Resistance among Gram-negative ESKAPE pathogens isolated from hospitalized patients with intra-abdominal and urinary tract infections in Latin American countries: SMART 2013–2015
Bibliographic record
Abstract
Gram-negative ESKAPE pathogens (Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are important etiologic agents of nosocomial infection that are frequently resistant to broad-spectrum antimicrobial agents. Gram-negative ESKAPE pathogens were collected from hospitalized patients in 11 Latin American countries from 2013 to 2015 as part of the Study for Monitoring Antimicrobial Resistance Trends (SMART) global surveillance program. In total, 2113 isolates from intra-abdominal infections (IAI) and 970 isolates from urinary tract infections (UTI) were tested against antimicrobial agents using standardized CLSI broth microdilution methodology. Of the agents tested, amikacin demonstrated the highest rates of susceptibility (%) for K. pneumoniae (92.2, 92.3), Enterobacter spp. (97.5, 92.1), and P. aeruginosa (85.3, 75.2) isolates from both IAI and UTI, respectively. Ertapenem (68.5, 62.6) and imipenem (79.2, 75.9) showed substantially higher rates of susceptibility (%) than other β-lactams, including piperacillin-tazobactam (35.9, 37.4) against ESBL-positive isolates of K. pneumoniae from IAI and UTI, respectively. Rates of susceptibility to all agents tested against A. baumannii were ≤30.9%. Gram-negative ESKAPE pathogens isolated from Latin America demonstrated compromised in vitro susceptibility to commonly prescribed broad-spectrum, parenteral antimicrobial agents. Continued surveillance is warranted. New antimicrobial agents with potent activity against Gram-negative ESKAPE pathogens are urgently needed.
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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 | 0.001 |
| 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".