Pharmacodynamic profiling of fluoroquinolones in Community Acquired Pneumonia (CAP) patients: Dose and age stratification study
Bibliographic record
Abstract
Objective: This study aimed to assess the probability of Levofloxacin (Levo) compared to Gatifloxacin (Gati) achieving favorable pharmacodynamic (PD) targets for bacterial eradication and prevention of resistance development in S. pneumoniae in both elderly (≥65 years) and younger (<65 years) patients with Community Acquired Pneumonia (CAP). Material and Methods: As part of a study comparing the clinical outcome of Levo vs. cefuroxime + erythromycin in hospitalized patients with CAP, demographics including age, weight, gender, race and renal function were gathered and analyzed from 263 elderly (≥65 years) and 48 younger patients (<65 years). Previously described and validated population pharmacokinetic (PK) models of levo and gati in patients with CAP were utilized. Free-drug AUC0-24 (f AUC0-24)were simulated in plasma (P) using Levo dosing at 500mg, 750mg and 1000mg OD as well as Gati 200mg and 400mg OD. Use of Monte Carlo simulation allowed for the full variability of encountered drug clearance to be incorporated. S. pneumoniae susceptibility data were obtained from the Canadian Respiratory organism Susceptibility Study (CROSS) study (an annual, national, ongoing surveillance study which has collected 8014 isolates from 1997-2004). Results: Probability of target attainment (f AUC0-24/MIC of 30) of Levo and Gati will be discussed. Conclusions: For all patients and for elderly hospitalized patients with CAP, Levo 750mg and Gati 400mg showed high probability for target attainment of f AUC0-24/MICall of 30. Ayman M. Noreddin, Clinic Pharmacol Biopharmaceut 2013, 2:3 http://dx.doi.org/10.4172/2167-065X.S1.002
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".