Shorter versus longer-duration antibiotic treatments for immunocompetent patients with bloodstream infections: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: The optimal duration of antibiotic treatment for bloodstream infections remains uncertain. This study aimed to compare the efficacy and safety of shorter versus longer duration antibiotic treatment for immunocompetent patients with bloodstream infections. Methods: We searched Medline, Embase, and Cochrane Central Register of Controlled Trials without language restrictions for randomized controlled trials (RCTs) published between database inception and 25 November 2024, comparing shorter-duration antibiotic treatments with longer-duration antibiotic treatments in patients with bloodstream infections with a minimum difference of 3 days in duration of therapy. We employed random-effects meta-analyses to summarize the evidence. We used the mean difference (MD) with 95% confidence intervals (CIs) for continuous outcomes. For dichotomous outcomes, we used the odds ratios (ORs) or risk ratios (RRs) with 95% CIs. We used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework to assess the certainty of evidence. This study is registered with Open Science Framework (https://osf.io/egs8q). Findings: Eleven RCTs published between 2006 and 2025, involving a total of 5505 participants, proved eligible. There are probably little or no differences in mortality (RR 0.91, 95% CI 0.79-1.05; moderate certainty), treatment failure (RR 1.08, 95% CI 0.69-1.68; moderate certainty), and relapse rates (RR 1.15, 95% CI 0.82-1.63; moderate certainty) between shorter- and longer-duration antibiotics. Compared with longer-duration antibiotics, shorter-duration antibiotics do not increase hospital readmission (RR 0.91, 95% CI 0.75-1.1; high certainty), but reduce the length of hospital stay (MD -3.04, 95% CI -3.9 to -2.18; high certainty). With very low certainty evidence, we are uncertain whether shorter-duration antibiotics decrease any adverse events (RR 1.0, 95% CI 0.76-1.32) and serious adverse events (RR 0.67, 95% CI 0.39-1.14) compared with longer-duration antibiotics. Interpretation: Shorter- and longer-duration antibiotics show similar efficacy for bloodstream infections, with shorter courses reducing hospital stay. Consistent effects were observed across age groups and bacterial types, but cautious interpretation is needed due to limited subgroup data. Funding: None.
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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 | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.047 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".