β-lactam antibiotic versus combined β-lactam antibiotics and single daily dosing regimens of aminoglycosides for treating serious infections: A meta-analysis
Bibliographic record
Abstract
Combining aminoglycosides with β-lactam antibiotics for treating serious infections has not been associated with reduced mortality in previous meta-analyses. However, the multiple daily aminoglycoside dosing regimen principally used in most of the included studies is inconsistent with current practice. To determine if a combination of an aminoglycoside administered as a single daily dose and a β-lactam antibiotic reduces all-cause mortality in patients compared with β-lactam antibiotic monotherapy. A systematic review and meta-analysis of clinical studies was performed (Prospero registration number #68506). Studies were included if they compared β-lactam antibiotic monotherapy with combined β-lactam and single daily dose aminoglycoside therapy for treating serious infections. Studies investigating multiple daily dosing aminoglycoside regimens, infective endocarditis and febrile neutropaenia were excluded. Study quality was assessed using the PEDro and Newcastle-Ottawa scoring systems. The end points for outcome analyses were 30-day all-cause mortality, clinical cure and nephrotoxicity. Four randomised controlled trials and five retrospective cohort studies were analysed. Compared with β-lactam antibiotic monotherapy, single daily aminoglycoside dosing in combination with β-lactam antibiotics was not associated with reduced mortality compared with β-lactam antibiotic monotherapy (n = 3686, OR 0.82, 95% CI 0.63–1.08, P = 0.10, I2 42%). A subgroup analysis of cohort studies suggested reduced mortality with combination therapy (n = 3563, OR 0.79, 95% CI 0.64–0.99, P = 0.04, I2 32%). No increased risk of nephrotoxicity was identified (n = 1110, OR 1.31, 95% CI 0.83–2.09, P = 0.40, I2 0%). The existing evidence suggests no added survival benefit from a single daily dosing regimen of an aminoglycoside when combined with β-lactam antibiotics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".