Emergence of Antimicrobial Resistance among Pseudomonas aeruginosa: Implications for Therapy
Bibliographic record
Abstract
Pseudomonas aeruginosa (PA), a nonlactose fermenting gram-negative bacillus, is a common cause of nosocomial infections in critically ill or debilitated patients, particularly ventilator-associated pneumonia (VAP), and infections of bloodstream, urinary tract, intra-abdominal, wounds/skin/soft tissue. PA rarely affects healthy individuals, but may cause serious infections in patients with chronic structural lung disease, comorbidities, advanced age, impaired immune defenses, or with medical devices (e.g., urinary or intravascular catheters, foreign bodies). Treatment of pseudomonal infections is difficult, as PA is intrinsically resistant to multiple antimicrobials, and may acquire new resistance determinants even while on antimicrobial therapy. Mortality associated with pseudomonal VAP or bacteremias is high (> 35%) and optimal therapy is controversial. Over the past three decades, antimicrobial resistance among PA has escalated globally, via dissemination of several international multidrug-resistant “epidemic” clones. We review the emergence of antimicrobial resistance to this pathogen, and discuss approaches to therapy (both empirical and definitive).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".