Evaluating Outcomes of Alternative Dosing Strategies for Cefepime
Bibliographic record
Abstract
OBJECTIVE: To perform a qualitative systematic review of the evidence comparing traditional with prolonged intermittent or continuous infusions of cefepime based on clinical and pharmacodynamic outcomes. DATA SOURCES: PubMed (1946 to October 2014), EMBASE (1980 to October 2014), CENTRAL, Cochrane Database of Systematic Reviews, Web of Science, and International Pharmaceutical Abstracts (1970 to October 2014) were searched using the terms cefepime, pharmacokinetics, pharmacodynamics, drug administration, intravenous infusions, intravenous drug administration, continuous infusion, extended infusion, and intermittent therapy. Reference lists from relevant materials were reviewed. STUDY SELECTION AND DATA EXTRACTION: Articles evaluating administration regimens of cefepime, one of which included the traditional, manufacturer-recommended 0.5-hour infusion and the other a prolonged or continuous infusion were included. Prespecified clinical outcomes of interest included all-cause mortality, length of hospital stay, clinical cure, and adverse events. The primary pharmacodynamic outcome was percentage time of unbound drug concentration remaining above the minimum inhibitory concentration. DATA SYNTHESIS: In all, 18 studies were included; 6 studies assessed clinical outcomes, and 12 assessed pharmacodynamic outcomes. Prolonged or continuous infusions of cefepime achieved the pharmacodynamic targets more often than traditional infusions. The association of improved clinical outcomes with prolonged or continuous infusions is unclear. All-cause mortality was significantly decreased with the use of a prolonged cefepime infusion in a retrospective study. Two prospective, randomized studies demonstrated no statistically significant difference in mortality between prolonged and intermittent infusions. CONCLUSIONS: The available literature on prolonged and continuous infusions of cefepime demonstrated an improved achievement of pharmacodynamic targets; however, the effect on clinical outcomes is inconclusive. Well-designed prospective studies are required to determine optimal dosing and administration strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.088 | 0.222 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".