Challenges in the Management of Community-Acquired Pneumonia: The Role of Quinolones and Moxifloxacin
Bibliographic record
Abstract
Current strategies and guidelines for the treatment of community-acquired pneumonia are directed toward making care cost effective, by treating patients on an outpatient basis whenever possible. The use of the new fluoroquinolones could help to achieve these goals. These agents are highly bioavailable and can facilitate the oral treatment of certain patients who otherwise might be admitted to the hospital, as outpatients. The good absorption and bioavailability of these agents can allow moderately ill patients to rapidly achieve effective serum levels of the drug after oral administration and can also facilitate early discontinuation of intravenous therapy and early discharge for responding inpatients. For inpatients or outpatients with clinical risk factors for acquiring drug-resistant pneumococci, quinolones represent a reliable monotherapy option and an effective alternative to a beta-lactam/macrolide combination. Although the in vitro differences among the various quinolones remain of unclear clinical relevance, preliminary data suggest that agents with enhanced in vitro activity against pneumococci, such as moxifloxacin, may have greater clinical efficacy and may lead to more-rapid resolution of fever and, potentially, less selection of future pneumococcal resistance to quinolones than that associated with agents with less intrinsic activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".