Efficacy of Antibiotic Regimens for Meningitis in Young Infants Aged 0–59 Days: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Meningitis is associated with high mortality risk in young infants, yet the optimal treatment regimen is unclear. OBJECTIVES: To systematically evaluate the efficacy of antibiotic regimens to treat meningitis in young infants aged 0 to 59 days on critical clinical outcomes. DATA SOURCES: MEDLINE, Embase, CINAHL, WHO Global Index Medicus, and Cochrane Central Registry of Trials. STUDY SELECTION: We included randomized controlled trials (RCTs) of young infants with meningitis (population) comparing the efficacy of antibiotic regimens (interventions) with alternate regimens (control) on clinical outcomes. DATA EXTRACTION: We extracted data on study characteristics and assessed risk of bias in duplicate. Grading of Recommendations Assessment, Development, and Evaluation was used to assess certainty of evidence. RESULTS: Of 1088 studies screened, only 2 RCTs were identified. They included 168 infants from 5 countries and were conducted between 1976 and 2015. Neither study compared current World Health Organization-recommended regimens. One multisite trial from 4 countries compared intrathecal gentamicin plus systemic ampicillin/gentamicin to systemic ampicillin/gentamicin and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or adverse events (no events in either trial arm). Another trial in India compared a 10-day versus 14-day course of antibiotics and found no difference in mortality (relative risk, 0.88; 95% confidence interval, 0.41-1.53; 1 trial, n = 98, very low certainty of evidence) or other outcomes. CONCLUSIONS: Trial data on the efficacy of antibiotic regimens in young infant meningitis are scarce. Rigorous RCTs are needed to inform recommendations for optimal antibiotic regimens for meningitis treatment in this vulnerable population, particularly within the context of changing epidemiology and increasing antimicrobial resistance.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".