had sulbactam-durlobactam MIC values that were ≥2 doubling-dilutions (4-fold) lower than sulbactam alone. Only 1.7% (84/5,032) of ABC isolates from 2016 to 2021 had sulbactam-durlobactam MIC values of >4 μg/mL. Of the 84 isolates, 94.0% were A. baumannii, 4.8% were A. pittii, and 1.2% were A. nosocomialis. In summary, sulbactam-durlobactam demonstrated potent antibacterial activity against a 2016 to 2021 collection of geographically diverse clinical isolates of ABC isolates, including carbapenem-non-susceptible and MDR isolates.
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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 | 0.000 | 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 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".