A Review of Clinical Outcomes Associated with Two Meropenem Dosing Strategies
Bibliographic record
Abstract
Meropenem is a carbapenem antibiotic that exhibits time-dependent bactericidal activity, traditionally dosed intravenously at 1 g every 8 h. In order to maximize its pharmacodynamic activity and reduce costs, an alternative regimen employed by many institutions is 500 mg every 6 h. The objective of this review was to summarize and evaluate published literature comparing clinical outcomes associated with these two meropenem dosing regimens. The literature was searched up to October 2016 using the MEDLINE, EMBASE, and Google Scholar databases. Three retrospective cohort studies were identified that compared clinical outcomes in general infectious disease patients (two studies) and patients with febrile neutropenia (one study). All studies reported no difference in clinical outcomes (clinical success, time to defervescence, sign or symptom resolution, length of stay, mortality, need for other antibiotics, and seizure rates). One study reported reduced economic costs with the alternative dosing. Interpretation of findings was primarily limited by small sample sizes and generalizability. Based on the data reviewed, the alternative dosing regimen of meropenem 500 mg intravenously every 6 h could be considered a therapeutic option. Future studies are needed to confirm the findings of this review, especially in high-risk populations such as immunocompromised patients or those with severe 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".