Infections Due to Acinetobacter baumannii–calcoaceticus Complex: Escalation of Antimicrobial Resistance and Evolving Treatment Options
Bibliographic record
Abstract
Abstract Bacteria within the genus Acinetobacter (principally A. baumannii–calcoaceticus complex [ABC]) are gram-negative coccobacilli that most often cause infections in nosocomial settings. Community-acquired infections are rare, but may occur in patients with comorbidities, advanced age, diabetes mellitus, chronic lung or renal disease, malignancy, or impaired immunity. Most common sites of infections include blood stream, skin/soft-tissue/surgical wounds, ventilator-associated pneumonia, orthopaedic or neurosurgical procedures, and urinary tract. Acinetobacter species are intrinsically resistant to multiple antimicrobials, and have a remarkable ability to acquire new resistance determinants via plasmids, transposons, integrons, and resistance islands. Since the 1990s, antimicrobial resistance (AMR) has escalated dramatically among ABC. Global spread of multidrug-resistant (MDR)-ABC strains reflects dissemination of a few clones between hospitals, geographic regions, and continents; excessive antibiotic use amplifies this spread. Many isolates are resistant to all antimicrobials except colistimethate sodium and tetracyclines (minocycline or tigecycline); some infections are untreatable with existing antimicrobial agents. AMR poses a serious threat to effectively treat or prevent ABC infections. Strategies to curtail environmental colonization with MDR-ABC require aggressive infection-control efforts and cohorting of infected patients. Thoughtful antibiotic strategies are essential to limit the spread of MDR-ABC. Optimal therapy will likely require combination antimicrobial therapy with existing antibiotics as well as development of novel antibiotic classes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".