Short‐course versus long‐course antibiotic treatment in patients with uncomplicated gram‐negative bacteremia: A systematic review and meta‐analysis
Bibliographic record
Abstract
WHAT IS KNOWN AND OBJECTIVE: Gram-negative bacteremia remains a major health problem around the world. The optimal duration of antibiotic treatment has been poorly defined, and there are significant differences of opinion between clinicians. We conducted this systematic review and meta-analysis to compare the clinical outcomes of short-course and long-course treatments in patients with uncomplicated gram-negative bacteremia. METHODS: We searched public databases (PubMed, EMBASE and Cochrane Library) to identify eligible studies. The primary outcomes were all-cause mortality and the incidence of recurrent bacteremia through day 30. We used the Cochrane risk of bias assessment tool to evaluate the risk of bias for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale for non-RCTs. RESULTS AND DISCUSSION: Six studies involving 2689 patients were included in the systematic review and meta-analysis. No significant difference was found between short-course and long-course antibiotic treatments in 30-day mortality (risk ratio [RR] 0.85; 95% confidence interval [CI] 0.65-1.13; P = .26), 30-day recurrent bacteremia (RR 1.07; 95% CI 0.68-1.67; P = .78), 90-day mortality (RR 0.84; 95% CI 0.57-1.24; P = .38), 90-day recurrent bacteremia (RR 0.98; 95% CI 0.50-1.89; P = .94), adverse events (RR 1.14; 95% CI 0.89-1.45; P = .30), Clostridium difficile infection (RR 0.86; 95% CI 0.40-1.86; P = .71) or resistance development (RR 1.19; 95% CI 0.66-2.14; P = .57). WHAT IS NEW AND CONCLUSION: Short-course was non-inferior to long-course antibiotic treatments for patients with uncomplicated gram-negative bacteremia. Considering the drug-related side effects and cost-effectiveness, a shorter duration of antibiotic treatment may be preferable for this particular population. However, additional high-quality RCTs are needed to further assess whether a shorter course of antibiotic treatment is of greater benefit for patients with uncomplicated gram-negative bacteremia.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.045 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".