Integrating pharmacokinetics, pharmacodynamics and MIC distributions to assess changing antimicrobial activity against clinical isolates of Pseudomonas aeruginosa causing infections in Canadian hospitals (CANWARD)
Bibliographic record
Abstract
OBJECTIVES: To study antimicrobial pharmacodynamic (PD) activity over time against clinical isolates of Pseudomonas aeruginosa in Canadian hospitals. METHODS: Integrated pharmacokinetic (PK)/PD analyses with Monte Carlo simulations were used to study cefepime, meropenem, piperacillin/tazobactam, ciprofloxacin, amikacin, gentamicin and colistin. Profiles of P. aeruginosa infections were modelled using CANWARD data from January 2007 to June 2012 inclusive. The probability of target attainment (PTA) was the proportion of cases achieving a %ƒT>MIC ≥ 50% for cefepime, meropenem and piperacillin/tazobactam, an ƒAUC/MIC ≥ 90 for ciprofloxacin and the aminoglycosides, and a total AUC/MIC ≥ 60 for colistin. RESULTS: Some 2126 P. aeruginosa isolates were identified. There were no significant trends over time in the PTA for cefepime (0.93-1.0), meropenem (0.89-0.92) or piperacillin/tazobactam (0.74-0.79) (data shown for the highest recommended doses). The PD activity for ciprofloxacin (PTA 0.48-0.64) was variable. There were notable improvements in the PTA for amikacin (from 0.21 to 0.55, P = 0.027), gentamicin (from 0.10 to 0.51, P = 0.035) and colistin (from 0.04 to ~0.20, P = 0.05), which were not reliably detected by MIC indices. There was a decline over time in the PTA for piperacillin/tazobactam from 0.73 to 0.61 against P. aeruginosa isolated from intensive care units (ICUs) (Pearson correlation coefficient -0.99, P = 0.003). Neither MIC50 nor MIC90 detected this reduction in PD activity. CONCLUSIONS: The overall PD activity against P. aeruginosa was stable from 2007 to 2012 for cefepime, meropenem and piperacillin/tazobactam, was variable and unreliable for ciprofloxacin, and improved significantly but remained relatively low for the aminoglycosides and colistin. There was a progressive reduction over time in the PD activity of piperacillin/tazobactam against ICU isolates, which was not detected by simply assessing MIC indices.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".