Antimicrobial susceptibility and combination testing of invasive<i>Stenotrophomonas maltophilia</i>isolates
Bibliographic record
Abstract
BACKGROUND: Treatment of invasive Stenotrophomonas maltophilia infections is difficult due to this organism's inherent multidrug resistance and increasing resistance to trimethoprim-sulfamethoxazole via acquisition of the sul genes. METHODS: In vitro antibiotic susceptibility testing was performed using a customized broth microdilution panel. Combination testing for tigecycline with anti-Stenotrophomonas agents (i.e. colistin, ticarcillin-clavulanate, ceftazidime, and levofloxacin) was done using the cross Etest method. Genotyping was done using automated repetitive PCR. RESULTS: A total of 90 patients with invasive S. maltophilia infections included: (79%) adults, and 21% children or infants [6/12 (50%) cases occurred in infants aged ≤ 1 year.]. S. maltophilia isolates were recovered from blood (69%), lower respiratory (21%) or other sites (CSF, peritoneal fluid) (11%). Seventeen percent of the isolates were SXT-R, and also demonstrated multi-drug resistant to two or more antibiotic classes. Minocycline, tigecycline and colistin had the best in vitro activities. The combination testing of tigecycline and colistin gave the best results; 12 isolates were tested and synergy occurred in 3 isolates while an additional 7 isolates showed additive results. CONCLUSIONS: We recommend further evaluation with killing assays and clinical studies to evaluate the effectiveness of tigecycline and colistin combination for invasive S. maltophilia infections.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".